Multi-user downlink scheduling method and computer equipment

Abstract

The invention relates to the technical field of wireless communication, and discloses a multi-user downlink scheduling method and computer equipment. Comprising the following steps: acquiring a large-scale channel coefficient from each user equipment to each far-end radio frequency unit in the distributed base station; determining a multi-user signal to interference and noise ratio of the user equipment on the allocated sub-band by using the large-scale channel coefficient and interference and noise of the user equipment on the corresponding sub-band; determining a target modulation coding strategy of the user equipment by using the multi-user signal to interference plus noise ratio so as to execute downlink transmission operation; wherein the target modulation coding strategy is used for describing a transmission parameter of the user equipment on the allocated sub-band. Therefore, the key channel characteristics are reserved while the calculation complexity is reduced, the MU-SINR is calculated in combination with sub-band level interference and noise, the actual channel quality in a multi-user coexistence scene can be accurately reflected, channel utilization and interference control are optimized, and the communication performance and resource efficiency of a cellular-free large-scale multiple-input-multiple-output communication system are greatly improved.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a multi-user downlink scheduling method and computer device. Background Technology

[0002] In modern mobile communications, resource scheduling determines the resource allocation and transmission parameters of user equipment, which depends on channel conditions and data flow status, and is crucial to system performance.

[0003] As networks evolve to Cell-Free Massive Multiple-Input Multiple-Output (CF-mMIMO) architecture, traditional baseband functions are further broken down into multi-level distributed units. In this multi-level architecture, the coordination between the channel characteristics of massive MIMO and transmission scheduling strategies becomes crucial. However, existing scheduling methods have limitations, necessitating a scheduling method that can effectively reduce computational complexity. Summary of the Invention

[0004] This application aims to at least partially solve one of the technical problems in related technologies. To this end, this application proposes a multi-user downlink scheduling method and a computer device. The main technical solutions adopted in this application include: In a first aspect, embodiments of this application provide a multi-user downlink scheduling method applied to a cellular-free massive MIMO communication system, the system including a distributed base station and user equipment; the method includes: acquiring large-scale channel coefficients from each user equipment to each remote radio frequency unit in the distributed base station; determining the multi-user signal-to-interference-plus-noise ratio (SINNR) of the user equipment in the allocated sub-band using the large-scale channel coefficients and the interference plus noise of the user equipment in the corresponding sub-band; determining the target modulation and coding strategy of the user equipment using the multi-user SINNR to perform downlink transmission operations; wherein, the target modulation and coding strategy is used to describe the transmission parameters of the user equipment in the allocated sub-band.

[0005] Secondly, embodiments of this application provide a multi-user downlink scheduling apparatus applied to a cellular-free massive MIMO communication system, the system including a distributed base station and user equipment; the apparatus includes: a coefficient acquisition module, used to acquire large-scale channel coefficients from each user equipment to each remote radio frequency unit in the distributed base station; a signal-to-interference-plus-noise ratio (SINR) determination module, used to determine the multi-user SINR of the user equipment in the allocated subband using the large-scale channel coefficients and the interference plus noise of the user equipment in the corresponding subband; and a downlink transmission module, used to determine the target modulation and coding strategy of the user equipment using the multi-user SINR to perform downlink transmission operations; wherein, the target modulation and coding strategy is used to describe the transmission parameters of the user equipment in the allocated subband.

[0006] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0007] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described above.

[0008] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the above methods.

[0009] In the above embodiments, by acquiring the large-scale channel coefficients from the user equipment to the remote radio unit, key channel characteristics are preserved while reducing computational complexity. Combining sub-band interference plus noise calculation to obtain MU-SINR accurately reflects the actual channel quality in multi-user coexistence scenarios, providing a reliable basis for scheduling decisions. Finally, based on MU-SINR, the appropriate MCS is determined and downlink transmission is executed, maximizing transmission efficiency while ensuring transmission reliability. This approach fully adapts to the distributed architecture characteristics of cellular-free massive MIMO systems, effectively improving system communication performance and frequency domain resource utilization. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0011] Figure 1a This is a schematic diagram of a basic architecture of a non-cellular wireless access network according to an embodiment of this application; Figure 1b This is a flowchart of a multi-user downlink scheduling method according to an embodiment of this application; Figure 1c This is a schematic diagram of a channel information processing module according to an embodiment of this application; Figure 1d This is a schematic diagram of interactive large-scale channel coefficient information provided according to an embodiment of this application; Figure 1e This is a schematic diagram of a modulation and coding strategy determination module according to an embodiment of this application; Figure 2 This is a flowchart of a multi-user device pairing method according to an embodiment of this application; Figure 3This is a structural block diagram of a multi-user downlink scheduling device according to an embodiment of this application; Figure 4 This is an internal structural diagram of a computer device provided according to an embodiment of this application. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] In mobile communication systems, resource scheduling is crucial. The scheduler is responsible for deciding when and to which User Equipment (UE) time, frequency, and spatial resources to allocate, and for determining which transmission parameters, such as data rate, to use. The information required by the scheduler depends on the specific scheduling policy, but most schedulers require at least the following: 1) the UE's channel conditions, including frequency and spatial domain attributes; 2) the buffer status and priorities of different data streams, including the amount of data to be retransmitted. In New Radio (NR) systems, separating the traditional Baseband Unit (BBU) into a Centralized Unit (CU) and a Distributed Unit (DU) is a major innovation in network architecture. This separation is designed to meet the high-performance requirements of 5G (such as extremely low latency, ultra-high bandwidth, and flexible services), while achieving more efficient networking and operation through functional reconfiguration and virtualization. In a typical split (Option 2), the Core Unit (CU) handles the higher-level protocol stack, such as the Packet Data Convergence Protocol (PDCP) layer and the Radio Resource Control (RRC) layer, to provide non-real-time functions, such as core network connectivity, Quality of Service (QoS) policies, and radio bearer management. The Utility Unit (DU) handles the lower-level protocol stack, such as the Radio Link Control (RLC), Medium Access Control (MAC), and Physical Layer (PHY). This includes resource scheduling that requires real-time processing, such as time-frequency resource allocation and Hybrid Automatic Repeat Request (HARQ). In Cell-Free Massive Multiple-Input Multiple-Output (CF-mMIMO) systems, the DU's function is further decomposed, forming User-Centric Distributed Units (UCDUs) and Edge Distributed Units (EDUs). EDU is responsible for the Lower Physical Layer (Low-PHY) functions. UCDU is responsible for the Higher Physical Layer (High-PHY) and some lower-layer protocol stack functions, including the allocation of time and frequency resources with high real-time requirements.These DU units connect to one or more Remote Radio Units (RRUs) via standardized fronthaul interfaces, such as the Common Public Radio Interface (eCPRI), the Open RAN Alliance Interface, or open interfaces defined by O-RAN. In actual deployments, multiple RRUs work collaboratively in a distributed manner to jointly complete the transmission and reception of UE signals. Through the hierarchical functional decomposition of UCDU-EDU and the distributed cooperation of RRUs, these network elements ultimately constitute the basic architecture of the Cell-Free Radio Access Network (CF-RAN), as shown below. Figure 1a As shown, a user-centric distributed unit is associated with an edge distributed unit that connects to L remote radio units. Each remote radio unit is equipped with M antennas, collectively providing services to K user equipment. However, in the classic CU-DU separation architecture (Option 2), the DU monopolizes dynamic resource scheduling functions with extremely high real-time requirements, such as time-slot-level / symbol-level time-frequency domain resource allocation and HARQ retransmission decisions. To achieve high real-time decision-making, the PHY layer synchronizes instantaneous Channel State Information (CSI) to the DU's kernel scheduling module through a fast hardware interface, such as shared memory or a DMA ring buffer. Through the direct access mechanism of memory-mapped I / O, the MAC layer can avoid protocol stack interaction overhead. However, under the CF-mMIMO architecture, UCDU faces new technical challenges in completing dynamic resource scheduling: 1) The real-time CSI carried by EDU needs to interact across nodes through the eCPRI standardized fronthaul interface, and transmitting the complete frequency domain and spatial domain CSI will significantly increase the fronthaul overhead; 2) The computational complexity of using the complete full-dimensional CSI for dynamic resource scheduling grows superlinearly, making it difficult to meet real-time requirements.

[0014] Based on this, according to the embodiments of this application, a multi-user downlink scheduling method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0015] This embodiment provides a multi-user downlink scheduling method, applied to a non-cellular massive MIMO communication system, which includes distributed base stations and user equipment; Figure 1b This is a flowchart of a multi-user downlink scheduling method according to an embodiment of this application, such as... Figure 1b As shown, the process includes the following steps: S110. Obtain the large-scale channel coefficients from each user equipment to each remote radio unit in the distributed base station.

[0016] Among them, the large-scale channel coefficient is a low-dimensional channel parameter obtained by averaging the full-dimensional channel coefficients in spatial and frequency dimensions. It is used to describe the channel characteristics of slow fading between the user equipment (UE) and the remote radio unit (RRU).

[0017] Specifically, the large-scale channel coefficients from each user equipment to each remote radio unit in the distributed base station can be obtained as follows: First, obtain the full-dimensional channel coefficients from each user equipment to each antenna on each remote radio unit. Then, simplify the full-dimensional channel coefficients to obtain the large-scale channel coefficients.

[0018] In this context, the full-dimensional channel coefficient refers to a multi-dimensional parameter describing the wireless signal transmission characteristics between user equipment and remote radio frequency units in a cellular-free massive MIMO system. For example, the full-dimensional channel coefficient can be written as g. l,k,s,n,m Where 'l' represents the index of the Remote Radio Unit (RRU), used to distinguish different RRUs; 'k' represents the index of the User Equipment (UE), used to distinguish different UEs; 's' represents the subband index, used to distinguish different subbands in the system; 'n' represents the subcarrier index; and 'm' represents the antenna index. It should be noted that the basic scheduling unit of frequency resources is the subband, while a subcarrier is a subdivided frequency unit within a subband; that is, each subband contains multiple subcarriers.

[0019] Alternatively, the full-dimensional channel coefficients can be determined using the following methods: First, the original radio frequency signal of each user equipment is processed by analog-to-digital conversion and time-frequency domain conversion to obtain the digital baseband signal of each user equipment.

[0020] Each user equipment's digital baseband signal contains subcarrier dimension information. It should be noted that this subcarrier dimension information indicates the subcarrier index, subcarrier frequency position, and subcarrier resource block affiliation of the digital baseband signal.

[0021] Specifically, each user equipment (UE) transmits sounding reference signals (SRS) to the base station via multiple remote radio units (RRUs) covering it, according to the system's configured period and power. These SRS are known pilot sequences used to estimate the channel response, containing transmission information for the corresponding UE across all active subbands. The base station-side RRUs, acting as the radio frequency front-end directly communicating with the UEs, are responsible for receiving the SRS and performing basic physical layer processing. Specifically, each RRU integrates all SRS radio frequency signals received from all UEs on each of its antennas, filters and amplifies them to convert them into baseband signals. Analog-to-digital conversion is then performed to convert the analog signals into digital signals. Next, cyclic prefix removal is performed to eliminate multipath interference. Finally, a fast Fourier transform is used to complete the time-frequency domain conversion, extracting the signal components of each subcarrier within the current subband for each UE, thus obtaining the digital baseband signal for each UE.

[0022] Secondly, the antenna domain channel matrix of each user equipment is calculated on each remote radio unit.

[0023] The antenna domain channel matrix is ​​a two-dimensional matrix that describes the channel transmission characteristics between different antennas and different subcarriers between the User Equipment (UE) and the Remote Radio Unit (RRU). The antenna domain channel matrix also contains subcarrier dimension information, which is used to indicate the subcarrier index to which it belongs.

[0024] It should be noted that after determining the digital baseband signal of each user equipment (UE), each remote radio unit (RRU) transmits it to the edge distributed unit (EDU). At this point, these digital baseband signals carry a clear RRU index. The EDU receives subband configuration information from the user-centric distributed unit (UCDU), or determines the subcarrier number corresponding to the digital baseband signal based on its pre-configured local configuration information. Subsequently, based on the protocol, the UE corresponding to the subcarrier number can be determined using the subcarrier number. Then, based on the pre-stored reference signals of the UEs, the channel coefficients from all antennas to each UE are calculated on each RRU, forming an antenna domain channel matrix.

[0025] For example, consider one user equipment and two remote radio units (RRUs), each with two antennas. First, UE1 transmits SRS on all subcarriers of the current subband. This signal is simultaneously received by antennas 1 and 2 of RRU1 and antennas 1 and 2 of RRU2.

[0026] The received signal is then processed by analog-to-digital conversion and time-frequency domain conversion to extract the digital baseband signal of UE1 on subcarrier 1 and distinguish it by antenna: the signal labeled RRU1-subcarrier 1-antenna 1 and the signal labeled RRU1-subcarrier 1-antenna 2; similarly, the signal transmitted after processing by RRU2 is labeled RRU2-subcarrier 1-antenna 1 and RRU2-subcarrier 1-antenna 2.

[0027] Next, the EDU calculates the channel coefficients for subcarrier 1 based on all received signals using a channel estimation algorithm. Specifically, for RRU1, using the known SRS sequence of UE1 on subcarrier 1, channel estimation is performed on the signals of RRU1-subcarrier 1-antenna 1 and RRU1-subcarrier 1-antenna 2 respectively, obtaining their channel coefficients. These are then integrated to form the row vector of RRU1 for UE1 on subcarrier 1. This row vector is essentially the set of channel coefficients from all antennas of the first RRU to the first UE on subcarrier 1. Similarly, for RRU2, the row vector of RRU2 for UE1 on subcarrier 1 is calculated. This row vector is essentially the set of channel coefficients from all antennas of the second RRU to the first UE on subcarrier 1.

[0028] Furthermore, the EDU repeats the above process for all subcarriers within the current subband (e.g., subcarrier 1 to subcarrier N), obtaining the row vector corresponding to each subcarrier n. Then, it arranges the row vectors of the same RRU on all subcarriers in ascending order of subcarrier number (column direction corresponds to subcarrier), thus combining them to form the antenna domain channel matrix g of the l-th RRU to the k-th UE on each subcarrier. l,k ∈C M×1 Where l is the number of the remote radio unit, k is the number of the user equipment; M is the total number of antennas on the remote radio unit, and N is the number of subcarriers in the subband. It should be noted that M×N is the dimension of this matrix, that is, the total number of antennas × the total number of subcarriers.

[0029] Finally, subband correlation and dimension mapping are performed based on the antenna domain channel matrix of each user equipment to obtain the full-dimensional channel coefficients.

[0030] It should be noted beforehand that the mapping relationship between subbands and subcarriers can be preset by the system. Specifically, N subcarriers can be pre-divided into S subbands, where each subband s contains x consecutive subcarriers. Then, subband association processing is performed based on the antenna domain channel matrix of each user equipment. Specifically, for each subcarrier in the antenna domain channel matrix, its subband is determined according to the preset subband and subcarrier mapping table. For example, subcarriers n=10~21 all belong to subband s=1. Subsequently, RRU index and UE index are introduced to reconstruct the channel coefficients according to the five-dimensional structure of remote radio unit, user equipment, subband, subcarrier, and antenna, finally obtaining the full-dimensional channel coefficients from each user equipment on the current subband to each antenna on each remote radio unit. For example, the full-dimensional channel coefficients can be in the form of g. l,k,s,n,m Where k is the user equipment number; l is the remote radio unit number; m is the antenna number on the remote radio unit; s is the current subband number; and n is the subcarrier number on the current subband.

[0031] Thus, the RF-to-baseband conversion and preliminary processing are completed on the RRU side, and high-precision channel estimation and five-dimensional structured mapping are completed on the EDU side. This significantly reduces the amount of fronthaul data while quickly and accurately obtaining the full-dimensional channel coefficients from each UE to each RRU, each antenna, and each subcarrier, laying a real-time and complete information foundation for subsequent scheduling.

[0032] Furthermore, after determining the full-dimensional channel coefficients, the full-dimensional channel coefficients can be simplified to obtain large-scale channel coefficients.

[0033] The simplification process includes modulo-square operation and average operation.

[0034] Specifically, the channel coefficients across all dimensions need to be averaged along the antenna dimension to eliminate small-scale differences between different antennas within the same remote radio unit. This can be achieved by calculating the average channel coefficients of all antennas m for a fixed remote radio unit l, user equipment k, subband s, and subcarrier n. Then, the channel coefficients are averaged along the subcarrier dimension across different subcarriers n within the same subband s to eliminate fast fading between subcarriers within the same subband.

[0035] Optionally, the edge distributed unit may include a channel information processing module, please refer to the appendix. Figure 1c It is used to perform modulo-square and averaging operations on the full-dimensional channel coefficients. For example, the large-scale channel coefficients from each remote radio unit to each UE in each subband can be determined in the following manner: Alternatively, large-scale channel coefficients can also be determined in the following ways: Where, β l,k,s Large-scale channel coefficients for each remote radio unit; k is the user equipment number; l is the remote radio unit number; m is the antenna number on the remote radio unit; s is the current subband number; n is the subcarrier number on the current subband; g l,k,s,n,m G represents the full-dimensional channel coefficients from each user equipment to each antenna on each remote radio unit in the current subband; N is the total number of subcarriers participating in the calculation of large-scale information within the current subband; M is the total number of antennas on the remote radio unit. N can represent the total number of all subcarriers in the subband, where g... l,k,s,n,m The channel estimation result at the subcarrier where the reference signal is located in the subband is interpolated to all subcarriers in the subband. Optionally, N can represent the number of subcarriers in the subband. In this case, the subcarriers participating in the calculation of the large-scale channel coefficients can be all subcarriers where the reference signal is located in the subband, or some subcarriers where the reference signal is located in the subband.

[0036] As can be seen from the above formula, the simplification process of large-scale channel coefficients essentially involves averaging the channel coefficients on all or part of the subcarriers and antennas within the subband, or averaging and then averaging. This achieves spatial averaging between antennas, filtering out small-scale differences between antennas within the same RRU while preserving the overall attenuation characteristics of the RRU for the UE. Simultaneously, it achieves frequency averaging between subcarriers, filtering out fast fading within the subband while preserving the long-term attenuation characteristics at the subband level. Thus, fast fading in both the spatial and frequency domains is filtered out, requiring only one scalar to represent the long-term channel energy of the entire subband, significantly reducing the fronthaul load.

[0037] Furthermore, after calculating the large-scale channel coefficients, the EDU can interact with the User-Centered Distributed Unit (UCDU) via the fronthaul interface to obtain the sub-band level large-scale channel coefficients of the User Equipment (UE). For example, please refer to... Figure 1d A field indicating the UE's subband-level large-scale channel coefficients can be added to the eCPRI interface, as shown below: { UE id: RRU id: Subband ID: Quantized large-scale channel coefficients Subband ID: Quantized large-scale channel coefficients … RRU id: Subband ID: Quantized large-scale channel coefficients Subband ID: Quantized large-scale channel coefficients … … UE id: RRU id: Subband ID: Quantized large-scale channel coefficients Subband ID: Quantized large-scale channel coefficients … RRU id: Subband ID: Quantized large-scale channel coefficients Subband ID: Quantized large-scale channel coefficients … … … } This enables edge distributed units to send large-scale channel coefficient information to user-centric distributed units.

[0038] S120. The multi-user signal-to-interference-plus-noise ratio of the user equipment in the allocated sub-band is determined by using the large-scale channel coefficients and the interference plus noise of the user equipment in the corresponding sub-band.

[0039] Interference-plus-noise (IPN) refers to the sum of background interference power and noise power experienced by a user equipment during communication. It is a benchmark value for measuring the interference environment in which a single user equipment is located, excluding interference generated by multiple user pairings in the same subband.

[0040] It should be noted that the channel environment and interference situation of each sub-band are independent. The interference plus noise needs to be matched with the specific sub-band assigned to the user equipment in order to reflect the actual interference level in that sub-band.

[0041] Specifically, the interference plus noise can be determined as follows: First, the single-user signal-to-interference-plus-noise ratio (SINNR) of the user equipment (UE) in the corresponding sub-band is determined based on the channel quality data of the UE across all sub-bands. Then, the interference plus noise of the UE in the corresponding sub-band is determined using the single-user SINNR.

[0042] Channel quality data can refer to the Channel Quality Indicator (CQI) of each user equipment (UE) on its assigned subband. Essentially, it is a quantification of the UE's single-user signal-to-interference-plus-noise ratio (SU-SINR). SU-SINR is the ratio of the useful signal power to the total power of background interference and noise when a UE occupies a specific subband alone, reflecting the channel quality of the UE when there is no interference from other users in the same subband.

[0043] Specifically, the user equipment first measures and reports its own channel quality indication (CQI) information in each subband. Then, the edge distributed unit (EDU) aggregates this information and sends it to the user-centric distributed unit (UCDU) through the fronthaul interface. This allows the UCDU to calculate the single-user signal-to-interference-plus-noise ratio (SIR) of each user equipment in the corresponding subband based on this information. and interference plus noise Where k represents the user equipment (UE) index, used to distinguish different UEs; s represents the subband index, used to distinguish different subbands in the system.

[0044] For example, there are two ways to calculate the single-user signal-to-interference-plus-noise ratio (SINNR). One method is to directly look up the predefined CQI-SU-SINR mapping table to obtain the SINNR corresponding to the CQI information for that user equipment. Alternatively, referring to the CQI table defined in Table 5.2.2.1 of the 3GPP 38.214 protocol, first find the spectral efficiency (efficiencyx) corresponding to the CQI information for that user equipment, and then calculate the corresponding SINNR using the Shannon formula. The calculation formula can be found as follows: SINR su =2 x -1 In the formula, SINR su The signal-to-interference-plus-noise ratio (SIR) of a user equipment is represented by x; x represents the spectral efficiency of the user equipment corresponding to the CQI information.

[0045] Furthermore, the physical expression for the signal-to-interference-plus-noise ratio (SIR) of a single user is known as follows: SINR su =P·|g| 2 / σ 2 In the formula, SINR su σ represents the single-user signal-to-interference-plus-noise ratio (SINNR) of the user equipment; P represents the transmit power of the Channel State Information Reference Signal (CSI-RS) antenna port, i.e., the useful signal power; g is the channel coefficient from the CSI-RS antenna port of a certain RRU to the UE; σ 2 Add noise to the interference. Therefore, UCDU can be obtained by reverse calculation using this formula: σ 2 =P|g| 2 / SINR su In the formula, σ 2 Add noise to the interference; SINR suThe signal-to-interference-plus-noise ratio (SIRR) of a single user equipment is represented by ; P represents the transmit power of the CSI-RS antenna port, which is the useful signal power; g is the channel coefficient from the CSI-RS antenna port of a certain RRU to the UE.

[0046] In some implementations, the UCDU can also control multiple RRUs to transmit CSI-RS signals simultaneously. In this case, the physical expression for the single-user signal-to-interference-plus-noise ratio is modified as follows: In the formula, g l Let l represent the channel coefficient from the CSI-RS port mapped to the UE (l = 1, 2, ..., L). Therefore, the UCDU can also calculate the interference plus noise using this formula: In the formula, σ 2 Add noise to the interference; SINR su g represents the signal-to-interference-plus-noise ratio (SIR) of a single user equipment. l This represents the channel coefficient from the CSI-RS port mapped to the UE by the l-th RRU.

[0047] In this way, UCDU can quickly and accurately calculate the single-user signal-to-interference-plus-noise ratio and interference plus noise for each user equipment in the corresponding subband based on the CQI information reported by the user equipment, providing key interference environment benchmark values ​​for subsequent multi-user scheduling.

[0048] Furthermore, after determining the interference plus noise, it can be used to further determine the multi-user signal-to-interference-plus-noise ratio of the user equipment on the allocated subband.

[0049] Among them, the multi-user signal-to-interference-plus-noise ratio (MU-SINR) can be defined as the ratio of the useful signal power of the target user to the total power of multi-user interference, background interference and noise when multiple users coexist in the same subband, reflecting its actual channel quality in multi-user scenarios.

[0050] Specifically, for a user equipment (UE) allocated to a target subband, its multi-user signal-to-interference-plus-noise (SINNR) in the allocated subband can be determined by its large-scale channel coefficient and interference-plus-noise power. For example, firstly, the precoding gain of the current subband can be determined using the large-scale channel coefficient of the UE in that subband. This precoding gain can be understood as the useful signal power of the UE, specifically the power of the target signal received by the UE from the server in the currently allocated subband, representing the effective signal strength necessary for normal communication. Then, the determined precoding gain is combined with the interference-plus-noise power of the UE in the allocated subband to quantify the level of interference and noise it experiences. Finally, the SINNR of the UE in the allocated subband can be calculated using the relationship between the precoding gain and the interference-plus-noise power.

[0051] S130. Utilize the multi-user signal-to-interference-plus-noise ratio to determine the target modulation and coding strategy of the user equipment in order to perform downlink transmission operations.

[0052] The target modulation and coding scheme (MCS) can be used to describe the transmission parameters of a user equipment on its allocated subband. Essentially, it's a combination of modulation scheme and coding rate determined based on the target user equipment's equivalent signal-to-interference-plus-noise ratio (SINR), used to balance transmission efficiency and reliability.

[0053] Optionally, the UCDU may also include a modulation and coding strategy determination module, please refer to [reference needed]. Figure 1e The Modulation and Coding Strategy Determination Module (MCS Determination Module) is used to determine the target modulation and coding strategy for the target user equipment (User Equipment) based on the multi-user signal-to-interference-plus-noise ratio (SIR / NDR) of the User Equipment in the allocated subband. Its core function is to select an appropriate modulation order and coding rate based on the current channel quality of the target User Equipment. The modulation order, such as QPSK, 16QAM, or 64QAM, determines the number of bits carried by each symbol. The coding rate determines the data redundancy; a lower coding rate provides stronger anti-interference capability. The MCS Determination Module ensures that downlink data transmission maximizes transmission efficiency while meeting bit error rate requirements.

[0054] It is understood that the transmission parameters of a user equipment on its allocated subband refer to the specific configuration parameters used for actual downlink data transmission, determined based on the target modulation and coding strategy. This can be understood as a refinement and implementation of the target modulation and coding strategy. For example, these may include modulation scheme, coding rate, transport block size (TBS), and spectral efficiency.

[0055] Furthermore, after determining the target modulation and coding strategy of the target user equipment, the downlink transmission operation of the target user equipment can be performed in the following manner. First, the core parameters are parsed based on the target modulation and coding strategy, including, for example, the modulation scheme of 64QAM, the coding rate of 0.78, and the corresponding spectral efficiency of 5.55 bps / Hz. Simultaneously, the transport block size (TBS) for a single transmission is calculated by combining the physical resource blocks (PRBs) allocated to the user equipment in the subband allocation results, such as 10 PRBs. For example, according to Tables 5.1.3.2-1 to 5.1.3.2-4 of the 3GPP TS 38.214 protocol, the TBS value, such as 666 bits, can be obtained through spectral efficiency, the number of PRBs, and the 12 subcarriers contained in each PRB, thus clarifying the amount of data to be transmitted. Subsequently, the UCDU performs channel coding on the data to be transmitted by the target user equipment according to the coding rate of the target modulation and coding strategy, and then maps the encoded data to modulation symbols according to the modulation scheme. Next, the modulation symbols are mapped to the subband and corresponding PRB resources allocated to the target user equipment, ensuring precise binding between data and physical frequency resources. Then, the remote radio unit (RRU) is controlled to transmit the signal to the target user equipment via an antenna. Upon receiving the signal, the user equipment can demodulate and decode it based on the known target modulation and coding scheme parameters to recover the original data. Finally, after completing this scheduling operation, the transmission status of all user equipment is updated. First, the current TBS is subtracted from the remaining data to be transmitted, and then the weighted historical average throughput of all user equipment is updated based on the current transmission rate, providing a reference for the next scheduling operation.

[0056] In the above implementation, by acquiring the large-scale channel coefficients from the user equipment to the remote radio unit, key channel characteristics are preserved while reducing computational complexity. Combining sub-band interference plus noise calculation to obtain MU-SINR accurately reflects the actual channel quality in multi-user coexistence scenarios, providing a reliable basis for scheduling decisions. Finally, based on MU-SINR, the appropriate MCS is determined and downlink transmission is executed, maximizing transmission efficiency while ensuring transmission reliability. This approach fully adapts to the distributed architecture characteristics of cellular-free massive MIMO systems, effectively improving system communication performance and frequency domain resource utilization.

[0057] In some implementations, before determining the multi-user signal-to-interference-plus-noise ratio (SINNR) of the user equipment in the allocated subband using large-scale channel coefficients and the interference plus noise of the user equipment in the corresponding subband, the method further includes: For the current sub-band, multi-user equipment pairing is performed using large-scale channel coefficients and the interference plus noise of user equipment in the corresponding sub-band to obtain the sub-band allocation result.

[0058] Multi-user equipment pairing refers to selecting a group of user equipment (UEs) for each subband in a cellular massive MIMO system, enabling these UEs to share the frequency resources of that subband for downlink transmission. Its core objective is to improve subband resource utilization through multi-user multiplexing while ensuring transmission quality. Simultaneously, by selecting user combinations with controllable interference, strong interference between users within the same subband is avoided.

[0059] Subband allocation results can refer to the set of target user equipment (User Equipment) that are allowed to use the current subband for downlink data transmission in a non-cellular massive MIMO communication system, as well as the correspondence between the target User Equipment and the allocated subband. It can be used to indicate the allocation mapping relationship between User Equipment and the allocated subband.

[0060] Specifically, for the current subband, firstly, the set of devices to be paired (user equipment that has not yet been allocated resources for this subband) and the set of paired devices (initially empty) are determined from all user equipment. Next, using the large-scale channel coefficients and corresponding interference plus noise of the user equipment in the current subband, compatibility data is determined between each user equipment to be paired in the set of devices to be paired and each paired user equipment in the set of paired devices in the current subband. Based on this compatibility data, target user equipment that meets preset screening conditions is selected from the set of devices to be paired. This target user equipment is then removed from the set of devices to be paired and added to the set of paired devices, resulting in updated sets of devices to be paired and paired devices. This process of determining compatibility data, screening target user equipment, and updating the sets is repeated for all subbands until a preset termination condition is met (e.g., no remaining devices in the set of devices to be paired or the number of paired devices reaches its limit), thus finally determining the target user equipment set corresponding to each subband and obtaining the subband allocation results for all subbands.

[0061] In the above implementation, by using large-scale channel coefficients and interference plus noise for multi-user pairing, it is possible to accurately select target user groups with low interference while ensuring transmission quality, thereby effectively improving the efficiency of subband resource reuse.

[0062] In some implementation methods, please refer to Figure 2 The sub-band allocation result is determined in the following way: S210. For the current sub-band, determine the set of devices to be paired and the set of paired devices in the user equipment.

[0063] The set of devices to be paired can refer to the set of user equipments (UEs) that have not yet been allocated resources and still need to participate in multi-user pairing, which can be denoted as set U = [UE1, ..., UE2]. K}, where k is the user equipment number. The set of paired devices can specifically refer to the set of target user equipment in the current subband that has been paired and determined to be able to share the resources of that subband, denoted as set U. +,s During initialization, it can be made Where s is the number of the current sub-band.

[0064] It should be noted that the Media Access Control (MAC) layer of the UCDU receives scheduling preparation information from higher layers, such as the Radio Resource Control (RRC) layer. When the RRC protocol is deployed in the Centralized Unit (CU), this scheduling preparation information is sent from the CU to the DU through the mid-transmission interface (F1-C).

[0065] Specifically, when preparing scheduling information for the current subband, the basic scheduling data must first be defined. For example, in addition to the set of devices to be paired and the set of paired devices, it is also necessary to include the set of data volumes {Q1,...,Q} on all subbands. K}, weighted historical average throughput set The data volume set includes the amount of data waiting to be transmitted in the caches of all user devices. The weighted historical average throughput set includes the weighted historical average throughput of all user devices, used to describe the historical service quality weights of all user devices.

[0066] In addition, it is necessary to define the set of devices that have not yet been paired. and the total set of paired devices on the current subband The set of devices that have not yet been paired refers to the set of UEs selected from the set of devices to be paired, which still have data to transmit and have not yet completed pairing in any subband (have not obtained any subband resources). Its core function is to provide candidate devices for the set of devices to be paired in the current subband; that is, devices to be paired in the current subband can only be selected from this set, avoiding duplicate selection from UEs already paired in other subbands. It should be noted that during initialization, since all UEs have not been allocated resources, this set can be configured to be consistent with the set of devices to be paired. As all subbands are traversed, the set of devices that have not yet completed pairing is gradually updated and separated from the set of devices awaiting pairing. The total set of paired devices in the current subband can refer to the set of UEs that have completed pairing and obtained resources in at least one subband across all subbands in the entire system. It is initially empty, and its core function is to record the global UE status that has obtained resources: on the one hand, it can avoid the same UE from being repeatedly paired in multiple subbands, thereby preventing resource waste and interference accumulation. On the other hand, it can combine the weighted historical average throughput of UEs to ensure fairness in cross-subband scheduling, for example, to prevent one UE from occupying resources in multiple subbands while other UEs are not scheduled for a long time.

[0067] Understandably, during the process of traversing all subbands for pairing, for each subband s that needs to be paired, a separate set of devices to be paired on the current subband needs to be defined: U = {UE1, ..., UE2}. K From the above set of devices that have not yet been paired Selected from the list. The set of paired devices U on this sub-band. +,s It only records the UEs that have completed pairing on this subband s. That is, by establishing a global set and a local set for the current subband, it can accurately achieve clear control over the scheduling status of all UEs, and provide accurate UE source and status basis for subsequent multi-user pairing in the current subband.

[0068] S220. Based on large-scale channel coefficients and interference plus noise, determine the compatibility data of the target user equipment to be paired in the set of devices to be paired with all paired user equipment in the set of paired devices in the current subband.

[0069] It should be noted that when the UCDU's MAC performs multi-user device pairing, it needs to traverse all subbands sequentially according to subband order. For example, taking the initial pairing as an example, the subband number s = 1 for the current subband, and then all candidate user devices to be paired and all paired user devices on the current subband are determined. Since this is the initial pairing, there are... Therefore, the user equipment to be paired can be a set of devices to be paired, U = {UE1, ..., UE2}. K}(which equals the set of devices that have not yet been paired) Once a candidate user device is selected, it can be used as the target user device to be paired for subsequent calculations.

[0070] Furthermore, since there are no paired user equipments in the current set of paired devices on the subband, it is necessary to first pair the devices in the set U = {UE1,...,UE2} to be paired. K} (equal to the set of devices that have not yet been paired) Select one user equipment from the list as the root user equipment for the current subband. For example, the user equipment to be paired with the largest proportional fairness coefficient can be selected as the root user equipment of the current subband using the proportional fairness criterion, as shown in the following formula: In the formula, This refers to the root user equipment number on the current subband s; U - SINR refers to the set of devices that have not yet been paired; su,k,s It refers to the single-user signal-to-interference-plus-noise ratio (SU-SINR) of the root user equipment in the current subband s; It is the weighted historical average throughput of root user devices.

[0071] As shown in the above formula, the root user equipment is a user equipment with good instantaneous channel quality and low historical service volume. After determining the root user equipment, it can also be added to the set U of paired equipment in the current subband s. +,s In, that is, update At the same time, the root user equipment also needs to be removed from the set of user equipment to be paired.

[0072] Understandably, even in cases involving non-initial pairing, it's still necessary to remove all paired devices from the set of devices that haven't completed pairing. In other words, before calculating the compatibility data for the current subband s in the next pairing round, the following operation needs to be performed:

[0073] Compatibility data can refer to an indicator that measures the overall transmission efficiency of the target user equipment to be paired with all paired user equipments when sharing resources in the current subband. For example, the sum of the rates corresponding to the multi-user signal-to-interference-plus-noise ratio (MU-SINR) of the target user equipment to be paired with all paired user equipments can be used as compatibility data. The larger the value, the less interference they have in the same channel, the higher the resource reuse efficiency, and the better the compatibility.

[0074] Specifically, based on large-scale channel coefficients and interference plus noise, the compatibility data between the target user equipment (UE) in the set of devices to be paired and all paired UEs in the set of paired devices is determined in the current subband. This includes: firstly, using large-scale channel coefficients and interference plus noise, determining the first multi-user signal-to-interference-plus-noise ratio (MINR) of the target UE and the second MINR of all paired UEs. Then, based on the first MINR, determining the instantaneous transmission rate of the target UE in the current subband. Next, based on the second MINR, determining the sum of the instantaneous transmission rates of all paired UEs in the current subband. Finally, using the instantaneous transmission rates and the sum of the instantaneous transmission rates, determining the total transmission rate in the current subband as the compatibility data.

[0075] Understandably, for the initial pairing scenario, where only the root user equipment is paired, the first multi-user signal-to-interference-plus-noise ratio (MINR) can be determined using the large-scale channel coefficients of the target user equipment in the current subband and its interference plus noise. Then, the second MINR can be determined using the large-scale channel coefficients of the root user equipment in the current subband and its interference plus noise.

[0076] If it is not the first pairing scenario, there may be multiple paired user devices. In this case, it is necessary to use the first multi-user signal-to-interference-plus-noise ratio (MINR) of the target user device to be paired and the second MINR of all paired user devices (which may include the MINR of multiple paired user devices) for pairing.

[0077] For example, the first and second multi-user signal-to-interference-plus-noise ratios (MINRs) can be determined as follows: First, the precoding gain of the target MINR and all paired MINRs in the current subband is determined based on the first large-scale channel coefficients of the target MINR and the second large-scale channel coefficients of all paired MINRs. Then, the first MINR is determined using the precoding gain and the first interference plus noise of the MINR. Finally, the second MINR is determined using the precoding gain and the second interference plus noise of the paired MINR.

[0078] Similarly, if it is not the first pairing scenario, since there may be multiple paired user equipments, the second large-scale channel coefficients can also include multiple large-scale channel coefficients of all paired user equipments. Then, based on the first large-scale channel coefficients of the target user equipment to be paired and the second large-scale channel coefficients of all paired user equipments, the precoding gain of the target user equipment to be paired and all paired user equipments in the current subband is determined.

[0079] It's important to understand that this precoding gain can be interpreted as the useful signal power of the user equipment (UE), which is limited by the total power of the remote radio unit (RRU) and dynamically adjusted with the number of paired users within the subband. That is, as the number of paired users increases, the total power needs to be distributed among more users, causing the useful signal power of each user, including the UE to be paired, to decrease as the precoding gain is diluted. Specifically, the precoding gain in the current subband can be determined as follows: First, determine the total power of the antennas on each RRU in the distributed base station and the number of antennas. Then, use the total power, the number of antennas, and the large-scale channel coefficients to determine the precoding gain of the target UE to be paired and all paired UEs in the current subband.

[0080] In this context, the total power of the antenna on each remote radio unit in a distributed base station can refer to the total power of the RRU on a single subcarrier, denoted as P. The number of antennas, i.e., the total number of antennas on the remote radio unit, can be denoted as M.

[0081] Specifically, approximate computation can be performed using distributed zero-forcing (ZF) precoding. Assume the physical layer has a set of paired devices {U} on the current subband s. +s, ∪UE k There are K' candidate user equipments using ZF precoding. Therefore, the downlink channel matrix from the K' candidate user equipments to the l-th remote radio unit (RRU) can be G = [g l,1 ,...,g l,K′ ] T ∈C K′×M Where l is the RRU number; K' is the total number of candidate user equipment; and M is the number of antennas.

[0082] The ZF precoder corresponding to RRUl is W = c1·G H (GG H ) -1 ∈C M×K′ Where K' is the total number of candidate user equipment; M is the number of antennas; c l G is the power coefficient of the l-th RRU; G is the downlink channel matrix from the K' candidate user equipments to the l-th RRU; G H Let be the conjugate transpose of the downlink channel matrices from the K' candidate user equipments to the l-th RRU.

[0083] Furthermore, considering the power constraint of the l-th RRU, we have Among them, W l It can be understood as the ZF precoding matrix corresponding to the l-th RRU; tr(·) is the trace operation of the matrix; P is the total power of the RRU on a single subcarrier.

[0084] Then you can get Therefore, the following formula can be derived: In the formula, Let be the normalized power coefficient of the l-th RRU, i.e., the precoding gain; P be the total power of the RRU on a single subcarrier, i.e., the total antenna power of each remote radio unit in the distributed base station; tr(·) is the trace operation of the matrix; G is the downlink channel matrix from K' candidate user equipment to the l-th RRU; G H Let be the conjugate transpose of the downlink channel matrices from the K' candidate user equipments to the l-th RRU.

[0085] It is easy to see that the precoding gain calculation described above requires complete spatial channel information. However, based on asymptotic orthogonality, the precoding gain can also be obtained by approximating the calculation using only large-scale channel coefficients.

[0086] Specifically, firstly, the product of the number of antennas and the total power of the antennas on each remote radio unit in the distributed base station can be calculated to reflect the total transmission capacity of the system. Then, the sum of the inverses of the large-scale channel coefficients of all candidate user equipment is calculated to reflect the relevant channel information. Finally, the product of the number of antennas and the total power is divided by the sum of the inverses of the large-scale channel coefficients of all candidate user equipment to approximately represent the gain that the system can obtain through precoding techniques, considering the overall influence of all candidate user channels.

[0087] For example, an approximate calculation can be performed using the following formula: In the formula, M is the precoding gain; P is the number of antennas; P is the total power of the antennas on each remote radio unit in the distributed base station; K' is the total number of candidate user equipment. These are large-scale channel coefficients.

[0088] Alternatively, a joint ZF precoding scheme can be executed by combining large-scale channel information from multiple RRUs to the UE, thereby further improving the precoding gain of the system.

[0089] For example, taking K' candidate user equipments using ZF precoding, the downlink channel matrix from the K' candidate user equipments to the l-th RRU is G. l =[g l，1 , ..., g l，K′ ] T ∈C K′×M .

[0090] The joint precoder W can be transformed into L submatrices through row partitioning: Where the submatrix W L ∈C M×K′ Let represent the local precoding matrix of the l-th RRU, and have .

[0091] Considering the power constraint of the l-th RRU, we have Right now: In the formula, c 2G is the precoding gain; G is the downlink channel matrix from the K' candidate user equipments to the l-th RRU; G is the conjugate transpose of the downlink channel matrix from the K' candidate user equipments to the l-th RRU; tr(·) is the trace operation of the matrix; P is the total power of the antenna on each remote radio unit in the distributed base station.

[0092] Then, based on asymptotic orthogonality, we have: Considering the precoding power constraint of a total of L RRUs, another formula for calculating the precoding gain is obtained: In the formula, c 2 β is the precoding gain; l，k is the large-scale channel coefficient; M is the number of antennas; l' is the RRU number.

[0093] Specifically, the above formula involves the following steps: Step 1: For each user equipment (UFO), calculate the sum of the large-scale channel coefficients of all RRUs to it, and then square this sum. Step 2: Divide the channel coefficient of the RRU corresponding to each UFO by the product of the number of antennas and the square of the sum obtained in Step 1. Step 3: For the current RRU1, sum the calculation results of all UFOs obtained in Step 2. Step 4: Divide the total power by the result obtained in Step 3. Finally, iterate through all L RRUs, repeating Steps 3 and 4 for each RRU to calculate all candidate precoding gains, and then take the minimum value from these L results as the final precoding gain.

[0094] This method allows for the rapid estimation of useful signals and multi-user interference power at the UCDU side using large-scale channel coefficients. This approximation simplifies spatial matrix operations to scalar operations, eliminating the need for cross-node transmission of high-dimensional CSI and adapting to the real-time scheduling requirements of non-cellular massive MIMO systems.

[0095] Furthermore, after determining the precoding gain of the target user equipment to be paired and all paired user equipments in the current subband, a first multi-user signal-to-interference-plus-noise ratio (SINNR) can be determined using the precoding gain and the first interference plus noise of the target user equipment. Finally, a second SINNR is determined using the precoding gain and the second interference plus noise of the paired user equipment.

[0096] Here, the first interference plus noise can refer to the sum of the background interference power and the noise power experienced by the user equipment k to be paired in the current subband, which can be denoted as: The second interference plus noise can refer to the sum of the background interference power and noise power experienced by the paired user equipment j in the current subband, which can be denoted as:

[0097] It should be noted that the calculation methods for the first interference plus noise and the second interference plus noise are the same. Taking the calculation of the first multi-user signal-to-interference-plus-noise ratio (SINNR) of the user equipment to be paired as an example, after determining the precoding gain of the current subband, it can be divided by the first interference plus noise of the user equipment to be paired to obtain the first SINNR, as shown in the following formula: In the formula, SINR mu，k，s The first multi-user signal-to-interference-plus-noise ratio is represented by ; k represents the number of the user equipment to be paired; l is the RRU number; L is the precoding gain; L is the total number of RRUs. This represents the first interference plus noise of the user equipment k to be paired on subband s.

[0098] In this way, based on the interference plus noise that reflects the useful signal strength and the coding gain and the level of interference, the actual signal quality when multiple users coexist is accurately quantified. Moreover, the calculation process only relies on the large-scale channel coefficient and its own interference plus noise, which balances accuracy and low complexity, and provides a reliable basis for subsequent compatibility judgment.

[0099] Furthermore, after determining the first multi-user signal-to-interference-plus-noise ratio (MINR) of the target user equipment to be paired and the second MINR of all paired user equipments, the instantaneous transmission rate of the target user equipment to be paired and the sum of the instantaneous transmission rates of all paired user equipments can be calculated based on them. Finally, the total transmission rate on the current subband is determined using the instantaneous transmission rate and the sum of the instantaneous transmission rates as compatibility data.

[0100] In this context, the instantaneous transmission rate can refer to the real-time data transmission rate of the target user equipment to be paired in a multi-user scenario on the current subband. The sum of instantaneous transmission rates can refer to the total real-time data transmission rate of all paired user equipments in a multi-user scenario on the current subband. The total transmission rate can refer to the sum of the instantaneous transmission rates of all paired user equipments on the current subband, including the current candidate target user equipment to be paired.

[0101] Specifically, for a selected target user equipment to be paired, its instantaneous transmission rate can be calculated based on its multi-user signal-to-interference-plus-noise ratio (MINR). Similarly, for each paired user equipment in the paired equipment set, its instantaneous transmission rate can also be calculated based on its MINR. These instantaneous transmission rates are then summed to obtain the sum of the instantaneous transmission rates of all paired user equipment. Finally, the sum of the instantaneous transmission rates of the target user equipment to be paired and all user equipment in the paired equipment set is added together to obtain the total rate of the current subband, which serves as compatibility data.

[0102] For example, the instantaneous transmission rate of all user equipment is calculated in the same way. Here, taking the target user equipment to be paired as an example, the instantaneous transmission rate R of the target user equipment to be paired is calculated. k,s Please refer to the following formula: R k，s =log2(1+SINR) mu，k，s ) In the formula, R k,s SINR represents the instantaneous transmission rate. mu,k,s This represents the first multi-user signal-to-noise ratio (SNR).

[0103] The sum rate of the current subband is then determined using the following formula: R s =log2(1+SINR) mu,k,s )+log2(1+SINR mu,j,s ) In the formula, SINR mu，k，s SINR represents the first multi-user signal-to-interference-plus-noise ratio. mu，j，s This indicates the second-most-user signal-to-noise ratio (SNR).

[0104] S230. Based on compatibility data, identify target user devices that meet preset screening conditions from the set of devices to be paired.

[0105] It should be noted that preset screening conditions refer to rules or thresholds set in advance during the device pairing process in wireless communication to select target user devices suitable for sharing the current subband with paired devices from the set of devices to be paired. These conditions can be used to measure the coexistence performance of the devices to be paired and paired devices in the current subband, ensuring that the overall communication quality after pairing meets the expected standards.

[0106] For example, preset filtering conditions may include transmission conditions, channel conditions, and interference conditions.

[0107] Among them, the transmission condition can refer to the fact that after the user equipment joins the pair, the overall transmission performance of the system must be better than the performance before joining, so as to ensure that the access of the new user can improve the system efficiency rather than reduce it.

[0108] For example, as shown in the following formula, it can be determined whether a user equipment meets the transmission conditions based on the sum and transmission rate (compatibility data) of the user equipment to be paired.

[0109] In the formula, k represents the user equipment number to be paired; j represents the paired user equipment number; s represents the current subband number; SINR mu，k，s SINR represents the first multi-user signal-to-interference-plus-noise ratio. mu，j，s This indicates the second-most-user signal-to-noise ratio (SNR).

[0110] It is understandable that in the above formula This indicates that the user equipment k to be paired is selected from the global set (devices that have not yet completed pairing) and other user equipment excluding the set of paired devices in the current subband. In the above formula This indicates that the paired device was selected from the set of paired devices.

[0111] Channel conditions refer to the requirement that the channel quality of the user equipment to be paired must reach a preset threshold to ensure that it can stably receive effective signals and meet basic communication needs.

[0112] Specifically, before the UCDU's MAC begins multi-user equipment pairing, pairing algorithm parameters can be configured, including a first threshold SINR for the minimum single-user signal-to-interference-plus-noise ratio (SU-SINR) of the user equipment to be paired. thres，1 That is, the multi-user signal-to-interference-plus-noise ratio (SINNR) of the user equipment to be paired in its current subband is compared with the first threshold to determine whether the user equipment to be paired meets the channel conditions.

[0113] Interference conditions can refer to the fact that after the user equipment to be paired joins the pairing, it will not cause unacceptable interference to the channel quality of the already paired user equipment, ensuring that the communication stability of the existing users is not compromised.

[0114] Specifically, when configuring the pairing algorithm parameters, a second threshold SINR can also be included, which represents the minimum multi-user signal-to-interference-plus-noise ratio (MU-SINR) if the user equipment to be paired is successfully paired in the current subband. thres，2 That is, after pairing is completed, the multi-user signal-to-interference-plus-noise ratio (SINNR) and a second threshold of all user devices in the current subband, including the user device to be paired that has just successfully completed pairing, can be compared to determine whether the user device to be paired meets the interference conditions.

[0115] Furthermore, determining the target user equipment that meets the preset screening conditions in the set of devices to be paired based on compatibility data may include: performing a transmission judgment based on compatibility data and transmission conditions to obtain a transmission judgment result; performing a channel judgment based on the single-user signal-to-interference-plus-noise ratio and channel conditions of the target user equipment to be paired to obtain a channel judgment result; performing an interference judgment based on the multi-user signal-to-interference-plus-noise ratio and interference conditions of the target user equipment to be paired to obtain an interference judgment result; and determining the target user equipment in the set of devices to be paired based on the transmission judgment result, the channel judgment result, and the interference judgment result.

[0116] Among them, the transmission judgment result, channel judgment result, and interference judgment result can be either satisfied or not satisfied with the conditions.

[0117] Specifically, if all three judgment results indicate that the target user device to be paired meets the corresponding screening conditions, the target user device to be paired can be regarded as the target user device that meets the preset screening conditions.

[0118] In other words, a target user equipment k0 must simultaneously meet the following three conditions to be considered a target user equipment and added to the current subband's set of paired devices U. +,s In (i.e., setting) ).

[0119] Before the target user equipment k0 participates in pairing, the current subband already paired device set U +，s The compatibility data of all paired user equipment j should be less than that of the user equipment k0 to be paired. After pairing, the set of paired devices U in the current subband, including k0, should be used. +，s of The system collects compatibility data for all paired user devices j to ensure the gain of system transmission.

[0120] Secondly, for the user equipment to be paired k0 itself, the multi-user signal-to-interference-plus-noise ratio (SINNR) of the user equipment to be paired in its current subband must be greater than the first threshold, i.e. This is to ensure the reliability of the new user's own channel.

[0121] Finally, after pairing is completed, the multi-user signal-to-interference-plus-noise ratio (SIR) of paired user equipment in the current subband, including k0, must be greater than or equal to the second threshold. That is, after successful pairing... SINR mu，j，s ≥SINR thres，2 This is to limit the disruptive impact of new users on existing users.

[0122] Thus, by leveraging the triple mechanism of transmission gain, channel threshold, and interference threshold, all candidate devices to be paired can be filtered layer by layer. First, it ensures that the total transmission rate will be increased after the addition of a new UE. Then, it eliminates those whose own channels are unqualified. Finally, it checks whether the interference of the paired users is within a controllable range. This ensures that the pairing results maximize system efficiency while maintaining the stability of existing users, achieving real-time scheduling that is both accurate and low-complexity.

[0123] S240. Remove the target user device from the set of devices to be paired and add the target user device to the set of paired devices to obtain the updated set of devices to be paired and the updated set of paired devices.

[0124] Specifically, after identifying target user devices that meet preset screening criteria from the set of devices to be paired based on compatibility data, these devices can be removed from the global set of users to be scheduled, resulting in an updated set of paired devices with the removed user device. This updated set is then added to the set of paired users on the current subband, resulting in an updated set of devices to be paired. User devices in this updated set of devices to be paired still belong to the set of devices that have not yet completed pairing; that is, they still have data to be transmitted and have not been assigned to any subband. They can continue to participate in the next round of pairing in the current subband, or they can participate in subsequent pairing processes in other subbands after all pairings in the current subband are completed.

[0125] S250. For the updated set of devices to be paired and the updated set of paired devices, repeat the above multi-user device pairing process. If the preset termination condition is met, obtain the sub-band allocation result for each sub-band.

[0126] The preset termination conditions can include the preset termination conditions for the current sub-band and the preset termination conditions for all sub-bands. Specifically, the preset termination conditions for the current sub-band can include that there are no remaining devices in the set of devices to be paired that can participate in the pairing of the current sub-band, or that the number of paired devices in the current sub-band has reached the spatial multiplexing capacity limit of the RRU.

[0127] Understandably, after the current subband pairing is complete, the following core data can be updated: First, there is the data set of all user devices {Q}. k}={Q1,...,Q K}, update the remaining amount of data to be transmitted on the target user device to Q. k =Q k -TBS k TBS k The transport block size obtained by the target user equipment in the current subband allocation result of the current subband.

[0128] Secondly, the weighted historical average throughput set of all user devices Specifically, the update can be performed using the following formula: In the formula, R represents the weighted historical average throughput of the k-th user device; k,s α represents the rate obtained by the k-th user equipment after scheduling on subband s; α represents the smoothing factor.

[0129] Finally, the sub-band number s = s + 1 is set, and the multi-user device pairing process for the next sub-band is executed.

[0130] Furthermore, for the next sub-band, the above multi-user device pairing process is repeated until the preset termination condition for all sub-bands is met. This termination condition can be that all sub-bands in the system have completed the above pairing process, or that the amount of data to be transmitted for all user devices is 0. This indicates that no data needs to be transmitted.

[0131] In the above implementation, by iteratively completing compatibility assessment, triple threshold filtering, set update and termination determination, the final output subband allocation result maximizes the total system rate while ensuring the stability of existing users, thus achieving low-forwarding, low-complexity and high-precision real-time multi-user pairing under the CF-mMIMO architecture.

[0132] It should be understood that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart above may include multiple steps or stages, which are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps.

[0133] This specification also provides a multi-user downlink scheduling device 300, applied to a non-cellular massive MIMO communication system, the system including distributed base stations and user equipment; such as Figure 3 As shown, it includes: a coefficient acquisition module 310, a signal-to-interference-plus-noise ratio (SIR) determination module 320, and a downlink transmission module 330. Wherein: The coefficient acquisition module 310 is used for large-scale channel coefficients from each user equipment to each remote radio frequency unit in the distributed base station.

[0134] The signal-to-interference-plus-noise ratio (SINR) determination module 320 is used to determine the multi-user SINR of the user equipment in the allocated subband by utilizing large-scale channel coefficients and the interference plus noise of the user equipment in the corresponding subband.

[0135] Downlink transmission module 330 is used to determine the target modulation and coding strategy of user equipment using the multi-user signal-to-interference-plus-noise ratio (SINNR) in order to perform downlink transmission operations; wherein, the target modulation and coding strategy is used to describe the transmission parameters of user equipment on the allocated subband.

[0136] In some implementations, the signal-to-interference-plus-noise ratio (SINR) determination module 320 is further configured to determine the single-user SINR of the user equipment in the corresponding sub-band based on the channel quality data of the user equipment in all sub-bands; and to determine the interference plus noise of the user equipment in the corresponding sub-band using the single-user SINR.

[0137] In some embodiments, the multi-user downlink scheduling apparatus 300 further includes a user equipment pairing module, which is used to pair multiple user equipment for the current subband using large-scale channel coefficients and the interference plus noise of user equipment in the corresponding subband to obtain a subband allocation result; wherein, the subband allocation result is used to indicate the allocation mapping relationship between user equipment and the allocated subband.

[0138] In some implementations, the user equipment pairing module is further configured to: determine a set of user equipment to be paired and a set of paired user equipment for the current subband; determine compatibility data of the user equipment to be paired in the set of user equipment to be paired and the user equipment in the set of paired user equipment for the current subband based on large-scale channel coefficients and interference plus noise; determine target user equipment that meets preset screening conditions in the set of user equipment to be paired based on the compatibility data; remove the target user equipment from the set of user equipment to be paired and add the target user equipment to the set of paired user equipment to obtain an updated set of user equipment to be paired and an updated set of paired user equipment; repeat the above multi-user equipment pairing process for the updated set of user equipment to be paired and the updated set of paired user equipment to obtain the subband allocation result for each subband when a preset termination condition is met.

[0139] In some implementations, the preset screening conditions include transmission conditions, channel conditions, and interference conditions; the user equipment pairing module is further configured to, when all user equipment to be paired meets the transmission conditions, channel conditions, and interference conditions, designate the user equipment to be paired as the target user equipment that meets the preset screening conditions.

[0140] In some implementations, the user equipment pairing module is further configured to determine a first multi-user signal-to-interference-plus-noise ratio (MINR) of the user equipment to be paired and a second MINR of the paired user equipment using large-scale channel coefficients and interference plus noise; determine a first instantaneous transmission rate of the user equipment to be paired on the current subband based on the first MINR; determine a second instantaneous transmission rate of the paired user equipment on the current subband based on the second MINR; and determine the sum transmission rate on the current subband using the first instantaneous transmission rate and the second instantaneous transmission rate as compatibility data.

[0141] In some implementations, the signal-to-interference-plus-noise ratio (SINNR) determination module 320 is further configured to determine the precoding gain on the current subband based on large-scale channel coefficients; determine a first multi-user SINNR using the precoding gain and a first interference plus noise of the user equipment to be paired; and determine a second multi-user SINNR using the precoding gain and a second interference plus noise of the paired user equipment.

[0142] In some implementations, the signal-to-interference-plus-noise ratio (SINR) determination module 320 is also used to determine the total power of the antennas on each remote radio frequency unit in the distributed base station and the number of antennas; and to determine the precoding gain on the current subband using the total power, the number of antennas, and the large-scale channel coefficient.

[0143] In some implementations, the coefficient acquisition module 310 is also used to acquire the full-dimensional channel coefficients of each antenna on each remote radio unit from each user equipment; and to simplify the full-dimensional channel coefficients to obtain large-scale channel coefficients; wherein the simplification process includes modulus square operation and average operation.

[0144] For specific limitations regarding a multi-user downlink scheduling device, please refer to the limitations of a multi-user downlink scheduling method described above, which will not be repeated here. Each module in the aforementioned multi-user downlink scheduling device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module. In this embodiment, the multi-user downlink scheduling device is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the aforementioned functions.

[0145] This application also provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a multi-user downlink scheduling method. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device casing, or an external keyboard, touchpad, or mouse. Those skilled in the art will understand that… Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0146] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0147] This application provides a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method of any embodiment of this application.

[0148] The multi-user downlink scheduling method, apparatus, device, and storage medium described in the above embodiments can be implemented by a computer chip or physical entity, or by a product with a certain function. A typical implementation device is a computer. For ease of description, the above apparatus is described by dividing it into various functional units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware. Those skilled in the art should understand that the embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0149] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. Since they are basically similar to the method embodiments, the descriptions are relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The above descriptions are merely embodiments of this application and are not intended to limit this application. For those skilled in the art, this application can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application. Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by the appended claims. In the description of this specification, the reference to terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., means that the specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0150] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0151] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A multi-user downlink scheduling method, characterized in that, The method is applied to a cell-free massive multiple-input multiple-output communication system, the system comprising distributed base stations and user equipment; the method comprising: obtaining large-scale channel coefficients of each user equipment to each remote radio unit in the distributed base stations; determining a multi-user signal-to-interference-and-noise ratio of the user equipment on an allocated subband using the large-scale channel coefficients and interference-plus-noise of the user equipment on a corresponding subband, wherein the multi-user signal-to-interference-and-noise ratio is used to describe transmission parameters of the user equipment on the allocated subband. The interference-plus-noise is determined in the following manner:

2. The method of claim 1, wherein, determining a single-user signal-to-interference-and-noise ratio of the user equipment on the corresponding subband based on channel quality data of the user equipment on all subbands; determining the interference-plus-noise of the user equipment on the corresponding subband using the single-user signal-to-interference-and-noise ratio. Before the step of determining the multi-user signal-to-interference-and-noise ratio of the user equipment on the allocated subband using the large-scale channel coefficients and the interference-plus-noise of the user equipment on the corresponding subband, the method further comprises:

3. The method of claim 1, wherein, performing multi-user equipment pairing using the large-scale channel coefficients and the interference-plus-noise of the user equipment on the corresponding subband to obtain a subband allocation result for a current subband, wherein the subband allocation result is used to indicate an allocation mapping relationship between the user equipment and the allocated subband. The subband allocation result is determined in the following manner:

4. The method of claim 3, wherein, determining a set of to-be-paired equipment and a set of paired equipment in the user equipment for the current subband; determining compatibility data of a target to-be-paired user equipment in the set of to-be-paired equipment and all paired user equipment in the set of paired equipment on the current subband based on the large-scale channel coefficients and the interference-plus-noise; determining a target user equipment satisfying a preset screening condition in the set of to-be-paired equipment based on the compatibility data; removing the target user equipment from the set of to-be-paired equipment and adding the target user equipment to the set of paired equipment to obtain an updated set of to-be-paired equipment and an updated set of paired equipment; repeating the multi-user equipment pairing process for the updated set of to-be-paired equipment and the updated set of paired equipment to obtain the subband allocation result of each subband when a preset termination condition is satisfied. The preset screening condition comprises a transmission condition, a channel condition, and an interference condition; and the target user equipment satisfying the preset screening condition in the set of to-be-paired equipment is determined based on the compatibility data in the following manner:

5. The method of claim 4, wherein, performing transmission judgment based on the compatibility data and the transmission condition to obtain a transmission judgment result; performing channel judgment based on a single-user signal-to-interference-and-noise ratio of the target to-be-paired user equipment and the channel condition to obtain a channel judgment result; performing interference judgment based on a multi-user signal-to-interference-and-noise ratio of the target to-be-paired user equipment and the interference condition to obtain an interference judgment result; and ​ determining the target user equipment in the set of to-be-paired devices based on the transmission judgment result, the channel judgment result and the interference judgment result.

6. The method of claim 4, wherein, The compatibility data is determined by determining a first multi-user signal-to-interference-and-noise ratio of the target to-be-paired user equipment and a second multi-user signal-to-interference-and-noise ratio of all the paired user equipment by using the large-scale channel coefficient and the interference-plus-noise; determining an instantaneous transmission rate of the target to-be-paired user equipment on the current sub-band based on the first multi-user signal-to-interference-and-noise ratio; determining instantaneous transmission rates of all the paired user equipment on the current sub-band based on the second multi-user signal-to-interference-and-noise ratio; and determining a total transmission rate on the current sub-band by using the instantaneous transmission rate and the sum of the instantaneous transmission rates as the compatibility data.

7. The method of claim 6, wherein, The determining of the first multi-user signal-to-interference-and-noise ratio of the target to-be-paired user equipment and the second multi-user signal-to-interference-and-noise ratio of all the paired user equipment by using the large-scale channel coefficient and the interference-plus-noise includes: determining a precoding gain of the target to-be-paired user equipment and all the paired user equipment on the current sub-band based on a first large-scale channel coefficient of the target to-be-paired user equipment and second large-scale channel coefficients of all the paired user equipment; determining the first multi-user signal-to-interference-and-noise ratio by using the precoding gain and a first interference-plus-noise of the to-be-paired user equipment, and determining the second multi-user signal-to-interference-and-noise ratio by using the precoding gain and a second interference-plus-noise of the paired user equipment.

8. The method of claim 7, wherein, The determining of the precoding gain of the target to-be-paired user equipment and all the paired user equipment on the current sub-band based on the first large-scale channel coefficient of the target to-be-paired user equipment and the second large-scale channel coefficients of all the paired user equipment includes: determining a total power of an antenna on each remote radio unit in the distributed base station and an antenna quantity of the antenna; determining the precoding gain of the target to-be-paired user equipment and all the paired user equipment on the current sub-band by using the total power, the antenna quantity and the large-scale channel coefficient.

9. The method of claim 1, wherein, The obtaining of the large-scale channel coefficient of each user equipment to each remote radio unit in the distributed base station includes: obtaining a full-dimension channel coefficient of each antenna on each remote radio unit for each user equipment; simplifying the full-dimension channel coefficient to obtain the large-scale channel coefficient, wherein the simplifying includes a modulus square operation processing and an average operation processing.

10. A computer device, comprising: The method includes: a memory and a processor, which are communicatively connected with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the method in any one of claims 1 to 9.

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