WO2025178525A1 - Improved uplink signal quantization - Google Patents

Abstract

A method performed by a radio unit (RU) for conducting an improved uplink signal quantization is disclosed. For example, the method includes performing channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, and conducting a beamforming and/or equalization operation on in-phase quadrature uplink signal samples associated with the uplink signal. The method further includes performing a scaling operation on the in-phase quadrature (IQ) uplink signal samples based on a determination as to how the uplink signal was originally modulated, and quantizing the scaled IQ uplink signal samples for transmission to a distributed unit via a fronthaul interface.

Description

IMPROVED UPLINK SIGNAL QUANTIZATION

TECHNICAL FIELD

[0001] The present disclosure relates generally to communications, and more particularly to methods and related devices and network nodes performing wireless and/or cellular based communications and signaling.

BACKGROUND

[0002] Open Radio Access Network (O-RAN) Alliance has published various Open Fronthaul specifications (e.g., “O-RAN Control, User and Synchronization Plane Specification 13.0”) that describe a functional split inside the physical layer existing between the O-RAN Distributed Unit (O-DU) and the O-RAN Radio Unit (O-RU). Notably, the O-RAN Open Fronthaul specification defines control-plane (C-plane) messages, synchronization plane (S-plane) messages, and user plane (U-plane) messages exchanged between the O-DU and O- RU. For each version of the specification, there is also an accompanying management plane (M-plane) specification that is detailed in a separate document.

[0003] Different data formats can be used to represent signal samples over a fronthaul interface, such as fixed point or block floating point (BFP) formats. In the uplink, in-phase quadrature (IQ) uplink signal samples are typically quantized using BFP where one exponent is shared over multiple values. For example, one common exponent can be shared for all real and imaginary values representing IQ uplink samples for the 12 resource elements (REs) in one resource block (RB) or one physical resource block (PRB).

[0004] The O-RAN WG4 Work Item Uplink Performance Improvement (ULPI) has identified that uplink performance for massive Multiple Input Multiple Output (MIMO) systems (e.g., massive MIMO typically entails 16 or more receive antennas) can be improved by transferring the uplink DMRS channel estimation and beamforming weight calculation operations from the O-DU to the O-RU. Currently, normative specification work is ongoing to standardize a new beamforming type, i.e., Demodulation Reference Signal based beamforming (DMRS-BF), that targets massive MIMO uplink communication.

[0005] In Fifth Generation (5G) New Radio (NR), the uplink data communicated via a Physical Uplink Shared Channel (PUSCH) can be accomplished using i) Discrete Fourier Transform (DFT) spread Orthogonal Frequency Division Multiplexing (OFDM), like Long Term Evolution (LTE) PUSCH or ii) regular cyclic prefix (CP) OFDM, not unlike that which is used in the downlink. DFT-spread OFDM, which is sometimes referred to as DFT-S-OFDM, or transform-precoded OFDM, has a lower peak-to-average power ratio in the time domain and is therefore typically used for user equipment (UE) devices on the cell border since use of DFT- spread OFDM allows for an increase of the UE’s transmit power without exhibiting clipping in the uplink signal. In the frequency domain, DFT-spread OFDM signals exhibit characteristics resembling close to Gaussian statistics, while CP-OFDM sends individual Quadrature Amplitude Modulation (QAM) constellation points per Resource Element (RE).

SUMMARY

[0006] There currently exist certain challenge(s). For many reasons, network operators often desire to reduce the fronthaul bitrate. However, reducing bit-width of samples can lead to a degradation of precision, which in turn can compromise signaling performance. For example, when quantization noise increases, a higher SINR may be needed on the air interface to achieve the same performance. If a higher SINR cannot be reached, signal data throughput may be reduced.

[0007] Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. For example, the disclosed subject matter applies to a lower-layer split of a base station, where an RU is configured to send quantized uplink samples to a DU over a digital fronthaul interface such as O-RAN Open Fronthaul. Each data stream may contain a single data layer. If multiple layers are received (i.e., from a single UE or multiple UEs), a layer separation operation is likely executed in the RU, e.g., by Zero-Forcing (ZF), Minimum Mean-Square Error (MMSE), MMSE with Interference Rejection Combining (MMSE-IRC), or some other beamforming method. The beamforming can also include equalization, where equalized IQ uplink samples are made ready for demodulation and decoding. An equalized signal can contain constellation points plus some residual(s) due to factors such as noise and errors introduced in the channel estimation.

[0008] In some embodiments, IQ uplink samples for different resource elements (REs) are arranged to (essentially) have constant average power (e.g., average over equiprobable constellation points for the modulation used) and a small phase variation (e.g., a few degrees). [0009] Notably, scaling can be optimized depending on whether the uplink signal is determined to have been sent by a UE via either CP-OFDM or DFT-spread OFDM. Optional saturation is used for CP-OFDM, either by using a signal level close to full scale of the data format, or by artificially saturating large signals, e.g., by limiting the maximum exponent for BFP. [0010] In one embodiment, a method performed by a RU for conducting an improved uplink signal quantization is disclosed. For example, the method includes performing channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, and conducting a beamforming and/or equalization operation on in-phase quadrature uplink signal samples associated with the uplink signal. The method further includes performing a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated (e.g., DFT-spread OFDM vs. CP-OFDM), and quantizing the scaled IQ uplink signal samples for transmission to a distributed unit via a fronthaul interface.

[0011] In one embodiment, RU node for conducting an improved uplink signal quantization is disclosed. The RU node comprises processing circuitry and at least one memory storing instructions executable by the processing circuitry to perform operations to perform (401) channel estimation corresponding to a wireless channel used to receive an uplink signal from a UE; conduct a beamforming and/or equalization operation on IQ uplink signal samples associated with the uplink signal; perform a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated; and quantize (404) the scaled IQ uplink signal samples for transmission to a DU via a fronthaul interface. [0012] In one embodiment, a computer program product comprising a non-transitory computer readable medium is disclosed. Notably, the computer readable medium is configured for storing instructions executable by processing circuitry of a radio unit node, the instructions executed by the processing circuitry to perform operations that include performing channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, and conducting a beamforming and/or equalization operation on in-phase quadrature uplink signal samples associated with the uplink signal. The operations further include performing a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated, and quantizing the scaled IQ uplink signal samples for transmission to a distributed unit via a fronthaul interface. [0013] Certain embodiments may provide one or more of the following technical advantage(s). Notably, uplink signal quantization performance is improved (e.g., a lower bitrate or reduced quantization noise) for CP-OFDM, without degrading performance for DFT- spread OFDM. O-RAN Open Fronthaul specifies that the de-spreading for DFT-spread OFDM is done in the O-DU, after equalization of uplink IQ samples. If equalization is done in the O- RU, it is possible to move the de-spreading operation to the O-RU, which enables optimization of the scaling of IQ samples. When the de-spreading is moved to the O-RU, IQ samples on the fronthaul interface for DFT-spread OFDM will behave as if originally modulated with CP- OFDM by the UE. The distribution of IQ samples will change from complex Gaussian-like to that of a QAM modulation with constellation points plus noise and interference, like in figure 2. If this move of functionality is done, the reduced complexity in the O-DU can enable an O- DU to support more O-RUs. Further, the same benefits for quantization could be achieved for DFT-spread OFDM as for CP-OFDM, for example using the methods in this disclosure. Application of these ideas is not limited to O-RAN but can be applied to any radio equipment controller connected to a radio equipment over a fronthaul connection.

BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate certain non-limiting embodiments of inventive concepts. In the drawings:

[0015] Figure 1 is a block diagram of an example 5G system architecture;

[0016] Figure 2 is an example QAM constellation including constellation points and related equalized IQ samples according to some embodiments;

[0017] Figure 3 is an example QAM constellation including constellation points with Dmax and Amax shown for In-phase (I) coordinates according to some embodiments;

[0018] Figure 4 is a flow chart illustrating example operations for performing an improved uplink signal quantization at a radio unit node according to some embodiments;

[0019] Figure 5 is a flow chart illustrating example operations for performing an improved uplink signal quantization at a radio unit node according to some embodiments;

[0020] Figure 6 is a block diagram of a communication system in accordance with some embodiments;

[0021] Figure 7 is a block diagram of a user device in accordance with some embodiments

[0022] Figure 8 is a block diagram of a network node in accordance with some embodiments;

[0023] Figure 9 is a block diagram of a host computer communicating with a user device in accordance with some embodiments; and

[0024] Figure 10 is a block diagram of a virtualization environment in accordance with some embodiments. DETAILED DESCRIPTION

[0025] Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0026] The disclosed subject matter pertains to methods and systems for improving uplink signal quantization. In some embodiments, the disclosed subject matter is primarily conducted by radio units deployed in 5G communications systems. For illustration and context, Figure 1 depicts an exemplary 5G system architecture 100 that includes a number of network components comprising a radio unit (RU) 102 (also referred to a O-RAN RU, or O-RU), distributed unit (DU) 106 (also referred to a O-RAN DU, or O-DU), a fronthaul connection 104, a mid-haul connection 108, a backhaul connection 112, and a central unit (CU) 110. In some instances, a plurality of RUs 102 are strategically distributed throughout the cellular system coverage area and are responsible for managing radio frequency (RF) communication with mobile subscriber user devices and/or user equipment. RU 102 incorporates antennas and transceivers, facilitating the conversion of digital signals into analog signals for wireless transmission to the UE and vice versa for digitized communication to DU 106. DU 106 is strategically located in the network and is configured to handle baseband processing tasks such as modulation, demodulation, and signal processing for the signals received from RU 102. The fronthaul connection 104 of the system is the network segment responsible for connecting RU 102 to DU 106, thereby facilitating the efficient transport of digitized signals for further processing. As indicated above, the O-RAN Open Fronthaul specification specifies that the despreading for DFT-spread OFDM is done in the O-DU, after equalization of uplink IQ samples. If equalization is done in the O-RU, it is possible to move the de-spreading operation to the O- RU, which enables optimization of the scaling of IQ samples. When the de-spreading is moved to the O-RU, IQ samples on the fronthaul interface for DFT-spread OFDM will behave as if originally modulated with CP-OFDM by the UE. The distribution of IQ samples will change from complex Gaussian-like to that of a QAM modulation with constellation points plus noise and interference, like in Figure 2. If this move of functionality is done, the reduced complexity in the O-DU can enable an O-DU to support more O-RUs. Further, the same benefits for quantization could be achieved for DFT-spread OFDM as for CP-OFDM, for example using the methods in this disclosure.

[0027] In Figure 1, mid-haul connection 108 connects DUs to the CU 110, facilitating the transport of aggregated data. The aggregated data provided to the CU 110 is ultimately communicated to the core network 114 via a backhaul connection 112. In some embodiments, the CU 110 acts as a centralized processing unit, overseeing and controlling the overall operation of the 5G network. It coordinates communication between DUs, manages mobility, and performs critical tasks such as user authentication and encryption. The modular and distributed nature of 5G system architecture 100 enables high-speed, low-latency, and reliable connectivity capabilities for next-generation wireless communication systems.

[0028] In some embodiments, the present disclosure entails the performing of channel estimation for an uplink signal received from a UE, preferably in the RU (e.g., as in O-RAN DMRS-BF). In other embodiments involving slowly varying channels and slowly varying intercell interference, the channel estimation may be performed in the DU if the DU sends channel estimates (e.g., O-RAN CIBF) or beamforming (BF) weights (O-RAN WDBF) to the RU.

[0029] The disclosed subject matter further includes the removing, or substantially reducing, the average IQ uplink signal sample magnitude and phase dependency on the wireless channel (and any signal chain imperfections) by conducting beamforming and/or equalization in the RU using beamforming weights based on channel estimates. Equalization may be preferred, but the methods disclosed herein can also provide some amount of gain for beamforming if the BF weights are not normalized to a constant gain but instead determined to be proportional to the inverse of the channel. If multiple uplink MIMO layers are received, the MIMO layers should be separated during the beamforming and/or equalization operation. It is also preferred to remove any frequency offset since frequency offsets cause phase rotation of the constellation. After such beamforming and/or equalization, the root mean square (RMS) value of the received signal is essentially constant, at least for high or infinite signal to interference plus noise ratio (SINR), i.e., low noise or no noise present.

[0030] Notably, the present disclosure includes adapting the scaling of IQ samples (e.g., before quantization) to improve quantization performance (e.g., allow fewer bits or reduce SNR degradation). If it is not known whether CP-OFDM or DFT-spread OFDM is being used, the scaling should give sufficient headroom for the high crest factor (e.g., peak to average) of DFT- spread OFDM. The high crest factor is typically ~12 dB, which means that the average signal power needs corresponding back-off below full scale to avoid overflow, e.g., two steps down from a maximum exponent with BFP, or two most-significant bits down for fixed point. At the same time, the disclosed subject matter can optimize mantissa utilization for CP-OFDM by controlling where in relation to the constellation points any BFP exponent will increase. As will be shown, a suitable value for the level of the wanted signal at high SINR can be -13.8 dBFS or -14 dBFS. [0031] If the uplink signal to be quantized is determined to have been sent by the UE via regular CP-OFDM or DFT-spread OFDM, the scaling can be further improved. In some embodiments, the uplink signal quantization determination may be conducted based on knowledge of configuration (e.g., only one type used for a particular RU or carrier), from statistics of the signal, or by information conveyed from the DU (e.g., per slot). An example of the latter option is to use information related to the DMRS configuration sent from the DU to the RU in the C-plane since there are differences in the DMRS configuration for the two types of OFDM, which might include an explicit indication such as a flag, or implicit information based on some difference in DMRS configuration, e.g., the use of low peak-to-average power ratio DMRS sequences. There may also be explicit information that states which OFDM scheme is used.

[0032] More specifically, the disclosed subject matter includes a determination step for ascertaining whether CP-OFDM or DFT-spread OFDM is used for the uplink signal (i.e., sent by the UE), and a subsequent scaling decision made based on the OFDM-type determination. In some embodiments where the type of OFDM is not known, the RU can be configured to select a scaling that is appropriate and/or relatively beneficial for both OFDM types, e.g., close to -14 dBFS.

[0033] However, if the OFDM type is determined to be CP-OFDM, a scaling that gives best performance can be selected (e.g., close to -2 dBFS) by the RU. Alternatively, the RU may use -14 dBFS and limit the exponent such that values larger than -12 dBFS are saturated.

[0034] For example, the IQ samples can be scaled by the RU such that either the full scale of the data format (e.g., fixed point or BFP), or the full scale of the mantissa (for BFP), is identical to or slightly larger than the magnitude of an outermost constellation point of a QAM constellation (see Figure 2 and description below). Values with a magnitude larger than the full scale of the data format are saturated to the largest magnitude value with same sign (e.g., no overflow). With saturation, best performance can be achieved with a back-off of around 2 dB below full scale. This works both for BFP and fixed point (and other formats). When BFP is used, good performance is also achieved for a back-off of 2-3 dB + an integer multiple of 6 dB (i.e., different BFP exponent levels), e.g., -8 dB or -14 dB.

[0035] If the OFDM type is instead determined to be DFT-spread OFDM, the RU can select a scaling that has sufficient headroom for the Gaussian-like peak-to-average power ratio. Notably, a true Gaussian-distributed signal has infinite peak-to-average power ratio but the higher the peak level, the lower the probability, which means that infinite time is needed to measure. Practical signals like OFDM do not have an infinite crest factor, but the maximum peak has very low probability and is difficult to measure. In the context of the present disclosure, the terms ‘crest factor’ or ‘peak-to-average power ratio’ refer to a value that is exceeded only a very small percentage of time, e.g., 0.01% or 0.001%. For example, IQ samples may be scaled by the RU to leave room for a Gaussian-like peak-to-average power ratio, e.g., a 12 dB backoff (or more) from the full scale of the data format (e.g., -12 dBFS).

[0036] To avoid a change of the signal level on the interface between the two OFDM types, it is possible to use, e.g., 14-15 dB back-off in both cases, and saturate the CP-OFDM signal level before quantization, or artificially limit the exponent to a few steps lower than the maximum when CP-OFDM is used. Limiting the exponent range to a level 2 steps below the maximum means that saturation occurs for a 12 dB lower level. Thus, -14 dBFS with such saturation corresponds to a back-off of 2-3 dB with saturation, but maintains the signal level of the -14 dBFS setting.

[0037] In some embodiments, additional scaling of samples with an SINR-dependent scale factor can optionally be performed such that the RMS value of IQ samples does not increase for low SINR (due to noise and interference). Such scaling, as exemplified below, is inherent in MMSE equalization. It seems natural to remove such scaling prior to performing front haul quantization to achieve a constant level of the desired signal. However, the disclosed subject matter demonstrates why it is beneficial to retain this SINR-dependent scale factor for MMSE- IRC equalization, and further apply the factor for other equalization methods (if the factor is not included). By avoiding an increase of RMS value (or e.g., IQ power, or variance) at low SINR, overflow in the fronthaul interface data format can be avoided, without using very large back-off of the signal level on the interface. Overflow can degrade performance, especially for DFT-spread OFDM. It can be shown that with scaling by G_t, the total variance of IQ samples (e.g., desired signal plus noise and interference) will be equal to G_t < 1 (assuming no errors in channel estimation) where G_t is defined here as (but not limited to):

^{Gi =} 1 + SINRt'

[0038] Lastly, the IQ samples are quantized after scaling, and sent over the fronthaul interface from the RU to the DU.

[0039] For sake of illustration, a 64-QAM constellation 200 and equalized uplink samples will be used as example to explain the disclosed methodology. An example ideal noise-free QAM constellation 200 is depicted in Figure 2 where 64-QAM constellation points 2011...64 (i.e., small circles) and corresponding equalized IQ uplink signal samples 2021 . 64 including noise (i.e., gray dots/splotches) are arranged within. For example, the QAM constellation 200 has unit energy (e.g., RMS value 1.0 over equiprobable constellation points) as defined in clause 5.1 of “5GNR Physical Channels and modulation,” and the equalized IQ uplink signal samples 2021 . 64 have an RMS value close to 1.

[0040] With perfect channel estimation the desired signal will exhibit an RMS value equal to 1.0, but the noise level increases the total RMS. However, for high SINR (e.g., 24 dB as shown in Figure 2), the RMS increase due to noise is negligible. Further, if optional scaling by Gi is performed, the RMS value will also be less than or equal to 1 for low SINR (e.g., high noise levels).

[0041] In some embodiments, quantization is assumed to be performed with one value for the T part and one value for the ‘Q’ part. Further, a typical BFP scheme may be used where the mantissa range is mapped to a semi-open range [-1.0, 1.0[ for some exponent lower than the maximum exponent. With a common exponent for 12 resource elements (REs), such an exponent would have to be increased as soon as any of the REs utilizes one of the constellation points in the outer edge (e.g., see edges 215-216). Since there are many points at the outer edge, the probability is close to 1 that at least one of the 12 REs in a PRB is located on the outer edge. Thus, the exponent will be increased and the mantissa for the higher exponent will cover a range of [-2, 2], However, there are almost no samples with |I|,[Q| > 1.2, which indicates that the mantissa will only be utilized to -60%. As such, the signal is degraded -4.4 dB relative to the quantization noise since the latter depends on the step size and not the mantissa utilization. [0042] Performance may be improved by adjusting the scaling such that the exponent increase occurs outside the outer constellation points. Far enough outside so that exponent increases have a low probability, but not so far outside that the mantissa utilization is reduced. In some embodiments, the optimal scaling may be formulated as an optimization problem that can be solved if the modulation order and SINR are known. Another alternative is to saturate all |I|,|Q| samples at some distance outside the outermost constellation points.

[0043] If the modulation order is not known by the O-RU, or if it is not necessary to have the optimal scaling (i.e., sufficiently good scaling is acceptable), the following approach can be used.

[0044] For -Q AM modulation generated with a minimum distance ( ) between adjacent constellation points, it is known that the average constellation energy (E) is: [0045] In some examples, d=2, which results in £=42 for 64-QAM (i.e., A/=64). The formula in “5G NR Physical Channels and modulation” for 64-QAM divides the possible I and Q values of {-7, -5, -3, -1, +1, +3, +5, +7} by A42 to get average energy equal to one for the constellation, like in Figure 2.

[0046] In some embodiments, the largest magnitude of |I|,|Q| for a unit-energy A/-QAM constellation is defined as:

D_max,M = max(max(|7|) , max

[0047] Further, A_max,M is defined as: where A_maxM equals D_max,_M ⁺ 2V ^{i e}” ^D max,M plus half the distance between two adjacent points. This is the outer limit of the constellation’s |I| or |Q| if it is assumed that each constellation point (including the ones at the edge) has an equally sized quantization interval around it. As the limit when AT approaches infinity, this results in:

If the coordinates of the constellation can be divided by D_max,M, the outermost constellation points would have |I|=1 and/or |Q|=1, but the BFP exponent would be increased by noise unless saturation is used. If instead the coordinates of the constellation are divided by AmaxM, the probability of increasing exponent is reduced, which is beneficial for BFP. If the modulation order is not known, A_{max oo} can instead be used to divide the constellation coordinates.

[0048] As shown in Table 1 below, the fourth column and fifth column demonstrate relatively similar results. Dividing by A_{max oo} (or multiplying by its inverse) will ensure that coordinates for all the constellation points will have |I|,|Q|<1. The rightmost (i.e., last) column shows that the outer limit of the outermost constellation point’s quantization interval is not entirely within the range [-1, 1[, especially for low AT. Since AT is typically selected by link adaptation based on SINR (e.g., for the same code rate, different modulation orders should have a similar likelihood ratio on the decision border between adjacent points), it may mean that low-order modulations have a slightly higher probability of increasing the exponent. If this is problematic, the scale factor can be modified slightly.

TABLE 1

[0049] The limits described above are illustrated in the QAM constellation 300 depicted in Figure 3. If the I,Q values are multiplied by 1/A_{max oo} , the constellation points 301 corresponding to the dash-dotted lines 310 would end up at ±0.8819, and the dashed line would end up at ±1.0079 which means that almost all IQ samples 202 (e.g., gray dots) in Figure 2 would end up in the interval [+1, -1 [, and that only a few samples would be truncated at full scale. If samples would be further scaled down by a power of two (e.g., multiples of 6dB), an exponent increase would only be triggered with a rather small probability. A more aggressive scheme using saturation could scale so that the dash-dotted line is barely inside the interval [+1, -1[ (or this interval scaled down by a power of two) but this might affect demodulation performance and will not work well without saturation.

[0050] As mentioned earlier, for low-order modulation and correspondingly lower SINR, the probability of having an IQ signal sample with |I| or |Q| outside A_{max oo} increases when the

IQ signal samples are multiplied by - since e.g., A_{max 4} substantially larger than A_{max oo}

^max,oo as can be seen by the ratio However, this problem may be mitigated without knowledge ^max.oo of the modulation order by further scaling by G_t from MMSE-IRC equalization, or by applying Gi for other equalization methods if not included. For an equal code rate, there will be approximately 6 dB difference in required SINR for each quadrupling of constellation size M. For SINR = 8 dB (e.g., QPSK with high code rate), G_L = 0.8632, while for SINR = 20 dB (e.g., 64-QAM with high code rate), G_t = 0.9901. With this example, the following is obtained: 967 0.9979

[0051] Thus, the quantization intervals around the outermost points are inside the desired limit of 1.0 even for low-order modulation while there is almost no change for high-order modulation (e.g., high SINR). This demonstrates that when this additional scaling is applied, the probability of exponent increase (e.g., mantissa exceeding 1.0) is quite similar for the different modulation orders as long as link adaptation works properly.

[0052] In link level simulations for CP-OFDM with MMSE-IRC equalization (including scaling by Gj) and CDL-B (Clustered Delay Line type B) channel model and the additional scaling by G_t included, it was seen that an IQ level for CP-OFDM of about -2 dBFS provided good results as seen in Table 2 below, with the lowest SNR degradation for a given data format.

For comparison, the proposed multiplier of - = - , optimized for infinite AT corresponds

^max.x 3 to -1.8 dBFS, which is close to the tested -2 dBFS value that gave good results for CP-OFDM. This confirms that the disclosed method is effective and that it is not sensitive to an exact scale

1 11 value. Further, a multiplier of - = - optimized for QPSK, corresponds to -3 dBFS in max,4 2

Table 2. Here, full scale (FS) of the data format is assumed to represent the |I| or |Q| value 1.0. A FS value of -12 dB corresponds to the maximum mantissa magnitude, but an exponent that is two integer steps below the maximum value. Such a dBFS value or lower may be needed for DFTs-spread OFDM. From the results, it is seen that if the type of OFDM is determined to be CP-OFDM, one should use a value close to -2 dBFS. If the type of OFDM is not known, one should use a value close to -14 dBFS, or perhaps -15 dBFS. Although results are only shown for CP-OFDM, all levels at or below -12 dBFS in Table 2 should be acceptable for DFT-spread OFDM as long as BFP is used with a sufficient number of exponent levels. For fixed point, precision will be reduced by downscaling, which may lead to some additional consideration.

TABLE 2

[0053] The methods described can be implemented in O-RAN. Existing O-RAN uplink in CUS specification version 13.00 uses a fixed gain in dB from the antenna to the interface, which means that IQ power will vary with received signal power from the UE and it will be difficult to optimize the quantization. If the O-DU instead can configure the scaling of IQ samples, e.g., as a dB value below full scale of the interface data format, selection of proper scale factor could give some benefits without any further change of the O-RU. In some embodiments, this scaling configuration may be accomplished via an “eq-scale-offset-config” described in clause 8.1.3.4 of CUS-specification version 16.01 (and/or newer). However, the O-RU may select (and report) an approximation of this value in the parameter “eq-scale-offset- used”. If, for example, the O-RU only supports scaling with integer multiples of 6 dB, it is not possible to use the best scale values, such as values close to -1.8 dB or -13.8 dB. Further benefits are possible if support is added for the additional scaling of IQ samples by G_t as defined. In some embodiments, this additional scaling is referred to as “Scaling Function 1” and is part of the CUS-specification version 16.01. An O-RU supporting DMRS-BF-EQ must support either Scaling Function 1 or Scaling Function 2 (e.g., ‘unity gain’). An O-DU supporting DMRS-BF-EQ must support both scaling functions.

[0054] There might be impact on O-RAN WG4 specifications (CUS-plane and M-plane), e.g., regarding the optional scaling by Gt, and regarding how to configure a suitable RMS level for IQ samples. The saturation part mentioned might be possible to implement as implementation specific method.

[0055] Figure 4 is a flow chart illustrating method 400 depicting exemplary operations for performing improved uplink signal quantization according to one embodiment.

Operations of a RU node, which in some embodiments may be implemented using the network node structure of the block diagram of Figure 8, will now be discussed with reference to the flow chart of Figure 4 according to some embodiments. For example, one or more modules may be stored in memory 804 of Figure 8, and these modules may provide instructions so that when the instructions of a module are executed by respective processing circuitry 802, the RU performs respective operations of the method 400.

[0056] In block 401, the method 400 includes performing channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment. In some embodiments, the channel estimation is performed in the RU. In some embodiments, the determination is performed in a DU that is communicatively connected to the RU.

[0057] In block 402, the method 400 includes conducting a beamforming and/or equalization operation on IQ uplink signal samples associated with the uplink signal. In some embodiments, the dependency of an average magnitude and/or phase rotation of the IQ uplink signal samples on the wireless channel is removed or reduced at the RU via the beamforming and/or equalization operation.

[0058] In block 403, the method 400 includes performing a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated. In some embodiments, the RU is configured to select the scaling operation from among a plurality of scaling operations based on whether the uplink signal was modulated via CP-OFDM or DFT spread OFDM. In some embodiments, performing the scaling operation (e.g., a scale offset) includes determining if the uplink signal was originally modulated via CP- OFDM or DFT-spread OFDM. In some embodiments, if the uplink signal is determined (e.g., by a DU that is communicatively connected to the RU) to be originally modulated via CP- OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or the maximum magnitude of a BFP data format for a specific exponent value is identical to or slightly larger than a magnitude of an outermost constellation point in a QAM constellation including the IQ uplink signal samples. In some embodiments, a signal level of the uplink signal originally modulated via CP-OFDM is saturated prior to signal quantization. In some embodiments, if the uplink signal is determined (e.g., by the DU) to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio. In some embodiments, the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a SINR dependent scale factor such that the RMS value of each of the IQ uplink signal samples does not increase for a low SINR. In some embodiments, the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a SINR dependent scale factor such that the variance of IQ samples (signal plus noise and interference) does not increase for a low SINR. [0059] In block 404, the method 400 includes quantizing the scaled IQ uplink signal samples for transmission to a distributed unit via a fronthaul interface.

[0060] Figure 5 is a flow chart illustrating method 400 depicting exemplary operations for performing improved uplink signal quantization according to one embodiment.

Operations of a RU node, which in some embodiments may be implemented using the network node structure of the block diagram of Figure 8, will now be discussed with reference to the flow chart of Figure 5 according to some embodiments. For example, one or more modules may be stored in memory 804 of Figure 8, and these modules may provide instructions so that when the instructions of a module are executed by respective processing circuitry 802, the RU performs respective operations of the method 400.

[0061] In block 501, the method 500 includes performing channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment. In some embodiments, the channel estimation is performed in the RU.

[0062] In block 502, the method 500 includes conducting a beamforming and/or equalization operation on IQ uplink signal samples associated with the uplink signal. In some embodiments, the dependency of an average magnitude and/or phase of the IQ uplink signal samples on the wireless channel is removed or reduced via the beamforming and/or equalization operation.

[0063] In block 503, the method 500 includes performing a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated. In some embodiments, performing the scaling operation (e.g., a scale offset) includes determining if the uplink signal was originally modulated via CP-OFDM or DFT- spread OFDM. In some embodiments, if the uplink signal is determined (e.g., by a DU that is communicatively connected to the RU) to be originally modulated via CP-OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or a BFP data format is identical to or slightly larger than a magnitude of an outermost constellation point in a QAM constellation including the IQ uplink signal samples. In some embodiments, a signal level of the uplink signal originally modulated via CP-OFDM is saturated prior to signal quantization. In some embodiments, if the uplink signal is determined (e.g., by the DU) to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio.

[0064] In block 504, the method 500 includes subjecting the IQ uplink signal samples to an additional scaling operation that utilizes a SINR dependent scale factor such that the RMS value of each of the IQ uplink signal samples does not increase for a low SINR. Without the additional scaling, the variance of the sum of the signal, interference, and noise will increase at low SINR, which can lead to, e.g., overflow of the quantization. In some embodiments, block 504 may be performed immediately prior to the execution of block 503 (instead of after block 503 as depicted in Figure 5).

[0065] In block 505, the method 500 includes quantizing the scaled IQ uplink signal samples for transmission to a distributed unit via a fronthaul interface.

[0066] Figure 6 shows an example of a communication system 600 in accordance with some embodiments.

[0067] In the example, the communication system 600 includes a telecommunication network 602 that includes an access network 604, such as a radio access network (RAN), and a core network 606, which includes one or more core network nodes 608. The access network 604 includes one or more access network nodes, such as network nodes 610a and 610b (one or more of which may be generally referred to as network nodes 610), or any other similar 3^rd Generation Partnership Project (3GPP) access nodes or non-3GPP access points. Moreover, as will be appreciated by those of skill in the art, a network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunication network 602 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 602 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other nodes to implement one or more functionalities of any node in the telecommunication network 602, including one or more network nodes 610 and/or core network nodes 608.

[0068] Examples of an ORAN network node include an open radio unit (O-RU), an open distributed unit (O-DU), an open central unit (O-CU), including an O-CU control plane (O- CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller (near-real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). The network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an Al, Fl, Wl, El, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface.

[0069] Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an O-2 interface defined by the O- RAN Alliance or comparable technologies. The network nodes 610 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs 612a, 612b, 612c, and 612d (one or more of which may be generally referred to as UEs 612) to the core network 606 over one or more wireless connections.

[0070] Example wireless communications over a wireless connection include transmitting and/or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and/or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system 600 may include any number of wired or wireless networks, network nodes, UEs, and/or any other components or systems that may facilitate or participate in the communication of data and/or signals whether via wired or wireless connections. The communication system 600 may include and/or interface with any type of communication, telecommunication, data, cellular, radio network, and/or other similar type of system.

[0071] The UEs 612 may be any of a wide variety of communication devices, including wireless devices arranged, configured, and/or operable to communicate wirelessly with the network nodes 610 and other communication devices. Similarly, the network nodes 610 are arranged, capable, configured, and/or operable to communicate directly or indirectly with the UEs 612 and/or with other network nodes or equipment in the telecommunication network 602 to enable and/or provide network access, such as wireless network access, and/or to perform other functions, such as administration in the telecommunication network 602.

[0072] In the depicted example, the core network 606 connects the network nodes 610 to one or more hosts, such as host 616. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network 606 includes one more core network nodes (e.g., core network node 608) that are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, network nodes, and/or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node 608. Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-concealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and/or a User Plane Function (UPF).

[0073] The host 616 may be under the ownership or control of a service provider other than an operator or provider of the access network 604 and/or the telecommunication network 602, and may be operated by the service provider or on behalf of the service provider. The host 616 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded audio/video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0074] As a whole, the communication system 600 of Figure 6 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and/or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (WiFi); and/or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, LiFi, and/or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox.

[0075] In some examples, the telecommunication network 602 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network 602 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 602. For example, the telecommunications network 602 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing Enhanced Mobile Broadband (eMBB) services to other UEs, and/or Massive Machine Type Communication (mMTC)/Massive loT services to yet further UEs.

[0076] In some examples, the UEs 612 are configured to transmit and/or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network 604 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 604. Additionally, a UE may be configured for operating in single- or multi-RAT or multi-standard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LTE, i.e., being configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network) New Radio - Dual Connectivity (EN- DC).

[0077] In the example, the hub 614 communicates with the access network 604 to facilitate indirect communication between one or more UEs (e.g., UE 612c and/or 612d) and network nodes (e.g., network node 610b). In some examples, the hub 614 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 614 may be a broadband router enabling access to the core network 606 for the UEs. As another example, the hub 614 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes 610, or by executable code, script, process, or other instructions in the hub 614. As another example, the hub 614 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub 614 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub 614 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 614 then provides to the UE either directly, after performing local processing, and/or after adding additional local content. In still another example, the hub 614 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0078] The hub 614 may have a constant/persistent or intermittent connection to the network node 610b. The hub 614 may also allow for a different communication scheme and/or schedule between the hub 614 and UEs (e.g., UE 612c and/or 612d), and between the hub 614 and the core network 606. In other examples, the hub 614 is connected to the core network 606 and/or one or more UEs via a wired connection. Moreover, the hub 614 may be configured to connect to an M2M service provider over the access network 604 and/or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 610 while still connected via the hub 614 via a wired or wireless connection. In some embodiments, the hub 614 may be a dedicated hub - that is, a hub whose primary function is to route communications to/from the UEs from/to the network node 610b. In other embodiments, the hub 614 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node 610b, but which is additionally capable of operating as a communication start and/or end point for certain data channels.

[0079] Figure 7 shows a UE 700 in accordance with some embodiments. As used herein, a UE refers to a device capable, configured, arranged and/or operable to communicate wirelessly with network nodes and/or other UEs. Examples of a UE include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage device, playback appliance, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), smart device, wireless customer-premise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded/integrated wireless device, etc. Other examples include any UE identified by the 3rd Generation Partnership Project (3GPP), including a narrow band internet of things (NB-IoT) UE, a machine type communication (MTC) UE, and/or an enhanced MTC (eMTC) UE. [0080] A UE may support device-to-device (D2D) communication, for example by implementing a 3 GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle- to-everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and/or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0081] The UE 700 includes processing circuitry 702 that is operatively coupled via a bus 704 to an input/output interface 706, a power source 708, a memory 710, a communication interface 712, and/or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in Figure 7. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0082] The processing circuitry 702 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory 710. The processing circuitry 702 may be implemented as one or more hardware-implemented state machines (e.g., in discrete logic, field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs, general -purpose processors, such as a microprocessor or digital signal processor (DSP), together with appropriate software; or any combination of the above. For example, the processing circuitry 702 may include multiple central processing units (CPUs). [0083] In the example, the input/output interface 706 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and/or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into the UE 700. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g., a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0084] In some embodiments, the power source 708 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricity outlet), photovoltaic device, or power cell, may be used. The power source 708 may further include power circuitry for delivering power from the power source 708 itself, and/or an external power source, to the various parts of the UE 700 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 708. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 708 to make the power suitable for the respective components of the UE 700 to which power is supplied.

[0085] The memory 710 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 710 includes one or more application programs 714, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 716. The memory 710 may store, for use by the UE 700, any of a variety of various operating systems or combinations of operating systems.

[0086] The memory 710 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD- DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a USIM and/or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 710 may allow the UE 700 to access instructions, application programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory 710, which may be or comprise a device-readable storage medium.

[0087] The processing circuitry 702 may be configured to communicate with an access network or other network using the communication interface 712. The communication interface 712 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 722. The communication interface 712 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another UE or a network node in an access network). Each transceiver may include a transmitter 718 and/or a receiver 720 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 718 and receiver 720 may be coupled to one or more antennas (e.g., antenna 722) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0088] In the illustrated embodiment, communication functions of the communication interface 712 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented in according to one or more communication protocols and/or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol/intemet protocol (TCP/IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0089] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 712, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0090] As another example, a UE comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0091] A UE, when in the form of an Internet of Things (loT) device, may be a device for use in one or more application domains, these domains comprising, but not limited to, city wearable technology, extended industrial application and healthcare. Non-limiting examples of such an loT device are a device which is or which is embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door/window sensor, a flood/moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a head-mounted display for Augmented Reality (AR) or Virtual Reality (VR), a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an loT device comprises circuitry and/or software in dependence of the intended application of the loT device in addition to other components as described in relation to the UE 700 shown in Figure 7.

[0092] As yet another specific example, in an loT scenario, a UE may represent a machine or other device that performs monitoring and/or measurements, and transmits the results of such monitoring and/or measurements to another UE and/or a network node. The UE may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3GPP NB-IoT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and/or reporting on its operational status or other functions associated with its operation. [0093] In practice, any number of UEs may be used together with respect to a single use case. For example, a first UE might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second UE that is a remote controller operating the drone. When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g., by controlling an actuator) to increase or decrease the drone’s speed. The first and/or the second UE can also include more than one of the functionalities described above. For example, a UE might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.

[0094] Figure 8 shows a network node 800 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and/or operable to communicate directly or indirectly with a UE and/or with other network nodes or equipment, in a telecommunication network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e g., O-RU, O-DU, O-CU).

[0095] Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. A base station may be a relay node or a relay donor node controlling a relay. A network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node) and/or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0096] Other examples of network nodes include multiple transmission point (multi-TRP) 5G access nodes, multi -standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi -cell/ multi cast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and/or Minimization of Drive Tests (MDTs).

[0097] The network node 800 includes a processing circuitry 802, a memory 804, a communication interface 806, and a power source 808. The network node 800 may be composed of multiple physically separate components (e.g., a NodeB component and a RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the network node 800 comprises multiple separate components (e.g., BTS and BSC components), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, the network node 800 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory 804 for different RATs) and some components may be reused (e.g., a same antenna 810 may be shared by different RATs). The network node 800 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 800, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node 800.

[0098] The processing circuitry 802 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and/or encoded logic operable to provide, either alone or in conjunction with other network node 800 components, such as the memory 804, to provide network node 800 functionality.

[0099] In some embodiments, the processing circuitry 802 includes a system on a chip (SOC). In some embodiments, the processing circuitry 802 includes one or more of radio frequency (RF) transceiver circuitry 812 and baseband processing circuitry 814. In some embodiments, the radio frequency (RF) transceiver circuitry 812 and the baseband processing circuitry 814 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry 812 and baseband processing circuitry 814 may be on the same chip or set of chips, boards, or units. [0100] The memory 804 may comprise any form of volatile or non-volatile computer- readable memory including, without limitation, persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and/or any other volatile or non-volatile, non-transitory device-readable and/or computerexecutable memory devices that store information, data, and/or instructions that may be used by the processing circuitry 802. The memory 804 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and/or other instructions capable of being executed by the processing circuitry 802 and utilized by the network node 800. The memory 804 may be used to store any calculations made by the processing circuitry 802 and/or any data received via the communication interface 806. In some embodiments, the processing circuitry 802 and memory 804 is integrated.

[0101] The communication interface 806 is used in wired or wireless communication of signaling and/or data between a network node, access network, and/or UE. As illustrated, the communication interface 806 comprises port(s)/terminal(s) 816 to send and receive data, for example to and from a network over a wired connection. The communication interface 806 also includes radio front-end circuitry 818 that may be coupled to, or in certain embodiments a part of, the antenna 810. Radio front-end circuitry 818 comprises filters 820 and amplifiers 822. The radio front-end circuitry 818 may be connected to an antenna 810 and processing circuitry 802. The radio front-end circuitry may be configured to condition signals communicated between antenna 810 and processing circuitry 802. The radio front-end circuitry 818 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry 818 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 820 and/or amplifiers 822. The radio signal may then be transmitted via the antenna 810. Similarly, when receiving data, the antenna 810 may collect radio signals which are then converted into digital data by the radio front-end circuitry 818. The digital data may be passed to the processing circuitry 802. In other embodiments, the communication interface may comprise different components and/or different combinations of components.

[0102] In certain alternative embodiments, the network node 800 does not include separate radio front-end circuitry 818, instead, the processing circuitry 802 includes radio front-end circuitry and is connected to the antenna 810. Similarly, in some embodiments, all or some of the RF transceiver circuitry 812 is part of the communication interface 806. In still other embodiments, the communication interface 806 includes one or more ports or terminals 816, the radio front-end circuitry 818, and the RF transceiver circuitry 812, as part of a radio unit (not shown), and the communication interface 806 communicates with the baseband processing circuitry 814, which is part of a digital unit (not shown). [0103] The antenna 810 may include one or more antennas, or antenna arrays, configured to send and/or receive wireless signals. The antenna 810 may be coupled to the radio front-end circuitry 818 and may be any type of antenna capable of transmitting and receiving data and/or signals wirelessly. In certain embodiments, the antenna 810 is separate from the network node 800 and connectable to the network node 800 through an interface or port.

[0104] The antenna 810, communication interface 806, and/or the processing circuitry 802 may be configured to perform any receiving operations and/or certain obtaining operations described herein as being performed by the network node. Any information, data and/or signals may be received from a UE, another network node and/or any other network equipment. Similarly, the antenna 810, the communication interface 806, and/or the processing circuitry 802 may be configured to perform any transmitting operations described herein as being performed by the network node. Any information, data and/or signals may be transmitted to a UE, another network node and/or any other network equipment.

[0105] The power source 808 provides power to the various components of network node 800 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 808 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 800 with power for performing the functionality described herein. For example, the network node 800 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 808. As a further example, the power source 808 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.

[0106] Embodiments of the network node 800 may include additional components beyond those shown in Figure 8 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and/or any functionality necessary to support the subject matter described herein. For example, the network node 800 may include user interface equipment to allow input of information into the network node 800 and to allow output of information from the network node 800. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 800.

[0107] Figure 9 is a block diagram of a host 900, which may be an embodiment of the host 616 of Figure 6, in accordance with various aspects described herein. As used herein, the host 900 may be or comprise various combinations hardware and/or software, including a standalone server, a blade server, a cloud-implemented server, a distributed server, a virtual machine, container, or processing resources in a server farm. The host 900 may provide one or more services to one or more UEs.

[0108] The host 900 includes processing circuitry 902 that is operatively coupled via a bus 904 to an input/output interface 906, a network interface 908, a power source 910, and a memory 912. Other components may be included in other embodiments. Features of these components may be substantially similar to those described with respect to the devices of previous figures, such as Figures 7 and 8, such that the descriptions thereof are generally applicable to the corresponding components of host 900.

[0109] The memory 912 may include one or more computer programs including one or more host application programs 914 and data 916, which may include user data, e.g., data generated by a UE for the host 900 or data generated by the host 900 for a UE. Embodiments of the host 900 may utilize only a subset or all of the components shown. The host application programs 914 may be implemented in a container-based architecture and may provide support for video codecs (e.g., Versatile Video Coding (VVC), High Efficiency Video Coding (HEVC), Advanced Video Coding (AVC), MPEG, VP9) and audio codecs (e.g., FL AC, Advanced Audio Coding (AAC), MPEG, G.711), including transcoding for multiple different classes, types, or implementations of UEs (e.g., handsets, desktop computers, wearable display systems, heads-up display systems). The host application programs 914 may also provide for user authentication and licensing checks and may periodically report health, routes, and content availability to a central node, such as a device in or on the edge of a core network. Accordingly, the host 900 may select and/or indicate a different host for over-the-top services for a UE. The host application programs 914 may support various protocols, such as the HTTP Live Streaming (HLS) protocol, Real-Time Messaging Protocol (RTMP), Real-Time Streaming Protocol (RTSP), Dynamic Adaptive Streaming over HTTP (MPEG-DASH), etc.

[0110] Figure 10 is a block diagram illustrating a virtualization environment 1000 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments 1000 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, UE, core network node, or host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment 1000 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface.

[0111] Applications 1002 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and/or benefits of some of the embodiments disclosed herein.

[0112] Hardware 1004 includes processing circuitry, memory that stores software and/or instructions executable by hardware processing circuitry, and/or other hardware devices as described herein, such as a network interface, input/output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers 1006 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 1008a and 1008b (one or more of which may be generally referred to as VMs 1008), and/or perform any of the functions, features and/or benefits described in relation with some embodiments described herein. The virtualization layer 1006 may present a virtual operating platform that appears like networking hardware to the VMs 1008.

[0113] The VMs 1008 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 1006. Different embodiments of the instance of a virtual appliance 1002 may be implemented on one or more of VMs 1008, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.

[0114] In the context of NFV, a VM 1008 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 1008, and that part of hardware 1004 that executes that VM, be it hardware dedicated to that VM and/or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs 1008 on top of the hardware 1004 and corresponds to the application 1002. [0115] Hardware 1004 may be implemented in a standalone network node with generic or specific components. Hardware 1004 may implement some functions via virtualization. Alternatively, hardware 1004 may be part of a larger cluster of hardware (e.g., such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration 1010, which, among others, oversees lifecycle management of applications 1002. In some embodiments, hardware 1004 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system 1012 which may alternatively be used for communication between hardware nodes and radio units. [0116] Although the computing devices described herein (e.g., UEs, network nodes, hosts) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and/or software needed to perform the tasks, features, functions and methods disclosed herein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and/or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and/or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.

[0117] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer- readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer- readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and/or by end users and a wireless network generally.

EMBODIMENTS

1. A method performed by a radio unit, RU, for conducting an improved uplink signal quantization, the method comprising: performing (401) channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, UE; conducting (402) a beamforming and/or equalization operation on in-phase quadrature, IQ, uplink signal samples associated with the uplink signal; performing (403) a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated; and quantizing (404) the scaled IQ uplink signal samples for transmission to a distributed unit, DU, via a fronthaul interface.

2. The method of embodiment 1, wherein the channel estimation is performed in the RU.

3. The method of embodiment 1, wherein dependency of an average magnitude and/or phase of the IQ uplink signal samples on the wireless channel is removed or reduced via the beamforming and/or equalization operation.

4. The method of embodiment 1, wherein performing the scaling operation includes determining if the uplink signal was originally modulated via cyclic prefix orthogonal frequency division multiplexing, CP-OFDM, or discrete Fourier transform, DFT, spread OFDM.

5. The method of embodiment 4, wherein if the uplink signal is determined to be originally modulated via CP-OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or a BFP data format is identical to or slightly larger than a magnitude of an outermost constellation point in a Quadrature Amplitude Modulation, QAM, constellation including the IQ uplink signal samples.

6. The method of embodiment 5, wherein a signal level of the uplink signal originally modulated via CP-OFDM is saturated prior to signal quantization.

7. The method of embodiment 4, wherein if the uplink signal is determined to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio.

8. The method of embodiment 1, wherein the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a signal to interference plus noise ratio, SINR, dependent scale factor such that the root mean square, RMS, value of each of the IQ uplink signal samples does not increase for a low SINR.

9. A radio unit, RU, node for conducting an improved uplink signal quantization , the RU node comprising: processing circuitry; and at least one memory storing instructions executable by the processing circuitry to perform operations to: perform (401) channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, UE; conduct (402) a beamforming and/or equalization operation on in-phase quadrature, IQ, uplink signal samples associated with the uplink signal; perform (403) a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated; and quantize (404) the scaled IQ uplink signal samples for transmission to a distributed unit, DU, via a fronthaul interface.

10. The radio unit node of embodiment 9, wherein the channel estimation is performed in the RU.

11. The radio unit node of embodiment 9, wherein dependency of an average magnitude and/or phase of the IQ uplink signal samples on the wireless channel is removed or reduced via the beamforming and/or equalization operation.

12. The radio unit node of embodiment 9, wherein performing the scaling operation includes determining if the uplink signal was originally modulated via cyclic prefix orthogonal frequency division multiplexing, CP-OFDM, or discrete Fourier transform, DFT, spread OFDM.

13. The radio unit node of embodiment 12, wherein if the uplink signal is determined to be originally modulated via CP-OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or a BFP data format is identical to or slightly larger than a magnitude of an outermost constellation point in a Quadrature Amplitude Modulation, QAM, constellation including the IQ uplink signal samples.

14. The radio unit node of embodiment 14, wherein a signal level of the uplink signal originally modulated via CP-OFDM is saturated prior to signal quantization.

15. The radio unit node of embodiment 12, wherein if the uplink signal is determined to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio.

16. The radio unit node of embodiment 9, wherein the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a signal to interference plus noise ratio, SINR, dependent scale factor such that the root mean square, RMS, value of each of the IQ uplink signal samples does not increase for a low SINR.

17. A computer program product comprising a non-transitory computer readable medium storing instructions executable by processing circuitry of a radio unit node, the instructions executed by the processing circuitry to perform operations comprising: performing (401) channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, UE; conducting (402) a beamforming and/or equalization operation on in-phase quadrature, IQ, uplink signal samples associated with the uplink signal; performing (403) a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated; and quantizing (404) the scaled IQ uplink signal samples for transmission to a distributed unit, DU, via a fronthaul interface.

18. The computer program product of embodiment 17, wherein the channel estimation is performed in the RU.

19. The computer program product of embodiment 17, wherein dependency of an average magnitude and/or phase of the IQ uplink signal samples on the wireless channel is removed or reduced via the beamforming and/or equalization operation.

20. The computer program product of embodiment 17, wherein performing the scaling operation includes determining if the uplink signal was originally modulated via cyclic prefix orthogonal frequency division multiplexing, CP-OFDM, or discrete Fourier transform, DFT, spread OFDM.

21. The computer program product of embodiment 20, wherein if the uplink signal is determined to be originally modulated via CP-OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or a BFP data format is identical to or slightly larger than a magnitude of an outermost constellation point in a Quadrature Amplitude Modulation, QAM, constellation including the IQ uplink signal samples.

22. The computer program product of embodiment 21, wherein a signal level of the uplink signal originally modulated via CP-OFDM is saturated prior to signal quantization.

23. The computer program product of embodiment 20, wherein if the uplink signal is determined to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio.

24. The method of embodiment 17, wherein the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a signal to interference plus noise ratio, SINR, dependent scale factor such that the root mean square, RMS, value of each of the IQ uplink signal samples does not increase for a low SINR.

REFERENCES

1. “O-RAN Control, User and Synchronization Plane Specification 13.0”, O- RAN.WG4.CUS.0-R003-vl3.00, O-RAN Working Group 4, October 2023

2. “5G NR Physical Channels and modulation”, 3GPP TS 38.211, any version, e.g., 16.9.0 published 2022-04.

Claims

1. A method performed by a radio unit, RU, for conducting an improved uplink signal quantization, the method comprising: performing (401) channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, UE; conducting (402) a beamforming and/or equalization operation on in-phase quadrature, IQ, uplink signal samples associated with the uplink signal; performing (403) a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated; and quantizing (404) the scaled IQ uplink signal samples for transmission to a distributed unit, DU, via a fronthaul interface.

2. The method of claim 1 , wherein the determination is performed in a distributed unit (DU) that is communicatively connected to the RU.

3. The method of claim 1, wherein dependency of an average magnitude and/or phase rotation of the IQ uplink signal samples on the wireless channel is removed or reduced at the RU via the beamforming and/or equalization operation.

4. The method of claim 1, wherein performing the scaling operation includes determining if the uplink signal was originally modulated via cyclic prefix orthogonal frequency division multiplexing, CP-OFDM, or discrete Fourier transform, DFT, spread OFDM.

5. The method of claim 4, wherein the RU is configured to select the scaling operation from among a plurality of scaling operations based on whether the uplink signal was modulated via CP-OFDM or DFT spread OFDM.

6. The method of claim 4, wherein if the uplink signal is determined to be originally modulated via CP-OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or the maximum magnitude of a BFP data format for a specific exponent value is identical to or slightly larger than a magnitude of an outermost constellation point in a Quadrature Amplitude Modulation, QAM, constellation including the IQ uplink signal samples.

7. The method of claim 6, wherein a signal level of the uplink signal originally modulated via CP-OFDM is saturated at a level below full scale of a fronthaul interface data format prior to signal quantization.

8. The method of claim 4, wherein if the uplink signal is determined to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio.

9. The method of claim 1, wherein the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a signal to interference plus noise ratio, SINR, dependent scale factor such that a variance of IQ samples does not increase for a low SINR.

10. A radio unit, RU, node for conducting an improved uplink signal quantization , the RU node comprising: processing circuitry; and at least one memory storing instructions executable by the processing circuitry to perform operations to: perform (401) channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, UE; conduct (402) a beamforming and/or equalization operation on in-phase quadrature, IQ, uplink signal samples associated with the uplink signal; perform (403) a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated; and quantize (404) the scaled IQ uplink signal samples for transmission to a distributed unit, DU, via a fronthaul interface.

11. The radio unit node of claim 10, wherein the determination is performed in a distributed unit (DU) that is communicatively connected to the RU.

12. The radio unit node of claim 10, wherein dependency of an average magnitude and/or phase rotation of the IQ uplink signal samples on the wireless channel is removed or reduced at the RU via the beamforming and/or equalization operation.

13. The radio unit node of claim 10, wherein performing the scaling operation includes determining if the uplink signal was originally modulated via cyclic prefix orthogonal frequency division multiplexing, CP-OFDM, or discrete Fourier transform, DFT, spread OFDM.

14. The radio unit node of claim 13, wherein the RU is configured to select the scaling operation from among a plurality of scaling operations based on whether the uplink signal was modulated via CP-OFDM or DFT spread OFDM.

15. The radio unit node of claim 13, wherein if the uplink signal is determined to be originally modulated via CP-OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or the maximum magnitude of a BFP data format for a specific exponent value is identical to or slightly larger than a magnitude of an outermost constellation point in a Quadrature Amplitude Modulation, QAM, constellation including the IQ uplink signal samples.

16. The radio unit node of claim 15, wherein a signal level of the uplink signal originally modulated via CP-OFDM is saturated at a level below full scale of a fronthaul interface data format prior to signal quantization.

17. The radio unit node of claim 13, wherein if the uplink signal is determined to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio.

18. The radio unit node of claim 10, wherein the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a signal to interference plus noise ratio, SINR, dependent scale factor such that a variance of IQ samples does not increase for a low SINR.

19. A computer program product comprising a non-transitory computer readable medium storing instructions executable by processing circuitry of a radio unit node, the instructions executed by the processing circuitry to perform operations comprising: performing (401) channel estimation corresponding to a wireless channel used to receive an uplink signal from a user equipment, UE; conducting (402) a beamforming and/or equalization operation on in-phase quadrature, IQ, uplink signal samples associated with the uplink signal; performing (403) a scaling operation on the IQ uplink signal samples based on a determination as to how the uplink signal was originally modulated; and quantizing (404) the scaled IQ uplink signal samples for transmission to a distributed unit, DU, via a fronthaul interface.

20. The computer program product of claim 19, wherein the determination is performed in a distributed unit (DU) that is communicatively connected to the RU.

21. The computer program product of claim 19, wherein dependency of an average magnitude and/or phase rotation of the IQ uplink signal samples on the wireless channel is removed or reduced at the RU via the beamforming and/or equalization operation.

22. The computer program product of claim 19, wherein performing the scaling operation includes determining if the uplink signal was originally modulated via cyclic prefix orthogonal frequency division multiplexing, CP-OFDM, or discrete Fourier transform, DFT, spread OFDM.

23. The computer program product of claim 22, wherein the RU is configured to select the scaling operation from among a plurality of scaling operations based on whether the uplink signal was modulated via CP-OFDM or DFT spread OFDM.

24. The computer program product of claim 22, wherein if the uplink signal is determined to be originally modulated via CP-OFDM, then the IQ uplink signal samples are scaled such that either a full scale of a fixed point data format or the maximum magnitude of a BFP data format for a specific exponent value is identical to or slightly larger than a magnitude of an outermost constellation point in a Quadrature Amplitude Modulation, QAM, constellation including the IQ uplink signal samples.

25. The computer program product of claim 24, wherein a signal level of the uplink signal originally modulated via CP-OFDM is saturated at a level below full scale of a fronthaul interface data format prior to signal quantization.

26. The computer program product of claim 22, wherein if the uplink signal is determined to be originally modulated via DFT-spread OFDM, then the IQ uplink signal samples are scaled to leave room to accommodate a Gaussian-like peak-to-average power ratio.

27. The computer program product of claim 19, wherein the IQ uplink signal samples are subjected to an additional scaling operation that utilizes a signal to interference plus noise ratio, SINR, dependent scale factor such that a variance of IQ samples does not increase for a low SINR.