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CN111147408A - Signal processing method and device for non-orthogonal multiple access - Google Patents

Signal processing method and device for non-orthogonal multiple access Download PDF

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CN111147408A
CN111147408A CN201811308471.3A CN201811308471A CN111147408A CN 111147408 A CN111147408 A CN 111147408A CN 201811308471 A CN201811308471 A CN 201811308471A CN 111147408 A CN111147408 A CN 111147408A
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candidate set
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CN111147408B (en
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项飞
白宁波
刘丽娇
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ZTE Corp
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Abstract

本发明实施例公开了一种非正交多址接入的信号处理方法及装置，所述方法包括：基站对具有多用户共享接入MUSA特性的接收信号进行初步盲均衡和盲检测处理，得到满足第一要求的接收特征序列，并形成初步备选集合；对所述初步备选集合进行粗频偏补偿和空间维度的合并处理，得到加权后数据，并从所述加权后数据中筛选出终极备选集合；对所述终极备选集合中的所述加权后数据进行解调译码处理，得到正确译码数据。

Figure 201811308471

The embodiment of the present invention discloses a signal processing method and device for non-orthogonal multiple access. The method includes: a base station performs preliminary blind equalization and blind detection processing on a received signal with multi-user shared access MUSA characteristics, and obtains Receive feature sequences that meet the first requirement, and form a preliminary candidate set; perform coarse frequency offset compensation and spatial dimension merging processing on the preliminary candidate set to obtain weighted data, and filter out the weighted data The final candidate set; perform demodulation and decoding processing on the weighted data in the final candidate set to obtain correctly decoded data.

Figure 201811308471

Description

Signal processing method and device for non-orthogonal multiple access
Technical Field
The embodiment of the invention relates to the technical field of mobile communication, in particular to a signal processing method and device for non-orthogonal multiple access.
Background
To cope with the explosive demand for traffic and the explosive growth of the number of user equipments in the fifth Generation (5th-Generation, 5G), various non-orthogonal access technologies are under active research. The basis of non-orthogonal access is to utilize near-far effect so that multiple users can use the same radio resource and complete orthogonality among users is not needed. Meanwhile, at a receiving end, Serial Interference Cancellation (SIC) is performed by using a certain power difference between users, so as to effectively separate the users.
A potential problem with existing non-orthogonal multiple access techniques, such as Low Density Signal Multiple Access (LDSMA) and Sparse Code Multiple Access (SCMA), is lack of stability. To overcome the above problems, another multiple Access technique, Multi-user Shared Access (MUSA), is proposed. One advantage of MUSA is non-orthogonality and freedom from authorization. Data is transmitted through a short spreading sequence, through complex field spreading. And at a receiving end, the SIC receiver is adopted to eliminate the interference of the user. Meanwhile, scheduling is avoided, so that scheduling overhead can be saved, and user capacity is greatly improved.
In a traditional data transmission mode based on scheduling, for Internet of things (IOT) application mainly based on uplink services, a narrowband Band-IOT protocol obtains a wide coverage effect by increasing the number of repetitions during transmission, but also reduces the use efficiency of a channel, and channel resources (such as control channel resources and broadcast channel resources) are seriously wasted, thereby becoming a bottleneck that restricts the number of effective connections.
Disclosure of Invention
The embodiment of the invention provides a signal processing method and device for non-orthogonal multiple access, which solve the problem of low channel use efficiency when the Internet of things realizes mass connection.
The embodiment of the invention provides a signal processing method for non-orthogonal multiple access, which comprises the following steps:
the base station carries out primary blind equalization and blind detection processing on a received signal with the characteristic of multi-user shared access MUSA to obtain a received characteristic sequence meeting a first requirement and form a primary alternative set;
the base station performs coarse frequency offset compensation and spatial dimension combination processing on the preliminary candidate set to obtain weighted data, and screens the weighted data meeting a second requirement from the weighted data to form a final candidate set;
and the base station demodulates and decodes the weighted data in the ultimate candidate set to obtain correct decoded data.
The embodiment of the invention provides a signal processing device for non-orthogonal multiple access, which comprises:
the primary screening module is used for carrying out primary blind equalization and blind detection processing on the received signals with the multi-user shared access MUSA characteristic to obtain a received characteristic sequence meeting a first requirement and form a primary alternative set;
the final screening module is used for performing coarse frequency offset compensation and spatial dimension combination processing on the preliminary candidate set to obtain weighted data, screening the weighted data meeting a second requirement from the weighted data, and forming a final candidate set;
and the decoding module is used for demodulating and decoding the weighted data in the ultimate candidate set to obtain correct decoded data.
The embodiment of the present invention provides a non-orthogonal multiple access signal processing apparatus, which includes a processor and a memory, and is characterized in that the memory stores a non-orthogonal multiple access signal processing program that is executable on the processor, and the non-orthogonal multiple access signal processing program implements the steps of the non-orthogonal multiple access signal processing method when executed by the processor.
An embodiment of the present invention provides a computer readable medium, on which a signal processing program for non-orthogonal multiple access is stored, and when the signal processing program for non-orthogonal multiple access is executed by a processor, the steps of the signal processing method for non-orthogonal multiple access are implemented.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
1. according to the embodiment of the invention, through a time domain signal (narrow-band transmission signal) which is designed by a transmitting end and combines the MUSA characteristics, simple repetition is converted into a frame structure design which can support high overload rate, so that the use efficiency of a channel and the overload rate of the whole system are improved;
2. the embodiment of the invention can realize the scheduling-free design under high overload rate through the blind equalization of the receiving end, the twice user identification and the iterative serial interference elimination module, thereby further improving the use efficiency of the channel;
3. the embodiment of the invention can support the scene of larger residual frequency offset through twice frequency offset estimation and compensation, is suitable for a low-cost terminal and realizes the low-power-consumption design of a system.
Drawings
Fig. 1 is a schematic flowchart of a signal processing method for non-orthogonal multiple access according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a signal processing method of a single transmission unit according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a frame format of a single transmission unit according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating a signal processing method of multiple transmission units according to an embodiment of the present invention;
fig. 5 is a diagram illustrating a frame format of a multi-transmission unit according to an embodiment of the present invention;
fig. 6 is a flowchart illustrating a signal processing method for multiple transmission units with a repeating format according to an embodiment of the present invention;
fig. 7 is a diagram illustrating a frame format of a multiple transmission unit with a repetition format according to an embodiment of the present invention;
fig. 8 is a schematic diagram of a signal processing apparatus for multiple transmission units with a repetitive format according to an embodiment of the present invention;
fig. 9 is a schematic structural block diagram of a non-orthogonal multiple access signal processing apparatus according to an embodiment of the present invention;
fig. 10 is a schematic structural block diagram of signal processing of non-orthogonal multiple access provided by an embodiment of the present invention;
fig. 11 is a diagram illustrating a system for processing signals of multiple transmission units with a repeating format according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, and it should be understood that the embodiments described below are only for illustrating and explaining the present invention and are not intended to limit the present invention.
Fig. 1 is a schematic flowchart of a signal processing method for non-orthogonal multiple access according to an embodiment of the present invention, and as shown in fig. 1, the method may include:
step S101: and the base station performs primary blind equalization and blind detection processing on the received signal with the MUSA characteristic to obtain a received characteristic sequence meeting the first requirement and form a primary alternative set.
In one embodiment, a base station performs blind equalization preprocessing on a received signal with an MUSA characteristic to obtain a received characteristic sequence, performs blind detection processing on the received characteristic sequence to obtain a received characteristic sequence meeting a first requirement, and forms a preliminary candidate set.
In this embodiment, the received signal includes a transmission unit having MUSA characteristics, and the transmission unit includes a data symbol, a pilot symbol, and a spreading sequence.
In this embodiment, the base station performs fast fourier transform processing on the received signal to obtain a frequency domain signal, and performs preliminary blind equalization processing according to a preset spatial relationship, a preset data spreading sequence candidate corpus, the frequency domain signal and a cross-correlation covariance matrix thereof to obtain a received signature sequence.
In this embodiment, the base station constructs a blind equalization factor according to a preset data spreading sequence candidate complete set and a cross-correlation covariance matrix of the frequency domain signals combined according to a preset spatial relationship, and obtains a receiving characteristic sequence corresponding to the preset spatial relationship according to the blind equalization factor and the frequency domain signals combined according to the preset spatial relationship.
In this embodiment, the number of the preset spatial relationships may be multiple, and the number is determined by the antenna dimension and the actual hardware processing capability, so that each preset spatial relationship can obtain a group of corresponding receiving feature sequences.
In this embodiment, the first requirement may be a power requirement. And the base station determines the power of the received characteristic sequences, and screens out a plurality of received characteristic sequences meeting the power requirement according to the power of the received characteristic sequences to form a preliminary alternative set.
Step S102: and the base station performs coarse frequency offset compensation and spatial dimension combination processing on the preliminary candidate set to obtain weighted data, screens the weighted data meeting a second requirement from the weighted data, and forms an ultimate candidate set.
In one embodiment, the received signal comprises a single transmission unit.
In this embodiment, the base station performs coarse frequency offset compensation on the received feature sequences in the preliminary candidate set to obtain a compensated preliminary candidate set, performs blind detection and equalization processing on the compensated preliminary candidate set to obtain equalized data, performs spatial dimension combination on the equalized data to obtain weighted data after spatial dimension combination, determines a signal to interference plus noise ratio of the weighted data, and screens out weighted data meeting the signal to interference plus noise ratio requirement according to the signal to interference plus noise ratio of the weighted data to form a final candidate set.
In another embodiment, the received signal comprises multiple transmission units.
In this embodiment, the base station performs multi-transmission unit joint coarse frequency offset compensation on the received feature sequences in the preliminary candidate set to obtain a compensated preliminary candidate set, then performs blind detection and equalization processing on the compensated preliminary candidate set to obtain equalized data, and performs spatial dimension combination on the equalized data to obtain weighted data after spatial dimension combination, and finally determines the signal-to-interference-and-noise ratio of the weighted data, and screens out weighted data meeting the signal-to-interference-and-noise ratio requirement according to the signal-to-interference-and-noise ratio of the weighted data to form a final candidate set.
In yet another embodiment, the received signal comprises a repeating multiple transmission unit.
In this embodiment, the base station performs multiple transmission unit joint coarse frequency offset compensation on the received feature sequences in the preliminary candidate set to obtain a compensated preliminary candidate set, performs blind detection and equalization processing on the compensated preliminary candidate set to obtain equalized data, performs spatial dimension combination on the equalized data to obtain weighted data after spatial dimension combination, and finally determines the signal-to-interference-and-noise ratio of the weighted data, and screens out the weighted data meeting the signal-to-interference-and-noise ratio requirement according to the signal-to-interference-and-noise ratio of the weighted data to form a final candidate set.
Step S103: and the base station demodulates and decodes the weighted data in the ultimate candidate set to obtain correct decoded data.
On the basis of the above embodiment, the method may further include: and reconstructing the correct decoding data and performing fine frequency offset recovery processing to obtain an accurate reconstruction signal.
In one embodiment, the received signal comprises a single transmission unit. In this embodiment, the base station performs fine frequency offset estimation and recovery processing on the reconstructed data by using a single transmission unit to obtain an accurate reconstructed signal.
In another embodiment, the received signal comprises multiple transmission units. In this embodiment, the base station performs multi-transmission-unit joint fine frequency offset estimation and recovery processing on the reconstructed data to obtain an accurate reconstructed signal.
In yet another embodiment, the received signal comprises a repeating multiple transmission unit. In this embodiment, the base station performs multi-transmission unit joint fine frequency offset estimation and repeated sample joint recovery processing on the reconstructed data to obtain an accurate reconstructed signal.
On the basis of the above embodiment, the method may further include:
the base station carries out joint fine channel estimation and serial interference elimination processing on the accurate reconstruction signal to obtain a new signal with the MUSA characteristic;
and sequentially carrying out blind equalization preprocessing, blind detection processing, coarse frequency offset compensation, spatial dimension combination processing and demodulation decoding processing on the new signal until correct decoding data cannot be obtained.
In one embodiment, the precise reconstruction signal is subjected to joint channel estimation to obtain a zero forcing result of the received signal, and serial interference cancellation processing is performed using the zero forcing result of the received signal to obtain the received signal from which the precise reconstruction signal is cancelled as the new signal.
The embodiment of the invention can improve the uplink connection number, reduce the use amount of the control channel, improve the transmission efficiency of the system and achieve the application purposes of mass connection and low power consumption.
Fig. 2 is a schematic flow chart of a signal processing method of a single transmission unit according to an embodiment of the present invention, and as shown in fig. 2, under the single transmission unit, a signal processing (or detecting) method based on non-orthogonal multiple access may include the following steps:
step S201: the base station receives a time domain signal (or a received signal or a non-orthogonal multiple access signal) with a specific frame format and performs blind equalization preprocessing.
The terminal transmits a signal without authorization according to the frame structure shown in fig. 3. Where Dx denotes a data symbol, Px denotes a pilot symbol, and Sx denotes a spreading sequence. For any terminal, the required data spreading sequence and pilot base sequence can be selected from the data spreading sequence candidate set and pilot base sequence candidate set according to some pseudo-random rule for transmission.
After receiving the time domain signal, the base station transforms the non-orthogonal multiple access signal from the time domain to the frequency domain through Fast Fourier Transform (FFT). And then, recombining the frequency domain data according to a preset spatial relationship, and constructing a blind equalization factor by using the cross-correlation covariance matrix of the combined frequency domain signals and a preset data expansion sequence alternative complete set.
Let Y be the frequency domain signal before blind equalization, S be the whole set of preset data spreading sequence alternatives, N represent the number of spreading sequences, N is the number of spreading sequenceseIndicates the spreading sequence length, NdIndicating the effective length of basic transmission unit data, NsAnd representing the number of the spatial relationship combinations, wherein the receiving characteristic sequence after blind equalization is as follows:
Figure BDA0001854337560000071
wherein R isYY＝E{YYHDenotes the cross-correlation covariance matrix of the frequency domain signals with dimension Ne×Ne；YGDimension of NxNdDimension S is NxNeY dimension is Ne×Nd。
Because each group of spatial relationship will obtain a group of corresponding receiving characteristic sequence YGSo that Y isGThe final dimension is NXNd×Ns。
The number N of spatial combination relations preset heresThe antenna dimension is related to the actual hardware processing capacity, and the value of the value can be determined according to the requirement in the actual engineering.
Step S202: and carrying out mathematical characteristic statistics on the received characteristic sequence, and screening out a preliminary alternative set according to a preset index requirement.
And calculating the power of the received characteristic sequence and then accumulating to obtain a decision vector Det:
Figure BDA0001854337560000081
Figure BDA0001854337560000082
wherein i belongs to (0, N-1), j belongs to (0, N)s-1)，k∈(0,Nd-1)。
Sorting the decision vectors Det to select the largest N0And taking the characteristic sequence corresponding to the value as a preliminary candidate set.
Step S203: and carrying out coarse frequency offset processing on the candidate sets, merging spatial dimensions, and screening out an ultimate candidate set to be detected (or an ultimate candidate set) according to a specific preset index requirement.
Coarse frequency deviation estimation is carried out by using pilot frequency corresponding to the preliminary alternative set and adopting a difference method, and then a characteristic sequence Y is subjected toGCompensating for the frequency offset to obtain YGfre。
And performing pilot frequency bit channel estimation blind detection, performing correlation operation on the receiving characteristic sequence of the current pilot frequency symbol and all available pilot frequency mother codes, and taking the channel estimation value of the sequence with the maximum correlation value as a pilot frequency bit channel estimation blind detection result. And performing blind detection of data bit channel estimation, comparing the receiving characteristic sequence of the current data symbol with a standard constellation diagram, counting the distribution characteristics of the data symbol, and taking the channel estimation value with the minimum absolute value of an error vector as a data bit channel estimation result. Weighting the pilot frequency bit channel estimation result and the data bit channel estimation result to obtain a comprehensive channel estimation result HcAt this time, the equalized data is:
DGfre(i,k,j)＝YGfre(i,k,j)×conj(HC(i,k,j))
wherein i ∈ (0, N)0-1)，j∈(0,Ns-1)，k∈(0,Nd-1)。
Calculating the SINR of the equalized data, and then merging the spatial dimensions to obtain weighted data, namely
Figure BDA0001854337560000091
Wherein i ∈ (0, N)0-1)，j∈(0,Ns-1)，k∈(0,Nd-1)。
Calculating the SINR of the weighted data, and selecting the maximum N1And taking the characteristic sequence corresponding to the value as an ultimate candidate set.
Step S204: and demodulating, decoding and reconstructing the final candidate set to be detected, and then performing fine frequency offset processing and recovery to obtain a more accurate reconstructed signal (or an accurate reconstructed signal).
Sequentially processing each group of data D in the ultimate candidate set to be detected (or ultimate candidate set)GfreAnd (i, k) demodulating and decoding, and reconstructing the correctly decoded user, namely recoding, modulating, spreading at a symbol level and mapping.
Using reconstruction data DnAnd a weighted data sequence DGfreCalculating a channel estimate Hc1Namely:
Hc1＝DGfre×conj(Dn)
wherein Hc1，DGfre，DnAll dimensions are Nd×1。
Then estimates the channel Hc1Estimating a fine frequency offset f by using a multi-interval difference mode according to the bandwidth rearrangement dimensionalitycAnd compensated to the reconstructed data DnTo obtain an accurate reconstructed signal DnfreNamely:
Figure BDA0001854337560000092
wherein D isnfreDimension Nsc×(Nsym×Ne) And has Nsc×Nsym＝Nd，NscRepresenting the number of subcarriers, N, in the frequency domain bandwidthsymRepresents the number of time domain significant symbols, and DnThe dimension of (c) requires re-ordering the dimension according to the bandwidth and according to the spreading sequence length NePerforming flat push expansion, i.e. with dimension Nsc×(Nsym×Ne)。
Assuming that the number of users who correctly decode and reject duplicates is N2Then N will be reconstructed2An accurately reconstructed signal DnfreCombining them into a set of reconstructed signals DAUe-nfreDimension Nsc×(Nsym×Ne)×N2。
Step S205: and performing joint channel estimation and serial interference elimination on the accurate reconstruction signal.
The specific process of this step can be broken down into:
(1) joint channel estimation, i.e. performing zero forcing operation on the original received data, the expression is as follows:
Figure BDA0001854337560000101
wherein Hc2-reFor multi-user zero-forcing per subcarrier results, the dimension is 1 XN2×NrxIt is Hc2A subset of (1), and Hc2Dimension Nsc×N2×Nrx；DAue-nfre-reDimension of (N)sym×Ne)×N2Is D ofAUe-nfreA subset of subcarrier dimensions; y isreDimension of (N)sym×Ne)×NrxIs a subset of the dimension of the sub-carriers of the received data Y, and the dimension of Y is Nsc×(Nsym×Ne)×Nrx；NrxIndicating the number of receive antennas at the base station side.
(2) And a serial interference elimination part, namely, eliminating the demodulated signal from the original received data. The expression is as follows:
Figure BDA0001854337560000102
wherein p ∈ (0, N)2-1); dimension of Y is Nsc×(Nsym×Ne)×Nrx。
And repeating the steps S201 to S205 until the maximum iteration number limit is reached or the decoding is not correct in the step S204.
Fig. 4 is a flowchart illustrating a signal processing method for multiple transmission units according to an embodiment of the present invention, and as shown in fig. 4, the signal processing (or detecting) method based on non-orthogonal multiple access may include the following steps:
step S401: and the base station receives the time domain signal with the specific frame format and performs blind equalization preprocessing.
The terminal transmits a signal without authorization according to the frame structure shown in fig. 5, and processes the mode synchronization per transmission unit (or basic unit) S201.
Step S402: the synchronization step S202.
Step S403: and carrying out multi-transmission unit joint coarse frequency offset processing on the candidate set (or the preliminary candidate set), merging the spatial dimensions, and screening out an ultimate candidate set to be detected (or an ultimate candidate set) according to a specific preset index requirement.
And for each transmission unit, utilizing the pilot frequency corresponding to the preliminary alternative set, obtaining a relative phase difference by adopting a difference method, then carrying out complex accumulation among a plurality of transmission units, further estimating a coarse frequency offset, and compensating the frequency offset for the characteristic sequence.
And then, carrying out pilot frequency bit channel estimation blind detection, carrying out correlation operation on the receiving characteristic sequence of the current pilot frequency symbol and all available pilot frequency mother codes, and taking the channel estimation value of the sequence with the maximum correlation value as a pilot frequency bit channel estimation blind detection result.
And performing blind detection of data bit channel estimation, comparing the receiving characteristic sequence of the current data symbol with a standard constellation diagram, counting the distribution characteristics of the data symbol, and taking the channel estimation value with the minimum absolute value of an error vector as a data bit channel estimation result.
Weighting the pilot frequency bit channel estimation result and the data bit channel estimation result to obtain a comprehensive channel estimation result HcThen the equalized data is:
DGfre(i,k,j)＝YGfre(i,k,j)×conj(HC(i,k,j))
wherein i ∈ (0, N)0-1)，j∈(0,Ns-1)，k∈(0,Nu×Nd-1)，NuIndicating the number of transmission units.
Calculating the SINR of the equalized data, and then combining the space dimensions to obtain weighted data, namely
Figure BDA0001854337560000111
Wherein i ∈ (0, N)0-1)，j∈(0,Ns-1)，k∈(0,Nu×Nd-1)。
Calculating the SINR of the weighted data, and selecting the maximum N1And taking the characteristic sequence corresponding to the value as an ultimate candidate set to be detected (or ultimate candidate set).
Step S404: and demodulating, decoding and reconstructing the ultimate candidate set to be detected (or ultimate candidate set), and then performing multi-transmission unit joint fine frequency offset processing and recovery to obtain a more accurate reconstructed signal.
The demodulation decoding reconstructs part of the synchronization step S204.
The fine frequency offset estimation part acquires a relative phase difference for each transmission unit by adopting a difference method, then performs complex accumulation among a plurality of transmission units, further estimates fine frequency offset, and compensates the frequency offset for the reconstructed signal.
Step S405: the synchronization step S205.
And repeating the steps S401 to S405 until the maximum iteration number limit is reached or the decoding is not correct in the step S404.
Fig. 6 is a flowchart illustrating a method for processing a signal of a multiple transmission unit with a repetition format according to an embodiment of the present invention, and as shown in fig. 6, in the multiple transmission unit with a repetition format, the method for processing (detecting) a signal based on non-orthogonal multiple access may include the following steps:
step S601: and the base station receives the time domain signal with the specific frame format and performs blind equalization preprocessing.
The terminal transmits a signal without authorization according to the frame structure shown in fig. 7, and processes the mode synchronization per transmission unit (or basic unit) S401.
Step S602: the synchronization step S402.
Step S603: and performing repeated inter-sample multi-transmission-unit joint coarse frequency offset processing on the candidate set (or the primary candidate set), merging the spatial dimensions, and screening out an ultimate candidate set to be detected (or an ultimate candidate set) according to a specific preset index requirement.
Assume that the number of repetitions is NrepnThen each transmission unit within each repeated sample utilizes the preliminary candidateAnd collecting corresponding pilot frequencies, acquiring a relative phase difference by adopting a difference method, then repeating a plurality of transmission units in the sample for a plurality of times, and adopting complex accumulation to estimate coarse frequency offset and compensate the frequency offset for the characteristic sequence. And then directly combining the frequency domain data among the repeated samples to equivalently obtain the frequency domain data of the single multi-transmission unit. The remaining operation is the same as step S403.
Step S604: and demodulating, decoding and reconstructing the ultimate candidate set to be detected (or the ultimate candidate set), and performing multi-transmission unit joint fine frequency offset processing and repeated sample joint recovery to obtain a more accurate reconstructed signal.
The demodulation decoding reconstruction part and the fine frequency offset estimation part are synchronized S404;
when compensating the frequency offset of the reconstructed signal, the repetition number N needs to be consideredrepnAnd compensating the frequency offset according to the maximum repetition time dimension of the sample so as to obtain a reconstructed signal (or an accurate reconstructed signal).
Step S605: synchronization step S405.
And repeating the steps S601 to S605 until the maximum iteration number limit is reached or the decoding is not correct in the step S604.
Fig. 8 is a schematic diagram of a signal processing apparatus for multiple transmission units in a repeating format according to an embodiment of the present invention, and as shown in fig. 8, the apparatus may include:
a blind equalization preprocessing module 81, configured to separate code sub to obtain a receiving characteristic sequence corresponding to each code sub;
mathematical characteristic statistical processing modules 82 and 84, configured to perform mathematical characteristic statistics on the received characteristic sequence, such as constellation error vector statistical characteristics or amplitude statistical characteristics, sort the received characteristic sequence according to a preset index based on the statistical characteristics, and then screen out an alternative set;
a coarse frequency offset processing module 83, configured to perform frequency offset estimation (or coarse frequency offset estimation) based on the original design pilot frequency and frequency offset compensation (or coarse frequency offset compensation) of preset target data;
a demodulation decoding reconstruction module 85 for reconstructing the original sequence;
a fine frequency offset processing module 86, configured to perform frequency offset estimation (fine frequency offset estimation) using the reconstructed data as a pilot frequency and perform frequency offset compensation (or fine frequency offset recovery) on preset target data;
the iterative successive interference cancellation module 87 performs joint channel estimation using the data passed through the fine frequency offset processing module 86, then cancels the correctly decoded data from the original received data, and considers the residual data as input data for a new iterative operation.
The embodiment of the invention can improve the uplink connection number of the 5G Internet of things application, reduce the use amount of the control channel, further improve the transmission efficiency of the system and achieve the application purposes of massive connection and low power consumption.
According to the requirement of the internet of things on low power consumption, a multiple access technology is required to be relatively simple on a terminal side, and a receiving end demodulation function on a base station side needs to be capable of dealing with the reality of poor indexes of a low-cost terminal, such as poor fixed frequency offset indexes and the like. The existing non-orthogonal multiple access technology is difficult to simultaneously consider, or has overhigh complexity, difficult realization of engineering or insufficient robustness, and can not meet various severe indexes under low-cost devices. The embodiment of the invention combines the modules in order, can achieve the aim of high overload rate access with lower implementation complexity and less control resource consumption, and can tolerate the existence of a low-cost terminal with poor crystal oscillator index. Assuming that the length of the spreading sequence is 4, when the residual frequency offset of the terminal is [ -50hz, 50hz ], the supported overload rate is 600%, that is, 24 users share the same time-frequency resource; when the residual frequency offset of the terminal is [ -200hz, 200hz ], the supported overload rate is 500%, that is, 20 users share the same time-frequency resource. In the practical test of the external field under the 5G large connection scene organized by the China department of Industrial information industry, by adopting the technology, the practical measured equivalent connection density of the external field reaches 5300 ten thousand connections/Mhz/hour/cell.
Fig. 9 is a schematic structural block diagram of a non-orthogonal multiple access detection apparatus according to an embodiment of the present invention, and as shown in fig. 9, the apparatus includes: a preliminary screening module 91 (implementing the functions of the blind equalization preprocessing module 81 and the mathematical characteristics statistics processing module 82 of fig. 8), a final screening module 92 (implementing the functions of the coarse frequency offset processing module 83 and the mathematical characteristics statistics processing module 84 of fig. 8), and a decoding module 93 (implementing the demodulation and decoding functions of the demodulation and decoding reconstruction module 85 of fig. 8).
The preliminary screening module 91 is configured to perform preliminary blind equalization and blind detection processing on the received signal with the MUSA characteristic to obtain a received feature sequence meeting the first requirement, and form a preliminary candidate set.
In one embodiment, the preliminary screening module 91 performs blind equalization preprocessing on a received signal with the MUSA characteristic to obtain a received feature sequence, performs blind detection processing on the received feature sequence to obtain a received feature sequence meeting a first requirement, and forms a preliminary candidate set.
In this embodiment, the received signal includes a transmission unit having MUSA characteristics, and the transmission unit includes a data symbol, a pilot symbol, and a spreading sequence.
In this embodiment, the preliminary screening module 91 performs fast fourier transform processing on the received signal to obtain a frequency domain signal, and performs preliminary blind equalization processing according to a preset spatial relationship, a preset data spreading sequence candidate corpus, the frequency domain signal and a cross-correlation covariance matrix thereof to obtain a received signature sequence.
In this embodiment, the first requirement may be a power requirement.
The preliminary screening module 91 determines the power of the received feature sequences, and screens out a plurality of received feature sequences meeting the power requirement according to the power of the received feature sequences to form a preliminary candidate set.
And the final screening module 92 is configured to perform coarse frequency offset compensation and spatial dimension combination processing on the preliminary candidate set to obtain weighted data, screen out weighted data meeting a second requirement from the weighted data, and form a final candidate set.
In one embodiment, the received signal comprises a single transmission unit.
In this embodiment, the final screening module 92 performs coarse frequency offset compensation on the received feature sequences in the preliminary candidate set to obtain a compensated preliminary candidate set, performs blind detection and equalization processing on the compensated preliminary candidate set to obtain equalized data, performs spatial dimension combination on the equalized data to obtain weighted data after spatial dimension combination, determines a signal-to-interference-and-noise ratio of the weighted data, and screens out the weighted data meeting the signal-to-interference-and-noise ratio requirement according to the signal-to-interference-and-noise ratio of the weighted data to form a final candidate set.
In another embodiment, the received signal comprises multiple transmission units.
In this embodiment, the final screening module 93 performs multi-transmission-unit joint coarse frequency offset compensation on the received feature sequences in the preliminary candidate set to obtain a compensated preliminary candidate set, performs blind detection and equalization processing on the compensated preliminary candidate set to obtain equalized data, performs spatial dimension combination on the equalized data to obtain weighted data after spatial dimension combination, determines a signal-to-interference-and-noise ratio of the weighted data, and screens out weighted data meeting the signal-to-interference-and-noise ratio requirement according to the signal-to-interference-and-noise ratio of the weighted data to form a final candidate set.
In yet another embodiment, the received signal comprises a repeating multiple transmission unit.
In this embodiment, the final screening module 93 performs multiple transmission unit joint coarse frequency offset compensation between repeated samples on the received feature sequences in the preliminary candidate set to obtain a compensated preliminary candidate set, performs blind detection and equalization processing on the compensated preliminary candidate set to obtain equalized data, performs spatial dimension combination on the equalized data to obtain weighted data after spatial dimension combination, determines a signal to interference plus noise ratio of the weighted data, and screens out the weighted data meeting the signal to interference plus noise ratio requirement according to the signal to interference plus noise ratio of the weighted data to form a final candidate set.
The decoding module 93 is configured to perform demodulation and decoding processing on the weighted data in the final candidate set to obtain correctly decoded data.
On the basis of the above embodiment, the apparatus may further include:
a reconstruction module 94 (implementing the reconstruction function of the demodulation decoding reconstruction module 85 and the function of the fine frequency offset processing module 86 in fig. 8) is configured to perform reconstruction and fine frequency offset compensation processing on the correctly decoded data to obtain an accurate reconstruction signal.
In one embodiment, the received signal comprises a single transmission unit.
In this embodiment, the reconstruction module 94 performs fine frequency offset estimation and recovery processing on the reconstruction data by using a single transmission unit to obtain an accurate reconstruction signal.
In another embodiment, the received signal comprises multiple transmission units.
In this embodiment, the reconstruction module 94 performs multi-transmission-unit joint fine frequency offset estimation and recovery processing on the reconstruction data to obtain an accurate reconstruction signal.
In yet another embodiment, the received signal comprises a repeating multiple transmission unit.
In this embodiment, the reconstruction module 94 performs multiple transmission unit joint fine frequency offset estimation and repeated sample joint recovery processing on the reconstruction data to obtain an accurate reconstruction signal.
On the basis of the above embodiment, the apparatus may further include:
an interference cancellation module 95 (implementing the function of the iterative serial interference cancellation module 87 in fig. 8) is configured to perform joint fine channel estimation and serial interference cancellation processing on the accurately reconstructed signal to obtain a new time domain signal with the MUSA characteristic, so as to perform blind equalization processing, blind detection processing, coarse frequency offset compensation, spatial dimension combination processing, and demodulation and decoding processing on the new time domain signal in sequence until correct decoding data cannot be obtained.
In one embodiment, the precise reconstruction signal is subjected to joint channel estimation to obtain a zero forcing result of the received signal, and serial interference cancellation processing is performed using the zero forcing result of the received signal to obtain the received signal from which the precise reconstruction signal is cancelled as the new signal.
Fig. 10 is a schematic structural block diagram of a detection apparatus for non-orthogonal multiple access according to an embodiment of the present invention, and as shown in fig. 10, the apparatus includes: a processor 10 and a memory 20; the memory 20 stores a non-orthogonal multiple access signal processing program operable on the processor 10, and the non-orthogonal multiple access signal processing program, when executed by the processor 10, implements the steps of the non-orthogonal multiple access signal processing method.
Fig. 11 is a schematic diagram of a system for detecting multiple transmission units with a repetition format according to an embodiment of the present invention, as shown in fig. 11, the system includes: the terminal 110 and the base station 120, the base station 120 is provided with a signal processing device 1201 of non-orthogonal multiple access.
The terminal 110 (or terminal side) uses a narrowband service transmission frame structure combined with the MUSA characteristics to perform signal transmission;
the base station 120 (or the base station test) receives the signal, performs blind equalization (or blind equalization preprocessing), then performs preliminary blind detection (or blind detection processing) on the user by using mathematical statistics characteristics, and screens out a preliminary alternative set (or preliminary alternative set);
for the alternative set sequence (the receiving characteristic sequence in the preliminary alternative set), performing frequency offset pre-estimation (or coarse frequency offset estimation) by using the pilot frequency, and performing frequency offset pre-compensation (or coarse frequency offset compensation) on blind equalization data corresponding to the possible sequence;
merging the spatial dimensions of the data after the frequency offset compensation by using the mathematical statistical characteristics again, and screening out an alternative set (or an ultimate alternative set) again;
demodulating, decoding and reconstructing users of the candidate set (or the ultimate candidate set);
performing fine frequency offset estimation and frequency offset recovery of reconstructed data by using the reconstructed data as a pilot frequency;
and finally, performing combined fine channel estimation and serial interference elimination, and performing iterative operation on the process.
The embodiment of the invention carries out the detection of the non-orthogonal multiple access based on the pilot frequency, and meets the application requirements of mass connection and low power consumption of the 5G Internet of things by defining a specific frame structure format and in a mode of supporting high overload rate, lower realization complexity and being beneficial to engineering realization.
The embodiment of the present invention further provides a computer readable medium, in which a signal processing program for non-orthogonal multiple access is stored, and when the signal processing program for non-orthogonal multiple access is executed by a processor, the steps of the signal processing method for non-orthogonal multiple access are implemented.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
The embodiment of the invention is used for receiving the sequence (or time domain signal) with a specific frame format and acquiring the sequence to be detected; carrying out blind equalization pretreatment on the sequence to be detected to obtain a receiving characteristic sequence; carrying out mathematical characteristic statistics on the received characteristic sequence, and screening out a preliminary alternative set according to a preset index requirement; performing coarse frequency offset processing on the candidate set (or the preliminary candidate set), merging spatial dimensions, and screening out an ultimate candidate set to be detected (or an ultimate candidate set) according to a specific preset index requirement; demodulating, decoding and reconstructing the final candidate set to be detected; performing fine frequency offset processing and recovery on the reconstructed signal to obtain a more accurate reconstructed signal; performing joint channel estimation and serial interference elimination on the accurate reconstruction signal to obtain input data of the next iteration; and finally, carrying out iteration processing on the process until iteration termination criteria are reached, stopping iteration operation, facilitating engineering realization, obtaining multiplied increase of the number of uplink connections, introducing a scheduling-free strategy, reducing the use amount of a control channel in a scheduling-free mode, further improving the transmission efficiency of the system, and achieving the application purposes of massive connection and low power consumption.
Although the present invention has been described in detail hereinabove, the present invention is not limited thereto, and various modifications can be made by those skilled in the art in light of the principle of the present invention. Thus, modifications made in accordance with the principles of the present invention should be understood to fall within the scope of the present invention.

Claims (13)

1.一种非正交多址接入的信号处理方法，其特征在于，所述方法包括：1. A signal processing method for non-orthogonal multiple access, wherein the method comprises: 基站对具有多用户共享接入MUSA特性的接收信号进行初步盲均衡和盲检测处理，得到满足第一要求的接收特征序列，并形成初步备选集合；The base station performs preliminary blind equalization and blind detection processing on the received signal with the characteristics of multi-user shared access MUSA, obtains a received characteristic sequence that meets the first requirement, and forms a preliminary candidate set; 所述基站对所述初步备选集合进行粗频偏补偿和空间维度的合并处理，得到加权后数据，并从所述加权后数据中筛选出满足第二要求的加权后数据，并形成终极备选集合；The base station performs coarse frequency offset compensation and spatial dimension merging processing on the preliminary candidate set to obtain weighted data, and selects weighted data that meets the second requirement from the weighted data, and forms a final backup. selection set; 所述基站对所述终极备选集合中的所述加权后数据进行解调译码处理，得到正确译码数据。The base station performs demodulation and decoding processing on the weighted data in the final candidate set to obtain correctly decoded data. 2.根据权利要求1所述的方法，所述基站对具有MUSA特性的接收信号进行初步盲均衡和盲检测处理，得到满足第一要求的接收特征序列，并形成初步备选集合包括：2. The method according to claim 1, wherein the base station performs preliminary blind equalization and blind detection processing on the received signal with MUSA characteristics, obtains a received characteristic sequence that meets the first requirement, and forms a preliminary candidate set comprising: 所述基站对具有MUSA特性的接收信号进行初步盲均衡处理，得到接收特征序列；The base station performs preliminary blind equalization processing on the received signal with the MUSA characteristic to obtain a received characteristic sequence; 所述基站对所述接收特征序列进行初步盲检测处理，得到满足第一要求的接收特征序列，并形成初步备选集合。The base station performs preliminary blind detection processing on the reception feature sequence, obtains a reception feature sequence that meets the first requirement, and forms a preliminary candidate set. 3.根据权利要求2所述的方法，其特征在于，所述基站对具有MUSA特性的接收信号进行初步盲均衡处理，得到接收特征序列包括：3. The method according to claim 2, wherein the base station performs preliminary blind equalization processing on the received signal with MUSA characteristics, and obtaining the received characteristic sequence comprises: 所述基站对所述接收信号进行快速傅立叶变换处理，得到频域信号；The base station performs fast Fourier transform processing on the received signal to obtain a frequency domain signal; 所述基站根据预设空间关系、预设数据扩展序列备选全集、所述频域信号及其互相关协方差矩阵，进行初步盲均衡处理，得到接收特征序列。The base station performs preliminary blind equalization processing according to the preset spatial relationship, the preset data expansion sequence candidate complete set, the frequency domain signal and its cross-correlation covariance matrix, and obtains the received characteristic sequence. 4.根据权利要求2所述的方法，其特征在于，所述第一要求是功率要求，所述基站对所述接收特征序列进行初步盲检测处理，得到满足第一要求的接收特征序列，并形成初步备选集合包括：4. The method according to claim 2, wherein the first requirement is a power requirement, and the base station performs preliminary blind detection processing on the receiving characteristic sequence to obtain a receiving characteristic sequence that meets the first requirement, and Forming a preliminary candidate set includes: 所述基站确定所述接收特征序列的功率；the base station determines the power of the received signature sequence; 所述基站根据所述接收特征序列的功率，筛选出满足功率要求的多个接收特征序列，形成初步备选集合。According to the power of the received feature sequence, the base station selects a plurality of receive feature sequences that meet the power requirement to form a preliminary candidate set. 5.根据权利要求1所述的方法，其特征在于，所述第二要求是信干噪比要求，所述基站对所述初步备选集合进行粗频偏补偿和空间维度的合并处理，得到加权后数据，并从所述加权后数据中筛选出满足第二要求的加权后数据，并形成终极备选集合包括：5 . The method according to claim 1 , wherein the second requirement is a signal-to-interference-noise ratio requirement, and the base station performs coarse frequency offset compensation and spatial dimension combination processing on the preliminary candidate set to obtain 5 . weighted data, and filter out the weighted data that meets the second requirement from the weighted data, and form the final candidate set including: 所述基站对所述初步备选集合进行粗频偏补偿，得到补偿后的初步备选集合；The base station performs coarse frequency offset compensation on the preliminary candidate set to obtain a compensated preliminary candidate set; 所述基站对所述补偿后的初步备选集合进行盲检测和均衡处理，得到均衡后数据，并对所述均衡后数据进行空间维度的合并，得到空间维度合并后的加权后数据；The base station performs blind detection and equalization processing on the compensated preliminary candidate set to obtain equalized data, and combines spatial dimensions on the equalized data to obtain weighted data after spatial dimensions are combined; 所述基站确定所述加权后数据的信干噪比，并根据所述加权后数据的信干噪比，筛选出满足信干噪比要求的加权后数据，形成最终备选集合。The base station determines the signal-to-interference-noise ratio of the weighted data, and according to the signal-to-interference-noise ratio of the weighted data, filters out the weighted data that meets the signal-to-interference-noise ratio requirement to form a final candidate set. 6.根据权利要求5所述的方法，其特征在于，所述基站对所述初步备选集合进行粗频偏补偿，得到补偿后的初步备选集合包括：6. The method according to claim 5, wherein the base station performs coarse frequency offset compensation on the preliminary candidate set, and the compensated preliminary candidate set comprises: 若所述接收信号包含具有MUSA特性的单传输单元，则所述基站对所述初步备选集合中的接收特征序列进行粗频偏补偿，得到补偿后的初步备选集合；If the received signal includes a single transmission unit with the MUSA characteristic, the base station performs coarse frequency offset compensation on the received characteristic sequence in the preliminary candidate set to obtain a compensated preliminary candidate set; 若所述接收信号包含具有MUSA特性的多传输单元，则所述基站对所述初步备选集合中的接收特征序列进行多传输单元联合粗频偏补偿，得到补偿后的初步备选集合；If the received signal includes multiple transmission units with MUSA characteristics, the base station performs multi-transmission unit joint coarse frequency offset compensation on the received characteristic sequences in the preliminary candidate set to obtain a compensated preliminary candidate set; 若所述接收信号包含具有MUSA特性的重复多传输单元，则所述基站对所述初步备选集合中的接收特征序列进行重复样本间多传输单元联合粗频偏补偿，得到补偿后的初步备选集合。If the received signal includes a repetitive multi-transmission unit with MUSA characteristics, the base station performs joint coarse frequency offset compensation between repetitive samples and multi-transmission units on the received characteristic sequence in the preliminary candidate set, and obtains a compensated preliminary equipment selection set. 7.根据权利要求1-6任意一项所述的方法，其特征在于，在所述得到正确译码数据后，还包括：7. The method according to any one of claims 1-6, characterized in that, after said obtaining the correctly decoded data, further comprising: 对所述正确译码数据进行重构和精频偏恢复处理，得到精确重构信号；Performing reconstruction and fine frequency offset recovery processing on the correctly decoded data to obtain an accurate reconstructed signal; 所述基站对所述精确重构信号进行联合信道估计和串行干扰消除处理，得到具有MUSA特性的新信号；The base station performs joint channel estimation and serial interference cancellation processing on the accurately reconstructed signal to obtain a new signal with MUSA characteristics; 对所述新信号依次进行初步盲均衡和盲检测处理、粗频偏补偿和空间维度的合并处理、解调译码处理，直至无法得到正确译码数据。Preliminary blind equalization and blind detection processing, coarse frequency offset compensation and spatial dimension merging processing, demodulation and decoding processing are sequentially performed on the new signal until correct decoding data cannot be obtained. 8.根据权利要求7所述的方法，其特征在于，所述对所述正确译码数据进行重构和精频偏恢复处理，得到精确重构信号包括：8. The method according to claim 7, characterized in that, performing reconstruction and fine frequency offset recovery processing on the correctly decoded data to obtain an accurate reconstructed signal comprises: 所述基站对正确译码数据进行重构，得到重构数据；The base station reconstructs the correctly decoded data to obtain reconstructed data; 若所述接收信号包含具有MUSA特性的单传输单元，则所述基站对所述重构数据进行单传输单元精频偏估计和恢复处理，得到精确重构信号；If the received signal includes a single transmission unit with MUSA characteristics, the base station performs single transmission unit precise frequency offset estimation and recovery processing on the reconstructed data to obtain an accurate reconstructed signal; 若所述接收信号包含具有MUSA特性的多传输单元，则所述基站对所述重构数据进行多传输单元联合精频偏估计和恢复处理，得到精确重构信号；If the received signal includes multiple transmission units with MUSA characteristics, the base station performs joint precise frequency offset estimation and recovery processing on the reconstructed data by multiple transmission units to obtain an accurate reconstructed signal; 若所述接收信号包含具有MUSA特性的重复多传输单元，则所述基站对所述重构数据进行多传输单元联合精频偏估计和重复样本联合恢复处理，得到精确重构信号。If the received signal includes repeated multiple transmission units with MUSA characteristics, the base station performs multiple transmission unit joint precise frequency offset estimation and repeated sample joint restoration processing on the reconstructed data to obtain an accurate reconstructed signal. 9.根据权利要求7所述的方法，其特征在于，所述基站对所述精确重构信号进行联合信道估计和串行干扰消除处理，得到具有MUSA特性的新信号包括：9. The method according to claim 7, wherein the base station performs joint channel estimation and serial interference cancellation processing on the accurately reconstructed signal, and obtaining a new signal with MUSA characteristics comprises: 对所述精确重构信号进行联合信道估计，得到所述接收信号的迫零结果；performing joint channel estimation on the accurately reconstructed signal to obtain a zero-forcing result of the received signal; 利用所述接收信号的迫零结果，进行串行干扰消除处理，得到已消除所述精确重构信号的接收信号作为所述新信号。Using the zero-forcing result of the received signal, serial interference cancellation processing is performed to obtain the received signal from which the accurately reconstructed signal has been eliminated as the new signal. 10.一种非正交多址接入的信号处理装置，其特征在于，所述装置包括：10. A signal processing apparatus for non-orthogonal multiple access, wherein the apparatus comprises: 初步筛选模块，用于对具有多用户共享接入MUSA特性的接收信号进行初步盲均衡和盲检测处理，得到满足第一要求的接收特征序列，并形成初步备选集合；The preliminary screening module is used to perform preliminary blind equalization and blind detection processing on the received signal with the characteristics of multi-user shared access MUSA, obtain the received characteristic sequence that meets the first requirement, and form a preliminary candidate set; 终极筛选模块，用于对所述初步备选集合进行粗频偏补偿和空间维度的合并处理，得到加权后数据，并从所述加权后数据中筛选出满足第二要求的加权后数据，并形成终极备选集合；The final screening module is used to perform a combination of coarse frequency offset compensation and spatial dimension on the preliminary candidate set, to obtain weighted data, and to screen out the weighted data that meets the second requirement from the weighted data, and form the final set of alternatives; 译码模块，用于对所述终极备选集合中的所述加权后数据进行解调译码处理，得到正确译码数据。A decoding module, configured to perform demodulation and decoding processing on the weighted data in the final candidate set to obtain correctly decoded data. 11.根据权利要求10所述的装置，其特征在于，所述装置还包括:11. device according to claim 10, is characterized in that, described device also comprises: 重构模块，用于对所述正确译码数据进行重构和精频偏补偿处理，得到精确重构信号；a reconstruction module, configured to perform reconstruction and fine frequency offset compensation processing on the correctly decoded data to obtain an accurate reconstructed signal; 干扰消除模块，用于对所述精确重构信号进行联合信道估计和串行干扰消除处理，得到具有MUSA特性的新信号，以便对所述新信号依次进行盲均衡处理、盲检测处理、粗频偏补偿和空间维度的合并处理、解调译码处理，直至无法得到正确译码数据。The interference cancellation module is used to perform joint channel estimation and serial interference cancellation processing on the accurately reconstructed signal to obtain a new signal with MUSA characteristics, so as to sequentially perform blind equalization processing, blind detection processing, coarse frequency processing on the new signal Offset compensation and spatial dimension merging processing, demodulation and decoding processing, until the correct decoding data cannot be obtained. 12.一种非正交多址接入的信号处理设备，所述设备包括处理器和存储器，其特征在于，所述存储器上存储有可在所述处理器上运行的非正交多址接入的信号处理程序，所述非正交多址接入的信号处理程序被所述处理器执行时实现如权利要求1至9中任一项所述的非正交多址接入的信号处理方法的步骤。12. A signal processing device for non-orthogonal multiple access, the device comprising a processor and a memory, wherein the memory stores a non-orthogonal multiple access that can run on the processor. The input signal processing program, when the non-orthogonal multiple access signal processing program is executed by the processor, realizes the non-orthogonal multiple access signal processing according to any one of claims 1 to 9. steps of the method. 13.一种计算机可读介质，其特征在于，其上存储有非正交多址接入的信号处理程序，所述非正交多址接入的信号处理程序被处理器执行时实现如权利要求1至9中任一项所述的非正交多址接入的信号处理方法的步骤。13. A computer-readable medium, characterized in that a signal processing program for non-orthogonal multiple access is stored thereon, and the signal processing program for non-orthogonal multiple access is executed by a processor to realize the method as claimed in the claim. The steps of the signal processing method for non-orthogonal multiple access according to any one of claims 1 to 9.
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