WO2026005667A1 - Method and network entity for estimating network capacity for serving wireless devices in a communication network - Google Patents

Abstract

Disclosed is a method for estimating network capacity for serving wireless devices in a service area (150) of a communication network (100) having a total amount of communication resources for providing wireless communication in the service area (150) via network nodes (130, 135). The method comprises obtaining, for a set of wireless devices (140, 145), requested values of service- related measures according to a Service Level Agreement, SLA and delivered values of the service-related measures. Then an SLA distance is determined for the set of wireless devices (140, 145) based on the requested and delivered values for the service-related measures. Thereafter, a communication resource margin is determined based on the SLA distance and amount of communication resources used for providing the delivered value for the service-related measurements, and eventually it is determined an SLA assurance state for the set of wireless devices (140, 145) based on the communication resource margin and on the total amount of communication resources, the SLA assurance state defining whether or to what extent the determined communication resource margin can be fulfilled.

Description

_{METHOD AND NETWORK ENTITY FOR ESTIMATING NETWORK CAPACITY} FOR SERVING WIRELESS DEVICES IN A COMMUNICATION NETWORK TECHNICAL FIELD _{[0001] The present disclosure relates generally to methods and network entities for estimating network capacity for serving wireless devices in a service area of a communication network, wherein the communication network comprises a at least one network node for providing wireless communication in the service area. The present disclosure further relates to computer programs and carriers} corresponding to the above methods and network entities. BACKGROUND _{[0002] To meet the huge demand for higher bandwidth, higher data rates and higher network capacity, due to e.g., data centric applications, existing 4th} Generation (4G) wireless communication network technology, aka Long-Term _{Evolution (LTE) is being extended or enhanced into a 5th Generation (5G)} technology, also called New Radio (NR) access. The following are requirements _{for 5G wireless communication networks: - Data rates of several tens of megabits per second should be supported for} tens of thousands of users; - _{1 gigabit per second is to be offered simultaneously to tens of workers on} the same office floor; - _{Several hundreds of thousands of simultaneous connections are to be} supported for massive sensor deployment; - _{Spectral efficiency should be significantly enhanced compared to 4G; - Coverage should be improved; - Signaling efficiency should be enhanced; and - Latency should be reduced significantly compared to 4G. [0003] As wireless communication evolves, it has become clear that different} wireless applications have very different demands on the network. For some applications, reliability of the connection is most important, such as security applications. For other applications, such as video streaming, high transmission

P110768 rate is most important, for yet other applications, such as machine-type communication, other demands apply. Also, different users of wireless devices may have different requirements on the network, e.g., depending on how a user uses their wireless device. For some users, latency is most important, for other users, throughput is more important. To cater for such different requirements, Service Level Agreements (SLA) may be set between users of wireless devices and communication network operators in which the operator promises to provide a _{set of wireless devices a service according to a service level defined in the SLA. Such a service level comprises one or more service-related measures, aka performance parameters that are to be fulfilled by the network operator. Examples of service-related measures/performance parameters are: throughput, i.e., how} much data that is provided to the wireless device per time unit, latency, i.e., how long time it takes to deliver a service, and data delivery reliability i.e. percentage of sent data that is correctly received. Throughput may be measured in e.g. Mbps. _{Latency may be measured in ms. For example, a set of wireless devices may have} agreed in the SLA with the communication network operator of a service level of a latency of 5 ms or lower and throughput of at least 10Mbps. _{[0004] One technology that has applied this service level concept and which} has evolved with 5G is network slicing. The basic idea of network slicing is to slice the network architecture in multiple logical and independent networks that are configured to effectively meet the various demands of the different applications or _{different set of wireless devices. For example, a first network slice has network} resources dedicated for providing machine-type communication, a second network slice has network resources dedicated for providing ultra-reliable low latency communication and a third network slice has network resources dedicated for providing enhanced mobile broadband content delivery. The service level _{requirements according to SLA are different for the different network slices. [0005] When using such SLAs for wireless devices in a communication network} there is a need to estimate how available network capacity matches with the service level requirements set in one or more different SLAs. For example, it is of interest to estimate whether amount of communication resources in a service area

P110768 is enough for delivering communication to a set of wireless devices in the service area, according to the service level agreed to in the SLA for the set of wireless devices. Such estimations may be used for example to determine whether it is possible to include more wireless devices into the service area. SUMMARY _{[0006] It is an object of embodiments of the invention to address at least some of the problems and issues outlined above. It is possible to achieve at least of one of these objects by using a method and one or more network entities as defined in} the attached independent claims. _{[0007] According to one aspect, a method is provided that is performed by one} or more network entities for estimating network capacity for serving wireless _{devices in a service area of a communication network. The communication network comprises at least one network node for providing wireless communication in the service area. Further, the communication network has a total} amount of communication resources for providing wireless communication in the _{service area via the at least one network node. The method comprises obtaining,} for a set of wireless devices served by the at least one network node, a requested value of each of one or more service-related measures according to SLA and obtaining, for the set of wireless devices, a delivered value of each of the one or more service-related measures. The method further comprises determining, for the set of wireless devices, an SLA distance that defines a distance between the requested value and the delivered value for the one or more service-related measures, based on the requested value and the delivered value for the one or more service-related measures. The method further comprises determining a communication resource margin for the set of wireless devices based on the SLA distance and a value related to a subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements, the communication resource margin being an estimated amount of communication resources needed to change the one or more service-related measures from the respective delivered value to the respective _{requested value. The method further comprises determining, for the set of wireless}

P110768 devices, an SLA assurance state based on the determined communication resource margin and on the total amount of communication resources, wherein the SLA assurance state defines whether or to what extent the determined communication resource margin can be fulfilled. _{[0008] According to another aspect, one or more network entities is provided that is configured to operate in or with a communication network and configured} for estimating network capacity for serving wireless devices in a service area of the communication network. The communication network comprises at least one network node for providing wireless communication in the service area. The communication network has a total amount of communication resources for providing wireless communication in the service area via the at least one network node. The one or more network entities comprises processing circuitry and a _{memory. Said memory contains instructions executable by said processing circuitry, whereby the one or more network entities is operative for obtaining, for a} set of wireless devices served by the at least one network node, a requested value _{of each of one or more service-related measures according to an SLA and} obtaining, for the set of wireless devices, a delivered value of each of the one or more service-related measures. The one or more network entities is further operative for determining, for the set of wireless devices, an SLA distance that defines a distance between the requested value and the delivered value for the one or more service-related measures, based on the requested value and the delivered value for the one or more service-related measures and for determining a communication resource margin for the set of wireless devices based on the SLA distance and a value related to a subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements, the communication resource margin being an estimated amount of communication resources needed to change the one or more service-related measures from the respective delivered value to the respective requested value. The one or more network entities is further operative for _{determining, for the set of wireless devices, an SLA assurance state based on the} determined communication resource margin and on the total amount of

P110768 communication resources, wherein the SLA assurance state defines whether or to what extent the determined communication resource margin can be fulfilled. _{[0009] According to other aspects, computer programs and carriers are also} provided, the details of which will be described in the claims and the detailed description. _{[00010] Further possible features and benefits of this solution will become} apparent from the detailed description below. BRIEF DESCRIPTION OF THE DRAWINGS _{[00011] The solution will now be described in more detail by means of exemplary} embodiments and with reference to the accompanying drawings, in which: _{[00012] Fig. 1 is a schematic diagram of a wireless communication network in} which the present invention may be used. _{[00013] Fig. 2 is a flow chart illustrating a method performed by one or more} entities, according to possible embodiments. _{[00014] Fig. 3 is a schematic diagram of the problem description of resource} allocation. _{[00015] Fig. 4 is a block diagram of an embodiment. [00016] Fig. 5 is a block diagram of another embodiment. [00017] Fig. 6 is a signaling diagram illustrating an embodiment. [00018] Fig. 7 is a signaling diagram illustrating another embodiment. [00019] Fig. 8 is a block diagram illustrating one or more entities in more detail,} according to further possible embodiments. DETAILED DESCRIPTION _{[00020] Fig. 1 shows an example of a communication network 100 in which the present invention may be used. The communication network 100 comprises a first}

P110768 _{radio access network (RAN) node aka network node 130 and a second network} node 135 that is in, or is adapted for, wireless communication with wireless _{communication devices aka wireless devices 140, 145. The first network node 130 is arranged to provide radio access in a first cell 132 covering a geographical area.} The second network node 135 is arranged to provide radio access in a second cell 137 covering a geographical area. The first and second network nodes 130, 135 _{are arranged for providing wireless communication in a service area 150 which covers the geographical area of both the first cell 132 and the second cell 137. [00021] The wireless communication network 100 may be any kind of wireless} communication network that can provide radio access to wireless devices. Example of such wireless communication networks are networks based on Global System for Mobile communication (GSM), Enhanced Data Rates for GSM _{Evolution (EDGE), Universal Mobile Telecommunications System (UMTS), Code} Division Multiple Access 2000 (CDMA 2000), Long Term Evolution (LTE), LTE Advanced, Wireless Local Area Networks (WLAN), Worldwide Interoperability for _{Microwave Access (WiMAX), WiMAX Advanced, as well as fifth generation (5G)} wireless communication networks based on technology such as New Radio (NR), and any possible future sixth generation (6G) wireless communication network. _{[00022] The first and second network nodes 130, 135 may be any kind of network node that can provide wireless access to the wireless devices 140, 145} alone or in combination with another network node. Examples of network nodes _{130, 135 are a base station (BS), a radio BS, a base transceiver station, a BS controller, a network controller, a Node B (NB), an evolved Node B (eNB), a} gNodeB (gNB), a Multi-cell/multicast Coordination Entity, a relay node, an access _{point (AP), a radio AP, a remote radio unit (RRU), a remote radio head (RRH)} and a multi-standard BS (MSR BS). _{[00023] The wireless device 140 may be any type of device capable of wirelessly communicating with a network node 130 using radio signals. For} example, the wireless device 140 may be a User Equipment (UE), a machine type _{UE or a UE capable of machine to machine (M2M) communication, a sensor, a}

P110768 tablet, a mobile terminal, a smart phone, a laptop embedded equipped (LEE), a laptop mounted equipment (LME), a USB dongle, a Customer Premises _{Equipment (CPE), an Internet of Things (IoT) device, etc. [00024] Embodiments of the invention are applicable to any kind of} communication network in which there is a service level agreement (SLA) between the communication network 100 and a set of wireless devices 140, 145, which agreement defines one or more service-related measures that are to be _{fulfilled by the communication network for delivering wireless communication to the set of wireless devices. An example of such a network is a network applying} network slicing. For network slicing, each network slice has its associated requirement on service level according to the SLA, which depends on the specifics of the communication of the network slice. How embodiments of the invention are applicable to the network slicing concept will be described in more detail further down in this document. _{[00025] Fig. 2, in conjunction with fig. 1, describes a method performed by one} or more network entities for estimating network capacity for serving wireless _{devices in a service area 150 of a communication network 100. The communication network 100 comprises at least one network node 130, 135 for providing wireless communication in the service area 150. Further, the} communication network 100 has a total amount of communication resources for providing wireless communication in the service area 150 via the at least one _{network node 130, 135. The method comprises obtaining 202, for a set of wireless devices 140, 145 served by the at least one network node 130, 135, a requested value of each of one or more service-related measures according to SLA and} obtaining 204, for the set of wireless devices 140, 145, a delivered value of each of the one or more service-related measures. The method further comprises determining 206, for the set of wireless devices 140, 145, an SLA distance that defines a distance between the requested value and the delivered value for the one or more service-related measures, based on the requested value and the _{delivered value for the one or more service-related measures. The method further comprises determining 208 a communication resource margin for the set of}

P110768 wireless devices 140, 145 based on the SLA distance and a value related to a subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements, the communication resource margin being an estimated amount of communication resources needed to change the one or more service-related measures from the respective delivered value to the respective requested value. The method further _{comprises determining 210, for the set of wireless devices 140, 145, an SLA} assurance state based on the determined communication resource margin and on the total amount of communication resources, wherein the SLA assurance state defines whether or to what extent the determined communication resource margin can be fulfilled. _{[00026] The term ”communication resources” comprises one or more of temporal resources such as time slots and frames, spectral resources such as frequencies} and physical resource blocks (PRBs), energy resources such as transmit power, and spatial resources such as beams produced by the network nodes and/or Multiple Input Multiple Output (MIMO). The ”set of wireless devices” may be between one wireless device to all active wireless devices in the service area. The set of wireless devices may also be the wireless devices which are within a partition of the service area. When each set of wireless devices comprises one or a few wireless devices, the method may be repeated for a plurality of such sets of wireless devices. The one or more service-related measures may also be called service-related Quality of Service (QoS) key performance indicators (KPIs). Requested values of one or more service-related measures according to SLA may be called ”a requested state according to SLA”. A service-related measure is e.g. throughput in e.g. bit rate, delay/latency, packet loss or energy consumption/power. If two such service-related measures are used, e.g. _{throughput and latency, the requested values are added into a vector, see further down for more information. The one or more service-related measures may be one, two or more service-related measures. The delivered values of the one or} more service-related measures is/are values at a current or recent time point, this may correspond to the term “actual SLA vector” as used further down in the _{description. The SLA distance may be a subtraction between requested and}

P110768 determined value. But in case there are more than one service-related measure they are not subtracted separately but together as vectors. See further in claim 3 below. Multiple options on how such a vector distance can be calculated have _{been suggested in the patent application. The value related to a subset of the total} amount of communication resources that are used for providing the delivered _{value for the one or more service-related measurements is a value related to the} subset of communication resources that are currently allocated to the set of wireless devices. It may be the same as the subset of communication resources that are currently allocated to the set of wireless devices. For example, the value related to a subset of the total amount of communication resources may be 1000 resources when the total amount of communication resources in the service area _{are 4000. The value related to a subset of the total amount of communication resources can be set based on a scheduler's allocation principles that determine} how communication resources should be divided among wireless devices based on conditions related to one or more of: QoS demands as expressed in SLA, channel conditions of the set of wireless devices, channel quality characteristics _{including interference, total traffic volume of the set of wireless devices, and} scheduling approaches incl. proportional-fairness, round-robin, max C/I scheduler etc. _{[00027] Further is an example of the method described: The set of wireless} devices are all wireless devices within the service area. The service-related measures are latency and throughput, that is, two different measures. The requested value of latency according to SLA is 10 ms. The requested value of throughput is 100 Mbps. The delivered value for latency is 12 ms and the delivered value for throughput is 80 Mbps. The delivered values can be for example average value over the set of wireless devices in the service area, or the lowest percentile. The SLA distance is then determined based on the requested and delivered value _{of latency, that is 12 and 10 ms, which means a lack of 2 ms, and based on} requested and delivered value of throughput, that is 100 and 80 Mbps, which _{means a lack of 20 Mbps. The SLA distance can be determined as a vector, as further defined in embodiments below. The communication resource margin, aka SLA elasticity distance, is the amount of communication resources that is}

P110768 estimated are needed to cover the SLA distance, that is, how many communication resources are estimated to be needed in order to decrease the latency from 12 ms to 10 ms and to increase the throughput from 80 Mbps to 100 Mbps, in addition to the subset of the total amount of communication resources that are used for providing the delivered value now. The SLA assurance state defines whether, or to what extent, this can be fulfilled, taken the total amount of communication resources in the service area into consideration. _{[00028] The one or more network entities that performs the method may be, or be} situated in, a node of the communication network 100, such as in any of the at _{least one network node 130, 135. Alternatively, the one or more network entities is} situated outside of the communication network 100, but connected to the communication network 100. Still alternatively, the functionality of the one or more _{network entities is spread out over a group of network nodes. The group of} network nodes may be different physical, or virtual, nodes inside or outside of the communication network 100. This alternative realization may be called a cloud- solution. _{[00029] By such a method, a good estimate is achieved whether the amount of communication resources in the service area currently allocated to the set of wireless devices is enough for delivering communication to the set of wireless,} according to the service level agreed to in the SLA. Put it in another way, a good estimate is achieved on how many communication resources are needed to allocate in addition to the already allocated resources to the set of wireless _{devices to be able to deliver according to the SLA. Also, in case the estimation} shows there is a surplus on communication resources for the set of wireless devices for delivering according to SLA, some of the communication resources allocated to the set of wireless devices can be distributed to another set of wireless devices. Based on the estimation, such distribution or allocation of communication can be performed. As an end result, communication resources in _{the communication network can be used in a more optimal way, taking the} obligations of the SLAs into consideration. P110768 _{[00030] According to an embodiment, the method further comprises determining} 207, for the set of wireless devices, an SLA resource coefficient that is an estimation of amount of the communication resources required per delivered value for the one or more service-related measures, the SLA resource coefficient being based on the subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related _{measurements. Further, the determining 208 of the communication resource} margin for the set of wireless devices 140, 145 is based on the SLA resource _{coefficient and the SLA distance. According to an embodiment, the SLA resource} coefficient may be equivalent to the value related to a subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements mentioned above. The SLA resource coefficient may be different from wireless device to wireless device. _{[00031] As a simple example, if the requested value of latency according to SLA is 10 ms and the delivered value of latency is 12 ms, one can analyze the number} of additional PRBs needed for improving latency with 2 ms for the set of wireless devices and determine that 200 PRBs are needed. Consequently, the amount of _{communication resources required per ms is then 200/2 = 100 PRBs. This} example is a simplified one-dimensional vector. If there are more than one SLA _{resource coefficient, for example latency (in ms) and throughput (in Mbps), it is a bit more complicated to determine the SLA resource coefficient per ms and Mbps} as an increase in number of PRBs would also increase the throughput. Examples _{on how this may be done is shown further down. The usage of such an SLA resource coefficient provides an improved method of estimating whether the} amount of communication resources in the service area currently allocated to the set of wireless devices is enough for delivering communication to the set of wireless, according to the service level agreed to in the SLA. _{[00032] According to another embodiment, the SLA distance for the set of wireless devices is determined 206 as a distance between an x-dimensional vector} of the requested value of the one or more service-related measures and an x- dimensional vector of the delivered value of the one or more service-related P110768 measures, wherein x is the number of different service-related measures and wherein x is at least one, or at least two. _{[00033] When x = 1, the vectors will be a one-dimensional vector, that is along a} line. When x = 2 or more, the vectors will be in corresponding two or more dimensions. Such a vector subtraction can be made by many different methods. _{For example, embodiments using an L1 and L2-based (Euclidean) method as it would be manifested in a Cartesian coordinate system are described in more} detail below, as well as other embodiments to express vector distance or vector _{similarity based on the cosine function with variances and normalizations. Such a} method of using vectors provides an improved method of estimating whether the amount of communication resources in the service area currently allocated to the set of wireless devices is enough for delivering communication to the set of wireless, according to the service level agreed to in the SLA. _{[00034] According to another embodiment, the method further comprises transmitting 212 information on the determined SLA assurance state for the set of wireless devices to the at least one network node 130, 135. Hereby, the network} nodes are made aware of the SLA assurance state, and can make decisions whether to increase or decrease amount of resources allocated to the set of wireless devices accordingly. _{[00035] According to yet another embodiment, the communication resource margin is further determined 208 based on amount of vacant network resources or} amount of utilized network resources of the total amount of network resources at a certain time point. _{[00036] According to yet another embodiment, there is a plurality of sets of} wireless devices within the service area, the plurality of sets including the set of _{wireless devices. Further, the method comprises performing the method of any of} the preceding embodiments for each of the plurality of sets of wireless devices. _{[00037] According to yet another embodiment, the communication resource margin determined 208 for each of the plurality of sets of wireless devices are} P110768 summed up into a total communication resource margin for the plurality of sets of _{wireless devices. Further, the SLA assurance state is determined 210 for the plurality of sets of wireless devices 140, 145 based on the determined total} communication resource margin and on the total amount of communication _{resources. Each of the plurality of sets of wireless devices is a subset of the} wireless devices in the service area, the subsets being mutually exclusive, i.e. a wireless device is only part of one such subset. Each of the plurality of sets of wireless devices may comprise from only one wireless device up to all but one wireless device of the wireless devices in the service area. This embodiment _{defines, for example, what to do when a set of wireless devices is smaller than all wireless devices in the service area, but it is to be determined whether the total} amount of communication resources are sufficient for all wireless devices in the service area. _{[00038] According to still another embodiment, the method further comprises} determining 214, based on the SLA assurance state for the plurality of sets of wireless devices, whether an additional set of wireless devices can be added to the service area in addition to the plurality of sets of wireless devices. _{[00039] According to still another embodiment, the communication network 100} has a plurality of network slices configured, each network slice being allocated a share of the total amount of network resources within the service area. The _{method is performed per such network slice, and the determining 210 of the SLA} assurance state is based on the share of the total amount of communication _{resources that the certain network slice is allocated. The network slice concept} may be performed for one set of wireless devices, wherein one such set may be _{some or all wireless devices in the service area. Alternatively, the network slice} concept may be performed for a plurality of sets of wireless devices as defined in _{some embodiments above. For the network slice concept, the method may be} repeated for many or all network slices as well as for a plurality of set of wireless devices. P110768 _{[00040] According to an embodiment of the above embodiment where the} communication network 100 has a plurality of network slices configured, the _{method further comprises determining 213, based on the determined SLA assurance state for the set of wireless devices, whether an additional network slice} can be configured in the communication network in addition to the plurality of network slices. _{[00041] In the following different examples or embodiment of the present invention are described. A problem that is discussed is to determine or estimate} the SLA assurance state for ensuring that the SLA in relation to Quality of Service (QoS) within a service area such as a cell, a tracking area or any other kind of _{service area can be satisfied with a certain probability. The problem boils down to identifying the communication network capacity. To do so, a communication} resource margin is computed to determine the current SLA assurance state. There are a couple of use cases tied to the size of the communication resource margin. In one example, the available communication resources can be redistributed according to the communication resource margin. In another example, it can be _{determined whether a new network slice can be supported. In yet another} example, it can be determined whether a new communication device or set of communication devices or communication device entity can be added. The examples can be combined so that it can be determined whether, based on the communication resource margin, new communication devices can be added within a network slice, etc. _{[00042] Fig. 3 presents a problem definition for an example in which a communication network has two network slices configured: Slice 1 and Slice 2, and there are two different sets of SLA entities in the service area. An SLA entity is} an entity of the RAN domain governed by the SLA requirements. In some _{embodiments, the term “SLA entity” is equivalent to the term “a set of wireless devices”. Such an SLA entity can be an individual wireless device or a group of wireless devices. Note that the SLA entity can as well represent all wireless devices in a network slice. The SLA requirements comprises a requested value of each of a number of service-related measures, aka QoS Key Performance} P110768 _{Indexes (KPI). In fig. 3 there is a resource domain 310 which defines the total amount of communication resources 312 in the service area and an assurance} domain 320 that defines the amount of communication resources needed to _{deliver service according to the SLA requirements. Slice 1 has a first slice} resource share 314 of the total amount of communication resources 312 and Slice 2 has a second share 316 of the total amount of communication resources _{312. The respective first and second slice resource share 314, 316 indicates the prioritized shares of resources of the respective first and second slice to the other one of the first and second slice within the resource domain 310. For example, if} the resource shares between Slice 1 and Slice 2 is 1:2 and there is resource contention for all slices, wireless devices of Slice 1 will have on average half of the _{communication resources than the wireless devices of Slice 2. Fig. 3 further} indicates amount of utilized communication resources 324 of the first slice _{resource share 314 for wireless devices 1.1, 1.2, 1.3 and 1.4, which are the} wireless devices of Slice 1.322 indicates amount of remaining or vacant _{communication resources for slice 1. Similarly, in fig. 3, 328 indicates amount of} utilized communication resources of the second slice resource share 316 for _{wireless devices 2.1, 2.2 and 2.3, which are the wireless devices of Slice 2. 326} indicates amount of remaining or vacant communication resources for slice 2. _{[00043] SLA entity resource share is specified per SLA entity in a RAN slice. In the case where the SLA entity is one wireless device, it is a share of resources in the resource domain which has been assigned to the wireless device. As an example, there are 3 wireless devices within slice A, and their wireless device} resource shares have relations 1:2:4. When there is a resource contention within _{the slice A, the third wireless device will have four-times and two-times resource more than the first and second wireless device, respectively. [00044] In the case where the SLA entity is a group of wireless devices, entity resource share is a share of resources from the resource domain for that group} relative to other SLA entities within the same slice. For example, there are two groups of wireless devices within slice A, group 1 has 3 wireless devices and group 2 has two wireless devices, while the SLA entities resource share relation P110768 for the two groups are 1:2. When there is a resource contention within the slice A, group 2 will have two times resource more than group 1. Regarding the allocation of resources within the group, it can be in many ways, but this is not in the scope _{of this disclosure. [00045] A problem formulation according to this embodiment is based on a} function h that maps the SLA domain 330 with the resource domain 310 where the SLA domain corresponds to the SLA requirements and the resource domain to the _{resource shares. Based on this mapping it is possible to determine whether the} resource margins in the system can compensate for a certain SLA deficit, and, _{consequently, derive an indication of a state of RAN SLA assurance. [00046] In the example of fig. 3, wireless device 1.2 in Slice 1 has SLA} requirements 332, for example the service-related measures, aka Quality of _{Service (QoS) metric, throughput ≥ x1 Mbps and latency ≤ y1 ms. However, the} service-related measures of the SLA requirements are not fulfilled with the _{communication resources that device 1.1 has, as indicated by 334. The deficit in} actual service-related measures and the required service-related measures _{according to SLA for device 1.1 is indicated by the striped area 336 in the SLA} domain 330. The resources that device 1.1 has is indicated in sub-field 1.1 in the _{utilized resources-field 324 in the resource domain 310. In the same way, wireless device 1.4 in Slice 1 has SLA requirements throughput ≥ x2 Mbps and latency ≤ y2 ms. However, those service-related measures according to the SLA requirements} are not fulfilled with the communication resources that device 1.4 has. The currently utilized communication resources for device 1.4 are indicated in sub-field _{1.4 in the utilized resources-field 324 in the resource domain 310. The deficit in service-related measures to achieve the SLA domain requirements for device 1.4 is indicated by the striped area 338. A question is then whether the amount of} remaining or vacant communication resources for slice 1, indicated by field 322 are enough to improve throughput and latency for device 1.1 and 1.4 to reach their respective SLA requirements in throughput and latency when the remaining communication resources 322 are allocated to device 1.1 and 1.4. Devices 2.1, 2.2 and 2.3 also have deficits between their service-related measures according to P110768 the SLA requirements and their actual service-related measures, which deficits are indicated with striped fields 340, 342 and 344, respectively. So, a question is then whether the amount of remaining or vacant communication resources for slice 2, indicated by field 326 are enough to improve throughput and latency for devices 2.1, 2.3 and 2.3 to reach their respective SLA requirements in throughput and latency when the remaining communication resources 326 for slice 2 are allocated to device 2.1, 2.2 and 2.3. Another possible question is whether it would be possible to re-allocate resources between Slice 1 and Slice 2 if there is a deficit in one Slice but vacant resources in the other Slice. _{[00047] In the case an SLA entity is a group of wireless devices, three different embodiments for SLA conditions may apply. The first embodiment is that SLA requirements are violated when any wireless device within the group has a QoS metric that does not fulfil the SLA requirement. The second embodiment is that SLA requirements are violated when an average of QoS metrics from all wireless devices within the group has a QoS metric that does not fulfil the SLA requirement. The third embodiment is that SLA requirements are violated when a sum of QoS metrics of all wireless devices within the group has a QoS metric that does not} fulfil the SLA requirement. _{[00048] According to an embodiment, solutions are disclosed to the problem of} estimating a system capacity of a network element, e.g., a base station, for serving RAN traffics, e.g., wireless devices or network slices, under a specific Service Level Agreement (SLA). The estimation is based on quantifying RAN elasticity distance, a single numerical quantity that summarizes available resource margins for complying with the SLA. Such derived information can be _{exchanged between, or sent to, network elements and/or RAN entities, i.e. network nodes, as an indicator of the capacity that the system can provide.} Specifically, a high elasticity distance indicates high resource margins to address large deficits, while a low elasticity distance implies low resource margins to address any deficits. P110768 _{[00049] One or more of the disclosed solutions enables a solution for SLA} assurance, which is quality of experience for telecommunication services. This would enable premium connectivity service, which can be additional revenue streams for communication service provider. The disclosed solutions are automated and does not require manual operations by service design. Thus, the _{disclosed solutions enable reduced operation expenses for communication service provider for providing, e.g., RAN slicing. One or more of the disclosed solutions allows for querying network elements about the indications of resource margins it} is obliged to serve RAN slices, through the RAN elasticity coefficient. By requesting such a margin indication, the SLA target assurance can be estimated at any time or any time interval. _{[00050] One or more of the disclosed solutions introduces an estimation of the} mapping of the targeted slice’s SLAs and the deficit or excess of resources to accommodate the targeted slice’s SLA. The advantage of this is that at any time, _{the network, or the one or more entities, may indicate the ability to assure existing} or newly added SLAs. As such it can be used to support slice SLA assurance, slice SLA admission, and slice SLA planning in a service area. _{[00051] In the following, basic concepts and notations are introduced that are} used in some of the embodiments, which embodiments comprises the use of network slices. _{[00052] SLA entity – SLA entity is a communicating entity, the communication of which is specified by a set of n QoS or KPI requirements ^ = {^^,^^, … , ^^} defining an SLA vector, ^ = {^^, ^^, … , ^^}, of length ^. The n QoS KPI} requirements may also be called required values for each of n service-related _{measures. The SLA vector may be associated with an individual wireless device, aka UE, or a group of UEs. As another embodiment, the SLA vector may also be} associated with individual flows for individual UEs. _{[00053] RAN slice resource share (for a resource) and SLA entity resource share} (for a resource). RAN slice resource share is specified per RAN slice; it is a non- negative integer number indicating the prioritized shares of communication P110768 resources of this network slice in relation to other network slices. SLA entity _{resource share is specified per SLA entity in a RAN slice. In case the SLA entity is one UE, SLA entity resource share is a share of communication resources which the UE has been assigned. In case the SLA entity is a group of UE, the SLA entity} resource share is a share of resources for that group of UEs relative to other SLA entities within the same slice. _{[00054] RAN slice configuration for SLA assurance of QoS in the RAN. SLA assurance of QoS refers to guaranteeing network slice SLA delivery according to the SLA quality demands of the slice. The problem may be transferred to determining a coefficient that indicates the elasticity margin for the assurance of} QoS in accordance with the SLA, here referred to as RAN SLA Assurance (RSA) elasticity coefficient. _{[00055] SLA distance. Let SLA target qt=(qt1, qt2, …, qtn) denote the SLA target} vector in the n-dimensional requirements space of KPIs and QoS of an SLA entity, _{also called requested values of each of the n service-related measures. In one example embodiment, the SLA target vector is a 2-dimensional vector q=(q1, q2) where q1 corresponds to requested throughput given as X kbs and q2 to a requested latency given as Y ms. Let also qa=(qa1, qa2, …, qan) denote the SLA actual vector where we currently operate, also called delivered values of each of the n, in this example two, service-related measures. The SLA current or actual vector refers to the KPIs and QoS values of an SLA entity that are measured at a} current or recent time instance. _{[00056] Determining the SLA distance, i.e. the distance between the SLA target} vector and the SLA actual vector can be done in many different embodiments by _{utilizing the mathematical concept of the norm that applies to a vector. The norm of a vector maps vector values to values in [0, ] and is useful because it can express distances between vectors. The p-th norm Lp of a vector is denoted ‖^‖p and is defined by:} (1) The most used norms are are given by: P110768 (2) _{( is defined as the norm of the difference} vector between the SLA target vector and SLA actual vector and is given by the l_{ength of the SLA distance vector d = qt − qa = (qt1 − qa1 , qt2 − qa2 , . . . , qtn − qan). For The L2-norm, the SLA distance of the d vector is calculated as follows:} (4) will be abandoned. [_{00057] SLA norm distance. In another embodiment, the SLA distance δ can be} defined as the difference between the norms of the SLA target vector and the SLA a_{ctual vector, i.e., d = ∥qt∥ − ∥qa∥. In terms of the L2-norm, the SLA norm distance} is calculated as follows: (5) This the SLA a_{ctual vector fulfills the SLA target vector, however, this is the case if and only if ∀^, ^^^^^ ≤ ^^^^^. In a further embodiment, the SLA distance δ is represented by means of the inner} product of the SLA target vector and the SLA actual vector as follows: (6) . _{gives no relative} indication of the distance, in another embodiment the SLA distance can be normalized. Based on (6) and the Gauchy-Schwarz inequality (see https://en.wikipedia.org/wiki/Cauchy%E2%80%93Schwarz_inequality), the inner- p_{roduct defined SLA distance can be normalized as follows} P110768 (7) _{When δn = 0, the SLA and when δn = 1 the} SLA target and the SLA actual are at the longest distance. An adjusted version of the SLA normalized distance δ_n can be also defined as follows: (8) _{[00059] as the} ^{number of resource units required to achieve a unit of the SLA norm distance} _{∥qunit∥ and may differ between SLA entities. Examples of resource unit include} bandwidth (if we assume the transmission power is fixed). The norm unit (r_tar) is _{then the amount of resources needed to achieve one bandwidth unit and is} indirectly defined by the SLA. (9) _{In one embodiment, the SLA h can be a function of the modulation-and-coding scheme (MCS), μ of the SLA entity, e.g., h = f (MCS), in} absolute values or h = f (μ/μmax), in normalized values. Since the radio resource _{coefficient h differs across SLA entities, it has to be estimated. An estimation ℎ^ of h may in one embodiment correspond to an average norm value that has been} established either based on long-term or short-term statistics. The former may correspond to the average of MCS, ^̂_^ of SLA entities over a longer period, which is a more robust estimation, while the latter may correspond to the average of MCS, ^_^̂ of the current set of SLA entities over a shorter window of the current is a more accurate instant value. _{[00060] In further embodiments, h can be defined as a function of channel state} estimations or measurements, such as, MCS, Channel Quality Indicator (CQI), Signal to Interference and Noise Ratio (SINR), Reference Signal Received Power _{(RSRP), UE Specific Reference Signal (URS), and/or UE mobility estimations or measurements, such as UE speed, UE position, UE velocity, incl. estimated speed, and direction. In another embodiment, h can be defined as a combination} of any of the above, e.g., h = f (CQI, …, UE_Velocity), etc. P110768 _{[00061] RAN SLA Assurance (RSA) elasticity coefficient. Let ravail denote the} amount of available communication resources for an SLA entity at any time, r_util denote the nominal amount of utilized communication resources, and r_tot the total _{number of communication resources in the service area. Then at any time, the available number of communication resources is given by ravail = rtot − rutil and consequently rutil = rtot − ravail holds. The resource deficit can be calculated as a mapping of communication resources to SLA entities, given that ∥qa∥ is achieved} ^{with r} _util ^{amount of communication resources, and that all communication} _{resources contribute equally. Given these resource quantities, the RSA elasticity} coefficient η is used to determine the communication resource margin, i.e. the number of resource units required up to a maximum to achieve the SLA distance _{δn. The RSA elasticity coefficient is a form of SLA distance δn transform reflecting} the effective contribution of resources to the SLA target. Opposite to radio _{resource coefficient h, the RSA elasticity coefficient η indicates the margins for} serving an SLA entity, and it is typically used to determine an estimation of the number of resources that can be made available at maximum to an SLA entity’s SLA distance. The number of resources can be calculated according to different embodiments based on the available resources, the residual ones and/or any combinations thereof. _{[00062] In one embodiment the RSA elasticity coefficient η can be nominally} expressed in terms of utilized or available resource fractions by (10) where r_avail are the amount and r_tot is the total amount of resources. _{In another embodiment the RSA elasticity coefficient η can be nominally} expressed in terms of required resource fraction by (11) where r_res is the amount of required resources. _{In yet another embodiment the RSA elasticity coefficient η can be nominally} expressed in terms of utilized, available and/or required resources by P110768 (12) Assuming all is an indication that resources are not enough to fill the distance gap δ_n. _{[00063] SLA elasticity distance (ω). Meeting the SLA target given the SLA distance δ, the RSA elasticity coefficient η indicates the margins that are available to compensate for the SLA distance δ. Firstly, the RSA elasticity coefficient refers} to the availability of resources by a scheduler to compensate for the SLA distance. _{Secondly, assuming that the SLA distance indicates the proportion of resources} required to fulfill the SLA target then the compensating RSA elasticity coefficient _{should not exceed and be limited by η → 1 – ρutil, where ρutil = rutil / rtot is the utilization ratio/factor. Given the RSA elasticity coefficient η as corresponding to an} adjustment of SLA distance δ and, reflecting the effective contribution of resources to the SLA target, the SLA elasticity distance ω can be defined as (13) _{As illustrated in fig. 4, equation to a transformation 404 of the SLA distance δ 402 in the KPI or QoS domain to an SLA elasticity distance ω 406} in the resource domain. _{[00064] RSA elasticity coefficient within/across levels. The RSA elasticity} coefficient η and elasticity distance ω can be defined within and across different _{levels: UE level - At a UE level across UEs and within a slice; Slice level - At a slice level across slices and within a partition; Partition level - At a partition level} across partitions and within a deployment area. A partition may be a set of RAN slices. A partition can be used to semantically group a set of slices, for instance, a _{RAN partition for Mobile Broadband (MBB) slices, while another RAN partition is for Ultra Reliable Low Latency Communication (URLLC) slices. To ease the} estimations, the remaining sections assume calculations according to the first RSA elasticity embodiment, i.e. at UE level. Without loss of generality, the estimations can be used for the second and third embodiments, i.e. slice level and partition _{level under the following definition assumption:} P110768 (14) _{[00065] assume the s-} th slice with N number of UEs, of which M UEs have non-zero SLA distances. All idle UEs, without traffic demands are by definition UEs with zero-SLA distances _{with rutil = rtar = 0. Based on these assumptions, the aggregate slice utilization ratio} ρs of the s-th slice is given by (15) , where ρs ≤ 1 and ρs,k is the the k-th UE within the s-th slice. The aggregate SLA user distance δs within the s-th slice is given by: (16) , where δs,k is the SLA the s-th slice. Assuming that the elasticity coefficient of the s-th slice (according to the first embodiment) is (17) , then the elasticity distance ωs (18) , and the minimum elasticity th UE with SLA distance δs,k given the s-th slice can be estimated by (19). _{[00066] RSA elasticity} p_{artition is a resource allocation level that is higher than a slice. Given the previous definitions, we can} define the elasticity coefficient ηp and elasticity distance ωp of the p-th partition consisting of Sp slices and UEs of which UEs with non-zero elasticity P110768 The aggregate distance δp of the p-th partition is given by (20), where δs is the SLA Let the elasticity coefficient ηp of the p-th partition be defined as (21). Then the elasticity ηp×δp and the _{minimum elasticity distance ωp,s,k of the k-th UE with SLA distance δp,s,k given} the s-th slice of the p-th partition can be estimated by (22). _{[00067] RSA level. A deployment area} or a deployment is a resource allocation level that is higher than a partition corresponding to a subset of the deployed infrastructure serving UEs in a certain (geographical) service area. A concrete embodiment of a deployment is a dual connectivity use case that will be elaborated on further down. Given the previous _{definitions, we can define the elasticity coefficient ηd and the elasticity distance ωd} of the d-th deployment consisting of Pd partitions each with Sp slices and UEs of which UEs with non-zero _{is given by:} (23), where δp is the Let the elasticity coefficient ωd of the d-th deployment be defined as (24), where the s-th slice of the p- th partition. P110768 Then the elasticity distance ωd of the d-th deployment is ωd = ηd × δd and the minimum elasticity distance ωd,p,s,k of the k-th UE with SLA distance δd,p,s,k given the s-th slice of the p-th partition of the d-th deployment can be estimated by (25). _{[00068] previous embodiments, the} RSA elasticity coefficient and elasticity distance have been defined and calculated in a deterministic manner based on calculations. The RSA elasticity coefficient of a slice indicates how much the system can compensate given traffic, channel quality, UE mobility, and/or any combination thereof. At any decision time, traffic, channel quality, and UE mobility-related parameters can be used as features to derive the RSA elasticity coefficient required to compensate for discrepancies between the SLA target and the SLA actual. _{[00069] In one embodiment of this invention, the disclosed method determines if the elasticity distance is sufficient to serve the SLA distance (deficit) between the SLA actual and the SLA target. In a deterministic scenario, the objective is to} estimate whether an SLA target can be assured or whether it is violated. _{[00070] In embodiments of this invention, the SLA assurance state corresponds} to an estimated and/or confirmed parameter that indicates whether an SLA target is assured or violated. The SLA assurance state may take binary values for the estimation where a value of 1 indicates SLA assurance success and a value of 0 indicates SLA assurance failure. Alternatively, the SLA assurance state may take _{continuous values in the interval of [0,1] indicating the estimated probability of} successful assurance. _{[00071] In one embodiment, a binary elasticity margins indicator can be} determined by comparing the total r_res and total r_avail. If the estimated amount of required resources is larger than the amount of available resources that can be shared among the UEs in the slice or even among slices, then the elasticity margins are not sufficient, and the SLA assurance state is violated. This would imply a situation when the SLA elasticity distance has its highest value. P110768 _{[00072] In another embodiment of the invention, the margin may be a continuous} value in the interval [0,1], instead of binary, allowing for various degrees of SLA distances and for expressing the success or violation SLA assurance state with _{probabilities. To this end, if the amount of required resources is much smaller than} the amount of available resources, then the distance will be small, and hence, the probability of violating the SLA target will be also small. On the other hand, if the amount of required resources gets as high as the amount of the available resources, then the SLA elasticity distance will get its highest value and the probability of violating the SLA target will be also very high. _{[00073] In a further embodiment, by assuming the existence of historical} breakthrough data, the estimation of the SLA assurance state can be derived. _{[00074] Fig. 5 illustrates a method according to an embodiment. The method} executes in three major steps and uses three broad input categories. _{[00075] The first input category 502 refers to UE context information and it comprises UE traffic information, such as expected amount of traffic within a time} period, amount of utilized communication resources (r_util) and r_tar, UE channel information, such as MCS, CQI, SINR, RSRP, URS etc, from which the radio _{resource coefficient (h) can be determined, and UE mobility information such as} UE position and estimated speed and direction, which also may be input to _{determining h. Apart from the UE context information, there are two SLA-related input categories. A second input category 504, which is referred to as the SLA} target state or SLA profile, contains the SLA target values of the KPIs defining the requested values of the service-related measures according to SLA. The second input category may also comprise current communication resource allocation such _{as RAN entity/slice resource share in %, rutil, rtar and ravail. A third category 506,} which is referred to as SLA actual state, contains the actual SLA values, i.e., delivered values of the service-related measures. _{[00076] Based on the input of one or more of UE context information, SLA target state information and SLA actual state information, the method first determines at 508.1 SLA distance ^^ at each level ^ according to the embodiments that are} P110768 _{expressed in equations (1)–(8) above, wherein ^ defines whether it is at UE level, slice level, or partition level. The aggregated distances for all UEs or group of UEs,} all slices or all partitions are calculated according to equations (16), (20) or (23) _{respectively. Then the method determines in 508.2 the SLA elasticity coefficient ^^ and elasticity distance ^^ at level ^ based on the calculations of one or more of} r_util, r_res, r_tar, r_avail, r_tot and ρ_s, and according to the embodiments that are expressed _{in equations (9)-(15). Whether ^ is at UE level, slice level, or partition level, the} SLA elasticity coefficients for each UE, slice or partition are calculated according _{to equations (17), (21) or (24), respectively, while the SLA elasticity distances are calculated according to equations (18)-(19), (22) or (25), respectively. Thereafter,} the method determines 508.3 the SLA assurance state, e.g. whether the SLA requirements can be assured (success) or whether the SLA requirements cannot _{be assured (violation). The determination may be performed by comparing the RSA elasticity distance with a value related to a subset of the total amount of} communication resources, wherein the value may be a value related to the total _{amount of vacant resources, to derive elasticity margins and whether the SLA assurance state is acceptable or violated. The SLA assurance state determination} can be applied at (i) UE level to determine if the SLA target for a UE will be violated, (ii) slice level to determine if the SLA target for an entire slice is violated, _{and (iii) partition level to determine if SLA targets of the slices within a partition will} be violated. _{[00077] The derived information, i.e. the RSA elasticity distance or coefficient,} can be exchanged between network partitions and RAN entities as an indicator of _{the SLA capacity the network can provide. The information allows the one or more entities to query a RAN entity, such as a gNB, about the margins it has to serve} network slices. By requesting an indication about the elasticity distance, the SLA assurance state can be estimated at any time or any time interval, for instance, when attempting to introduce a new SLA within a partition or serve a new UE within a network slice. A high elasticity distance indicates high resource margins to address large deficits, while a low elasticity distance implies low resource margins to address any deficits. P110768 _{[00078] In the following, sequence diagrams are discussed illustrating signaling} between network entities. In doing so, two embodiments are shown. In fig.6, a distributed RAN resource recommendation embodiment is described and in fig.7 a _{centralized RAN resource recommendation embodiment is shown. In figs. 6 and 7,} processing steps are denoted as A1-A4 while signaling steps are denoted S0-S5. For the steps in the sequence diagrams, the following assumptions and notations are used: “A” represents a geographical service area, e.g., 1.) a specific geographical area, e.g., a certain city, 2.) a tracking area, or 3.) a set of geographical coordinates; “S” represents a set of SLA entities. As mentioned earlier in this document, an SLA entity may be a set of UEs, i.e., one or more UEs; “G” represents a set of base stations, e.g., gNB1, gNB2, …, gNB |G|. _{[00079] In fig. 6 and 7, an apparatus 600, aka “one or more entities”, obtains a request S0 for estimating network capacity for SLA entities 630 within a service} area A, the service area S comprising a plurality of network nodes gNB1610 and _{gNB2620. The request S0 comprises among others the SLA profile-related information, such as, SLA target QoS/KPI values, qt=(qt1, qt2, …, qtn). Such a} request S0 triggers step A1, wherein the apparatus 600 is to obtain input data for determining the SLA assurance state of the SLA entities S for the set of base stations G within service area A. The input data include but is not limited to channel estimation, mobility prediction, etc. To obtain the required input, two signals S1 and S2 are sent. The first signal S1 is a request for configuration and measurement related to SLA entities S within A, which is sent to each of the gNBs 610, 620. The second signal S2 is a request for SLA entity-specific measurements, e.g., channel state information, position of the SLA entity. The second signal S2 is sent by the respective gNB 610, 620 to their respective SLA _{entities 630. S2 may be sent on request of the apparatus 600 or the respective gNB 610, 620 may perform this anyhow with their respective SLA entities for other} purposes. _{[00080] The signal received from the respective gNB 610, 620 in response to the S1 signal, called “S1 response”, comprises among others SLA state related information, including for example the actual SLA values, qa=(qa1, qa2, …, qan), and} P110768 _{resource related estimations, such as rutil, rres, rtar, ravail, rtot and ρs. The signal} received from the respective SLA entity 630 via the respective gNB 610, 620 in _{response to the S2 signal, called “S2 response” comprises among others UE context-related information, such as one or more of UE uplink traffic information,} incl. bitrate/latency/loss/buffer size, etc., UE channel state estimations or measurements, such as, MCS, CQI, SINR, RSRP, URS, and/or UE mobility estimations or measurements, such as user speed, user position, user velocity, incl. estimated speed, and direction. _{[00081] Thereafter follows step A2 in which the apparatus 600 computes RAN SLA Assurance (RSA) elasticity coefficient indicating the communication resource margin for each SLA entity S 630 for each gNB G 610, 620. For the distributed} embodiment, which is the embodiment of fig.6, this step involves sending a signal _{S3 comprising the RSA elasticity coefficient to each gNB 610, 620. For the} centralized embodiment of fig.7, signal S3 is omitted. For the distributed _{embodiment of fig. 6, step A2 may correspond to the three-step elasticity embodiment described above for determining the SLA distance ^^, the RSA} elasticity coefficient ^_^, and the RSA elasticity distance ^_^ at each level ^, where ^ _{can correspond to slice or partition levels The S3 signal may comprise one or more of the determined SLA distance ^^, the RSA elasticity coefficient ^^, and the} RSA elasticity distance ^_^ at any level ^. _{[00082] Then step A3 is performed in which a recommended RAN slice resource configuration, e.g., RAN entity share, is determined for each SLA entity 630 for each of the gNBs G 610, 620. Using the computed RSA elasticity coefficient, this} step is for recommending RAN slice resource configuration for SLA entities S 630 _{for each gNB in G = {g1, g2}). As an embodiment to perform this, it can be a simple} recommendation like allocating entity share proportionally to the RSA elasticity coefficient. Alternatively, it can be a complex recommendation like using support _{from a machine learning model. For the distributed embodiment of fig. 6, the} determination A3 of recommended resource configuration is performed by one the _{gNBs, in the example of fig. 6, gNB1610. The determined recommended resource} configuration is then sent in signal S4 from gNB1 to the other gNBs in the service P110768 _{area A, in the example of fig. 6, gNB2620. The S4 signal of fig. 6 may comprise} among others the SLA assurance state and whether resources can be freely used or whether resources should be used with care, for instance, when SLA assurance is violated. For the centralized embodiment of fig.7, the determination A3 of recommended resource configuration is performed by the apparatus 600, which is also why the S3 signal can be omitted. The S4 signal of fig.7 comprises among others the SLA assurance state and whether resources can be freely used or whether resources should be used with care, for instance, when SLA assurance is violated. _{[00083] Then step A4 is performed in which the recommendation of RAN resource configuration is applied and executed by each gNB 610, 620. Thereafter,} an S5 signal is sent, which comprises an adjusted resource allocation in RAN for _{each SLA entity 630 in S according to the applied resource configuration. [00084] In the following, the impact on standardized technical specifications by at} least some of the described embodiments is further described. The below explanation is based on a dual connectivity (DC) use case, wherein dual connectivity is a standardized function of radio access networks. For the following description, the following assumptions are used: A represents a geographical service area, e.g., 1.) a specific geographical area, e.g., a certain city, 2.) a tracking area, or 3.) a set of geographical coordinate, wherein A is assumed to comprise a deployment; G is a set of base stations, e.g., gNB1, gNB2, …, gNB |G| covering subareas in deployment A that are partly overlapping, wherein each base station constitutes its partition, and each partition accommodates the same slice; S represents a set of SLA entities in service area of deployment A. As mentioned earlier in this document, an SLA entity is a set of UEs, i.e., one or more UEs, and _{may be positioned in the overlapping area part. The use case scenario resembles that of dual connectivity (DC), where UEs in S in the overlapping area are served by two base stations, e.g., gNB1 and gNB2. DC in 5G radio access networks is a} feature that allows a UE of a slice to be simultaneously connected to two base stations: a Primary Serving Cell (PSC), e.g., gNB1, and a Secondary Serving Cell _{(SSC), e.g., gNB2. Being connected to both the PMC and the SSC implies that the} P110768 UE is situated in their overlapping coverage area. This setup enhances data throughput and reliability by leveraging the capacities of both cells. DC coordination typically involves the following 6 steps: 1_{. Initial Connection Setup where the UE establishes a connection with the} PMC. 2_{. Secondary Cell Selection is determined by PMC which identifies the need} for dual connectivity based on factors like signal quality, load balancing, or t_{hroughput requirements. In this case, the PMC selects an appropriate SSC} for the UE, often based on proximity, capacity, or frequency band compatibility. 3_{. The setup of SSC follows the selection process. The PMC communicates} with the SSC configuration details and security parameters for the UE. This communication is conveyed via the 3GPP X2/Xn or S1 interfaces. 4_{. After the SSC setup, the two base stations can coordinate the data flow of the UE. For example, in the case of downlink data, both the PMC and SSC} can simultaneously transmit downlink data to the UE. The split of data can be dynamic, based on real-time conditions. Coordination about the split of data utilizes the 3GPP X2/Xn or S1 interfaces. 5_{. Handover and control messages between the UE and PMC continue through the primary connection. The PMC remains in control of the primary} connection and can make decisions about handovers or adjusting the dual connectivity setup. 6_{. If the secondary cell is no longer needed or optimal, the PMC can release} the SSC connection. The UE then returns to being served solely by the P_{MC or another SSC can be selected.} In the above description, embodiments of this invention can be used for _{coordination of the data flow of the UE between PMC and SSC. To this end, assuming distributed RAN resource recommendation and that the one or more entities coincides with PMC, the processes A2 and A3 can be performed by PMC,} i.e., gNB1, and signals S3 and S4 can be sent to SSC, i.e., gNB2. P110768 _{[00085] O-RAN implementation. In one embodiment, the start node (apparatus 600) can be implemented in a Near-Real Time RAN Intelligent Controller (RIC)} receiving the S0 signal request from the Non-Real Time RIC, via the O-RAN A1 interface, and sending the S1 and S3 signals, via the O-RAN E2 interface to _{Centralized Unit – Control Plane (CU-CP) nodes, i.e., gNBs. [00086] Technical specification impact. DC in 5G networks involves complex coordination between the PMC and SSC, facilitated by 3GPP-defined interfaces like X2/Xn and S1. This setup allows for more efficient use of network resources} and provides a better user experience in terms of data rates and connectivity _{reliability. The X2/Xn Interface connects two base stations and is used for coordination and data transfer between the PMC and SSC. The S1 Interface connects the base station to the Evolved Packet Core (EPC) in LTE or to the 5G} Core network. It is used for control and mobility management, as well as user data _{forwarding. The above interfaces will be used to convey the signals S1, S3, and} S4 described above. _{[00087] Fig. 8, in conjunction with fig. 1, describes one or more network entities 600 configured to operate in or with a communication network 100, and configured} for estimating network capacity for serving wireless devices in a service area 150 _{of the communication network 100. The communication network 100 comprises at} least one network node 130, 135 for providing wireless communication in the _{service area 150. The communication network 100 has a total amount of} communication resources for providing wireless communication in the service area _{150 via the at least one network node 130, 135. The one or more network entities 600 comprises processing circuitry 603 and a memory 604. Said memory contains} instructions executable by said processing circuitry, whereby the one or more _{network entities 600 is operative for obtaining, for a set of wireless devices 140,} 145 served by the at least one network node 130, 135, a requested value of each _{of one or more service-related measures according to an SLA and obtaining, for} the set of wireless devices 140, 145, a delivered value of each of the one or more service-related measures. The one or more network entities is further operative for determining, for the set of wireless devices 140, 145, an SLA distance that defines P110768 a distance between the requested value and the delivered value for the one or more service-related measures, based on the requested value and the delivered value for the one or more service-related measures and for determining a communication resource margin for the set of wireless devices 140, 145 based on the SLA distance and a value related to a subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements, the communication resource margin being an estimated amount of communication resources needed to change the one or more service-related measures from the respective delivered value to the respective requested value. The one or more network entities is further operative _{for determining, for the set of wireless devices 140, 145, an SLA assurance state} based on the determined communication resource margin and on the total amount of communication resources, wherein the SLA assurance state defines whether or to what extent the determined communication resource margin can be fulfilled. _{[00088] The one or more network entities may be, or be situated in, a node of the communication network 100, such as in any of the at least one network node 130, 135. Alternatively, the one or more network entities is situated outside of the communication network 100, but connected to the communication network 100. Still alternatively, the functionality of the one or more network entities is spread out} over a group of network nodes. The group of network nodes may be different physical, or virtual, nodes inside or outside of the communication network 100. This alternative realization may be called a cloud-solution. _{[00089] According to an embodiment, the one or more network entities 600 is} further operative for determining, for the set of wireless devices, an SLA resource coefficient that is an estimation of amount of the communication resources required per delivered value for the one or more service-related measures, the SLA resource coefficient being based on the subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements. Further, the determining of the communication resource margin for the set of wireless devices 140, 145 is based on the SLA resource coefficient and the SLA distance. P110768 _{[00090] According to another embodiment, the SLA distance for the set of} wireless devices is determined as a distance between an x-dimensional vector of the requested value of the one or more service-related measures and an x- dimensional vector of the delivered value of the one or more service-related measures, wherein x is the number of different service-related measures and wherein x is at least one. _{[00091] According to another embodiment, the one or more network entities is further operative for transmitting information on the determined SLA assurance state for the set of wireless devices to the at least one network node 130, 135. [00092] According to another embodiment, the one or more network entities is} operative for the determining of the communication resource margin 208 by further determining the communication resource margin based on amount of vacant network resources or amount of utilized network resources of the total amount of _{network resources at a certain time point. [00093] According to another embodiment, there is a plurality of sets of wireless} devices within the service area, the plurality of sets including the set of wireless devices, and the one or more network entities 600 is further operative as defined in any of the above embodiments for each of the plurality of sets of wireless devices. _{[00094] According to another embodiment, the one or more network entities is operative for summing up the communication resource margin determined for} each of the plurality of sets of wireless devices into a total communication resource margin for the plurality of sets of wireless devices, and for the _{determining of the SLA assurance state for the plurality of sets of wireless devices} 140, 145 based on the determined total communication resource margin and on the total amount of communication resources. _{[00095] According to yet another embodiment, the one or more network entities is} further operative for determining, based on the SLA assurance state for the plurality of sets of wireless devices, whether an additional set of wireless devices P110768 can be added to the service area in addition to the plurality of sets of wireless devices. _{[00096] According to yet another embodiment, the communication network 100} has a plurality of network slices configured, each network slice being allocated a _{share of the total amount of network resources within the service area. Further, the} one or more network entities is operative as defined in any of the above _{embodiments for each such network slice, and the one or more network entities is} operative for the determining of the SLA assurance state based on the share of the total amount of communication resources that the certain network slice is allocated. _{[00097] According to yet another embodiment, the one or more network entities} 600 is further operative for determining, based on the SLA assurance state for the set of wireless devices, whether an additional network slice can be configured in the network in addition to the plurality of network slices. _{[00098] According to other embodiments, the one or more network entities 600} may further comprise a communication unit 602, which may be considered to comprise conventional means for communication with network nodes of the communication network 100. The instructions executable by said processing _{circuitry 603 may be arranged as a computer program 605 stored e.g. in said memory 604. The processing circuitry 603 and the memory 604 may be arranged} in a sub-arrangement 601. The sub-arrangement 601 may be a micro-processor and adequate software and storage therefore, a Programmable Logic Device, PLD, or other electronic component(s)/processing circuit(s) configured to perform _{the methods mentioned above. The processing circuitry 603 may comprise one or} more programmable processor, application-specific integrated circuits, field _{programmable gate arrays or combinations of these adapted to execute} instructions. _{[00099] The computer program 605 may be arranged such that when its} instructions are run in the processing circuitry 603, the instructions cause the one _{or more network entities 600 to perform the steps described in any of the} P110768 _{described embodiments of the network node 130 and its method. The computer} program 605 may be carried by a computer program product connectable to the processing circuitry 603. The computer program product may be the memory 604, or at least arranged in the memory. The computer program product may be called a computer-readable storage medium. The memory 604 may be realized as for _{example a Random-access memory (RAM), Read-Only Memory (ROM) or an Electrical Erasable Programmable ROM (EEPROM). In some embodiments, a carrier may contain the computer program 605. The carrier may be one of an} electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, _{an electric signal, a radio signal, a microwave signal, or computer readable storage medium. The computer-readable storage medium may be e.g., a CD, DVD or flash memory, from which the program could be downloaded into the memory} 604. Alternatively, the computer program 605 may be stored on a server or any other entity to which the one or more network entities 600 has access via the communication unit 602. The computer program 605 may then be downloaded from the server into the memory 604. _{[000100] Although the description above contains a plurality of specificities, these} should not be construed as limiting the scope of the concept described herein but as merely providing illustrations of some exemplifying embodiments of the described concept. It will be appreciated that the scope of the presently described concept fully encompasses other embodiments which may become obvious to those skilled in the art, and that the scope of the presently described concept is accordingly not to be limited. Reference to an element in the singular is not intended to mean "one and only one" unless explicitly so stated, but rather "one or more." All structural and functional equivalents to the elements of the above- described embodiments that are known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed _{hereby. Moreover, it is not necessary for an apparatus or method to address each} and every problem sought to be solved by the presently described concept, for it to _{be encompassed hereby. In the exemplary figures, a broken line generally} signifies that the feature within the broken line is optional. P110768

Claims

CLAIMS 1. A method performed by one or more network entities for estimating _{network capacity for serving wireless devices in a service area (150) of a communication network (100), the communication network (100) comprising at least one network node (130, 135) for providing wireless communication in the service area (150), wherein the communication network (100) has a total amount of communication resources for providing wireless communication in the service area (150) via the at least one network node (130, 135), the method comprising: Obtaining (202), for a set of wireless devices (140, 145) served by the at least one network node (130, 135), a requested value of each of one or more service-related measures according to a Service Level Agreement, SLA; Obtaining (204), for the set of wireless devices (140, 145), a delivered value of each of the one or more service-related measures, Determining (206), for the set of wireless devices (140, 145), an SLA distance that defines a distance between the requested value and the delivered value for the one or more service-related measures, based on the requested value and the delivered value for the one or more service-related measures; Determining (208) a communication resource margin for the set of wireless devices (140, 145) based on the SLA distance and a value related to a} subset of the total amount of communication resources that are used for providing _{the delivered value for the one or more service-related measurements, the} communication resource margin being an estimated amount of communication _{resources needed to change the one or more service-related measures from the respective delivered value to the respective requested value, and Determining (210), for the set of wireless devices (140, 145), an SLA assurance state based on the determined communication resource margin and on} the total amount of communication resources, wherein the SLA assurance state _{defines whether or to what extent the determined communication resource margin} can be fulfilled. 2. Method according to claim 1, further comprising: P110768 _{Determining (207), for the set of wireless devices, an SLA resource coefficient that is an estimation of amount of the communication resources required per delivered value for the one or more service-related measures, the SLA resource coefficient being based on the subset of the total amount of} communication resources that are used for providing the delivered value for the one or more service-related measurements, and wherein the determining (208) of the communication resource margin for the set of wireless devices (140, 145) is based on the SLA resource coefficient and the SLA distance. _{3. Method according to claim 1 or 2, wherein the SLA distance for the set} of wireless devices is determined (206) as a distance between an x-dimensional vector of the requested value of the one or more service-related measures and an x-dimensional vector of the delivered value of the one or more service-related measures, wherein x is the number of different service-related measures and wherein x is at least one. 4. Method according to any of the preceding claims, further comprising: transmitting (212) information on the determined SLA assurance state _{for the set of wireless devices to the at least one network node (130, 135).} 5. Method according to any of the preceding claims, wherein the _{communication resource margin is further determined (208) based on amount of} vacant network resources or amount of utilized network resources of the total amount of network resources at a certain time point. 6. Method according to any of the preceding claims, wherein there is a plurality of sets of wireless devices within the service area, the plurality of sets including the set of wireless devices, and the method comprises performing the method of any of the preceding claims for each of the plurality of sets of wireless devices. _{7. Method according to claim 6, wherein the communication resource} margin determined (208) for each of the plurality of sets of wireless devices are P110768 summed up into a total communication resource margin for the plurality of sets of wireless devices, and wherein the SLA assurance state is determined (210) for the _{plurality of sets of wireless devices (140, 145) based on the determined total} communication resource margin and on the total amount of communication resources. _{8. Method according to claim 6 or 7, further comprising:} determining (214), based on the SLA assurance state for the plurality of sets of wireless devices, whether an additional set of wireless devices can be added to the service area in addition to the plurality of sets of wireless devices. 9. Method according to any of the preceding claims, wherein the communication network (100) has a plurality of network slices configured, each network slice being allocated a share of the total amount of network resources _{within the service area, and wherein the method is performed per such network} slice, and the determining (210) of the SLA assurance state is based on the share of the total amount of communication resources that the certain network slice is allocated. 10. Method according to claim 9, further comprising: d_{etermining (213), based on the SLA assurance state for the set of} wireless devices, whether an additional network slice can be configured in the network in addition to the plurality of network slices. _{11. One or more network entities (600) configured to operate in or with a communication network (100), and configured for estimating network capacity for} serving wireless devices in a service area (150) of the communication network (100), the communication network (100) comprising a at least one network node (130, 135) for providing wireless communication in the service area (150), wherein the communication network (100) has a total amount of communication resources for providing wireless communication in the service area (150) via the at least one _{network node (130, 135), the one or more network entities (600) comprising processing circuitry (603) and a memory (604), said memory containing} P110768 instructions executable by said processing circuitry, whereby the one or more _{network entities (600) is operative for:} Obtaining, for a set of wireless devices (140, 145) served by the at least one network node (130, 135), a requested value of each of one or more service- related measures according to a Service Level Agreement, SLA; Obtaining, for the set of wireless devices (140, 145), a delivered value of each of the one or more service-related measures, Determining, for the set of wireless devices (140, 145), an SLA distance that defines a distance between the requested value and the delivered value for the one or more service-related measures, based on the requested value and the _{delivered value for the one or more service-related measures;} Determining a communication resource margin for the set of wireless devices (140, 145) based on the SLA distance and a value related to a subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements, the communication resource margin being an estimated amount of communication resources needed to change the one or more service-related measures from the _{respective delivered value to the respective requested value, and Determining, for the set of wireless devices (140, 145), an SLA} assurance state based on the determined communication resource margin and on the total amount of communication resources, wherein the SLA assurance state defines whether or to what extent the determined communication resource margin can be fulfilled. 12. One or more network entities (600) according to claim 11, further being operative for: Determining, for the set of wireless devices, an SLA resource coefficient that is an estimation of amount of the communication resources required per delivered value for the one or more service-related measures, the SLA resource coefficient being based on the subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements, P110768 and wherein the determining of the communication resource margin for the set of wireless devices (140, 145) is based on the SLA resource coefficient and the SLA distance. 13. One or more network entities (600) according to claim 11 or 12, wherein the SLA distance for the set of wireless devices is determined as a distance between an x-dimensional vector of the requested value of the one or more service-related measures and an x-dimensional vector of the delivered value of the _{one or more service-related measures, wherein x is the number of different} service-related measures and wherein x is at least one. _{14. One or more network entities (600) according to any of claims 11-13,} further being operative for: transmitting information on the determined SLA assurance state for _{the set of wireless devices to the at least one network node (130, 135).} 15. One or more network entities (600) according to any of claims 11-14, _{operative for the determining of the communication resource margin (208) by} further determining the communication resource margin based on amount of vacant network resources or amount of utilized network resources of the total amount of network resources at a certain time point. 16. One or more network entities (600) according to any of claims 11-15, wherein there is a plurality of sets of wireless devices within the service area, the plurality of sets including the set of wireless devices, and the one or more network _{entities (600) is further operative as defined in any of claims 11-15 for each of the} plurality of sets of wireless devices. 17. One or more network entities (600) according to claim 16, operative for summing up the communication resource margin determined for each of the plurality of sets of wireless devices into a total communication resource margin for the plurality of sets of wireless devices, and for the determining of the SLA _{assurance state for the plurality of sets of wireless devices (140, 145) based on} P110768 the determined total communication resource margin and on the total amount of communication resources. _{18. One or more network entities (600) according to claim 16 or 17, further} being operative for: determining, based on the SLA assurance state for the plurality of sets of wireless devices, whether an additional set of wireless devices can be added to the service area in addition to the plurality of sets of wireless devices. _{19. One or more network entities (600) according to any of claims 11-18,} wherein the communication network (100) has a plurality of network slices configured, each network slice being allocated a share of the total amount of _{network resources within the service area, and wherein the one or more network} entities is further operative as defined in any of claims 11-18 for each such network slice, and the one or more network entities is operative for the determining of the SLA assurance state based on the share of the total amount of communication resources that the certain network slice is allocated. 20. One or more network entities (600) according to claim 19, further being operative for: determining, based on the SLA assurance state for the set of wireless devices, whether an additional network slice can be configured in the network in addition to the plurality of network slices. _{21. A computer program (605) comprising instructions, which, when executed by at least one processing circuitry of one or more network entities (600) configure to operate in or with a communication network (100), the communication network (100) comprising a at least one network node (130, 135) for providing} wireless communication in the service area (150), wherein the communication network (100) has a total amount of communication resources for providing wireless communication in the service area (150) via the at least one network _{node (130, 135), causes the one or more network entities (600) to perform the} following steps: P110768 Obtaining, for a set of wireless devices (140, 145) served by the at least one network node (130, 135), a requested value of each of one or more service- related measures according to a Service Level Agreement, SLA; Obtaining, for the set of wireless devices (140, 145), a delivered value of each of the one or more service-related measures, Determining, for the set of wireless devices (140, 145), an SLA distance that defines a distance between the requested value and the delivered value for the one or more service-related measures, based on the requested value and the _{delivered value for the one or more service-related measures;} Determining a communication resource margin for the set of wireless devices (140, 145) based on the SLA distance and a value related to a subset of the total amount of communication resources that are used for providing the delivered value for the one or more service-related measurements, the communication resource margin being an estimated amount of communication resources needed to change the one or more service-related measures from the respective delivered value to the respective requested value, and D_{etermining, for the set of wireless devices (140, 145), an SLA} assurance state based on the determined communication resource margin and on the total amount of communication resources, wherein the SLA assurance state defines whether or to what extent the determined communication resource margin can be fulfilled. _{22. A carrier containing the computer program (605) according to claim 21,} wherein the carrier is one of an electronic signal, an optical signal, a radio signal, _{an electric signal or a computer readable storage medium (606).} P110768