Non-orthogonal multiple access method, base station, and user equipment

Abstract

A non-orthogonal multiple access method is performed in a system having a central controller, a plurality of transmission and reception points (TRPs), and user equipment (UE) in a cloud radio access network (CRAN). The UE performs an open-loop power control method to determine a power domain eigenvalue based on macro diversity associated with the UE. The central controller obtains the signal quality of the UE from the power domain eigenvalue of the UE, classifies the UE according to the signal quality of the UE, and differentiates different practices regarding whether to use a multi-user interference cancellation scheme in the decoding of the radio signal for the classified UE.

Description

Technical Field

[0001] The present disclosure relates to the field of communication systems, and more particularly, to non-orthogonal multiple access (NOMA) in a cloud radio access network (CRAN) with high connection density. Background Art

[0002] Wireless communication systems, such as the standards and technologies of third-generation (3G) mobile phones, are well known. Such 3G standards and technologies were developed by the Third Generation Partnership Project (3GPP). The third-generation wireless communication was widely developed to support giant cellular mobile phone communication. Communication systems and networks have evolved into a broadband and mobile system. In a cellular wireless communication system, a user equipment (UE) is connected to a radio access network (RAN) through a wireless link. The RAN includes a set of base stations (BSs) that provide wireless links for user equipment in the cells covered by the base stations, and an interface with a core network (CN) that provides overall network control. It can be understood that the RAN and the CN each perform functions related to the entire network. The Third Generation Partnership Project developed the so-called Long Term Evolution (LTE) system, i.e., the evolved universal mobile telecommunication system territorial radio access network (E-UTRAN), for mobile access networks, where a base station called an evolved NodeB (eNodeB or eNB) supports one or more giant cells. Recently, LTE is further evolving towards the so-called 5G or New Radio (NR) system, where one or more cells are supported by base stations called gNBs.

[0003] With the proliferation of smart devices and the rise of new services with high-capacity requirements, wireless networks are facing a series of brand-new challenges in terms of technology and business models.

[0004] In fact, the next-generation mobile network must meet diverse requirements through different key performance indicators (KPIs). The 5G mobile network can enable three major categories of emerging services: enhanced mobile broadband (eMBB), ultra-reliable and low-latency communication (uRLLC), and massive machine type communication (mMTC).

[0005] The current mobile network architecture has proven insufficient to meet the requirements of 5G services. In fact, previous generations of networks were designed specifically to meet the requirements of voice and traditional mobile broadband services. Since the 5G network is expected to provide diverse services, support current standards such as LTE and wireless local area network (WLAN), and coordinate different site types, a more flexible and distributed service-driven architecture is needed. Summary of the Invention

[0006] An object of the present disclosure is to propose a NOMA method, a base station, and a user equipment.

[0007] The first aspect of the present disclosure provides a non-orthogonal multiple access (NOMA) method, which can be executed in a central controller of a base station and includes:

[0008] Receiving wireless signals from a group of V user equipments (UEs) through a group of M distributed radio nodes, where V and M are positive integers;

[0009] Estimating the signal quality of each user equipment in the group of V user equipments;

[0010] Classifying the group of V user equipments into a high signal quality subgroup and a low signal quality subgroup according to the estimated signal quality of each user equipment in the group of V user equipments; and

[0011] Using a multi-user interference cancellation scheme to decode the wireless signals of the user equipments belonging to the low signal quality subgroup; and

[0012] Decoding the wireless signals of the user equipments belonging to the high signal quality subgroup without using the multi-user interference cancellation scheme.

[0013] The second aspect of the present disclosure provides a non-orthogonal multiple access method, which can be executed in a user equipment (UE) and includes:

[0014] Obtain a plurality of power domain measurements of wireless signals of a set of distributed radio nodes;

[0015] Obtain a power domain eigenvalue of the user equipment from the plurality of power domain measurements; and

[0016] Transmit the power domain eigenvalue for a multiple access procedure associated with the user equipment.

[0017] A third aspect of the present disclosure provides a base station, comprising:

[0018] A transceiver; and

[0019] A processor, connected to the transceiver and configured to perform the following steps, including:

[0020] Receive wireless signals from a set of V user equipments (UEs) through a set of M distributed radio nodes, where V and M are positive integers;

[0021] Estimate the signal quality of each user equipment in the set of V user equipments;

[0022] Classify the set of V user equipments into a high signal quality subgroup and a low signal quality subgroup according to the estimated signal quality of each user equipment in the set of V user equipments; and

[0023] Decode the wireless signals of the user equipments belonging to the low signal quality subgroup using a multi-user interference cancellation scheme; and

[0024] Decode the wireless signals of the user equipments belonging to the high signal quality subgroup without using the multi-user interference cancellation scheme.

[0025] A fourth aspect of the present disclosure provides a user equipment (UE), characterized by comprising:

[0026] A transceiver; and

[0027] A processor, connected to the transceiver and configured to perform the following steps, including:

[0028] Obtain a plurality of power domain measurements of wireless signals of a set of distributed radio nodes;

[0029] Obtain a power domain eigenvalue of the user equipment from the plurality of power domain measurements; and

[0030] Transmit the power domain eigenvalue for a multiple access procedure associated with the user equipment.

[0031] The disclosed method can be implemented in a chip. The chip may include a processor configured to call and run a computer program stored in a memory to cause a device in which the chip is installed to execute the disclosed method.

[0032] The disclosed method can be programmed as computer-executable instructions stored in a non-transitory computer-readable medium. The non-transitory computer-readable medium, when loaded into a computer, instructs a processor of the computer to execute the disclosed method.

[0033] The non-transitory computer-readable medium may include at least one from the following group: hard disk, CD-ROM, optical storage device, magnetic storage device, read-only memory, programmable read-only memory, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory, and flash memory.

[0034] The disclosed method can be programmed as a computer program product to cause a computer to execute the disclosed method.

[0035] The disclosed method can be programmed as a computer program to cause a computer to execute the disclosed method.

[0036] Advantageous effects:

[0037] The present invention realizes grant-free uplink power-domain NOMA in a hyper-dense CRAN while improving network performance. The disclosed invention can be implemented by a computer program executable by a computerized device and can be stored in a memory or a storage medium, which, when loaded into the device, instructs a processor of the device to execute the method.

[0038] The present invention optimizes the combination of the cloud radio access network (CRAN) and NOMA to address the disadvantages of the two technologies and achieve grant-free access to UEs (such as MTC devices). The key part of the present invention includes leveraging the significant macro diversity of the CRAN architecture to address the difficulties of the power-domain NOMA. The proposed power control and detection weight optimization are both based on the CRAN macro diversity. The proposed detection weight optimization can avoid the need for power control allocated by the network and optimize the NOMA receiver by reducing the workload of interference cancellation. Description of the Drawings

[0039] To more clearly illustrate the embodiments of the present disclosure or related technologies, the following will briefly introduce the embodiments. Obviously, the accompanying drawings are only some embodiments of the present disclosure content. Those of ordinary skill in the art can obtain other drawings based on these drawings without paying the above-mentioned premise.

[0040] Figure 1 is a schematic diagram showing a telecommunications system.

[0041] Figure 2 is a schematic diagram showing a CRAN with a baseband unit pool, remote radio heads, and UEs.

[0042] Figure 3 is a schematic diagram showing a NOMA method executed on the UE side according to an embodiment of the present disclosure.

[0043] Figure 4 is a schematic diagram showing a NOMA method executed on the uplink receiving end according to an embodiment of the present disclosure.

[0044] Figure 5 is a schematic diagram showing the influence of the proposed open-loop power control method on the spectral efficiency (SE) of different priority / reliability (P / R) coefficients.

[0045] Figure 6 is a schematic diagram showing a NOMA method executed on the uplink receiving end according to another embodiment of the present disclosure content.

[0046] Figure 7 is a schematic diagram showing the bit error rate as a function of the SIC decoding rank for two active UE devices.

[0047] Figure 8 is a schematic diagram showing the bit error rate as a function of the SIC decoding rank for four active UE devices.

[0048] Figure 9 is a block diagram showing a wireless communication system according to an embodiment of the present disclosure. Detailed implementation manners

[0049] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings in combination with technical matters, structural features, implementation purposes, and effects. Specifically, the terms in the embodiments of the present disclosure are only used for the purpose of describing specific embodiments and do not limit the present disclosure.

[0050] Using software-defined networking (SDN) and network functions virtualization (NFV), the cloud network architecture can effectively handle the diverse 5G services through various key performance indicators (KPIs). A cloud radio access network (CRAN) with flexible base station function splitting options has been proposed to address the limitations of traditional network architectures.

[0051] CRAN enables UEs to receive diverse services with high energy efficiency, high spectral efficiency, and even lower network operating costs. However, due to a large number of user connections, the increasingly severe spectrum scarcity, and energy-constrained devices, CRAN faces many technical challenges. A potentially promising technology to address these issues is non-orthogonal multiple access (NOMA). The orthogonal access schemes traditionally used in previous network standards may be very limited in the CRAN environment.

[0052] Maintaining orthogonal access to network resources leads to limitations in system connectivity, capacity, and even increased latency due to signaling overhead. This limitation means that alternative multiple access schemes need to be considered to meet the large-scale connectivity requirements of mMTC in 5G. In the description, several NOMA schemes are proposed to address the KPIs of the new radio (NR) that cannot be solved by orthogonal access. NOMA itself introduces multi-user interference because different data layers are multiplexed on the same orthogonal resources. Signals from different users can be distinguished based on user-specific signatures. The users described in this article represent user equipment.

[0053] Due to the sporadic, latency-tolerant, and uplink-biased traffic characteristics of MTC devices, NOMA is particularly interesting for mMTC. When designing an uplink (UL) NOMA scheme, the following key aspects need to be considered:

[0054] · Unauthorized transmission;

[0055] · Support for overloaded transmission; and

[0056] · Low-complexity receivers.

[0057] The present disclosure aims to optimize the combination of the CRAN and NOMA technologies to overcome their respective limitations. The main goal of the present invention is to implement unlicensed uplink power domain NOMA in CRAN. This is achieved through a novel open-loop power control scheme and a fully optimized reception scheme.

[0058] 5G and beyond networks are expected to support a wide range of vertical services with different requirements. In fact, future networks need to provide access to a variety of service categories with heterogeneous traffic characteristics. Different service categories emphasize different KPIs. For MTC, the main KPIs include connection density, deep coverage, and energy efficiency.

[0059] With the advent of the Internet of Things (IoT) applications, it has become critical to enable the simultaneous transmission of large amounts of data in wireless networks, which may require a departure from the traditional orthogonal multiple access techniques such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), and orthogonal frequency division multiple access (OFDMA). These orthogonal schemes require orthogonality of the signals of the devices in the time domain, frequency domain, or code domain. Maintaining this orthogonality can be cumbersome, especially in high-density scenarios, as a large number of scheduling signals are required. The base station needs to send a grant as a scheduling signal to each of the multiple UEs to allocate radio resources to the UE. Signals can also be separated in the spatial domain, utilizing multiple input and multiple output (MIMO) and massive MIMO at the base station. The density of connected devices is bound to continue to increase, and with it, it is critical to adjust adequate multiple access schemes to cope with the requirements of 5G and MTC and IoT applications outside the network.

[0060] One approach to circumventing the limitations is non-orthogonal multiple access schemes, such as interleave-grid multiple access (IGMA) and interleave division multiple access (IDMA).

[0061] These schemes allow a large number of devices to transmit simultaneously without the need for orthogonal separation in the time, frequency, or spatial domain. Device-specific signatures and sophisticated receivers such as successive interference cancellation (SIC), parallel interference cancellation (PIC), message passing algorithm (MPA), and maximum likelihood (ML) are used to distinguish different data streams. 3GPP has studied uplink (UL) NOMA schemes in its 5G standardization work. Different NOMA schemes have been proposed, relying on various receivers and user-specific signatures. For example, the main principle of power domain NOMA lies in distinguishing users in the power domain and adopting a SIC receiver. IGMA uses a combination of user-specific interleaver and sparse mapping patterns to distinguish signals. IGMA adopts an elementary signal estimator (ESE) or maximum a posteriori (MAP) algorithm at the receiving end. In addition to the interleaver-based signature, IDMA also adopts an ESE receiver. Other proposed schemes include RSMA, MUSA, PDMA, and NCMA, etc.

[0062] Although there is a great possibility in the future, these schemes have a major drawback, namely receiver complexity, especially in the dense connection framework. In addition, some of these schemes require closed-loop control. In the case of UL power domain NOMA, a power difference is required so that the SIC receiver can distinguish the different data signals. The power difference of SIC can be achieved through closed-loop power control, which is not very practical in the dense scenario.

[0063] The present invention solves the power domain NOMA problem in CRAN. Utilizing the macro diversity of the CRAN, the disclosed method provides an efficient license-free uplink power domain NOMA scheme. To avoid the need for closed-loop control, the previously disclosed method uses the macro diversity of the CRAN to create the power difference required for the efficient operation of NOMA. Macro diversity is the spatial and power domain diversity associated with user equipment in a macro cell.

[0064] The fifth-generation (5G) wireless system is generally a cellular communication system in frequency range 2 (FR2), ranging from 24.25 GHz to 52.6 GHz, where multiple transmit (Tx) and receive (Rx) beams are used by a base station (BS) and / or a user equipment (UE) to cope with large path losses in the high-frequency band. Due to hardware limitations and costs, the BS and the UE may be equipped with only a limited number of transmission and reception units (TXRUs).

[0065] Referring to Figure 1 , a telecommunications system including a group 100a of multiple UEs, a base station (BS) 200a, and a network entity device 300 performs the disclosed method according to an embodiment of the present disclosure. The multiple UEs of the group 100a may include UE 10a, UE 10b, and other UEs. Figure 1 The representation of is for illustration only and not restrictive, and the system may include more user devices, base stations, and core network entities. The connections between devices and device components are shown as lines and arrows in the figure. The connections between devices may be implemented through wireless connections. The connections between device components may be implemented through cables, buses, traces, cables, or optical fibers. The UE 10a may include a processor 11a, a memory 12a, and a transceiver 13a. The UE 10b may include a processor 11b, a memory 12b, and a transceiver 13b. The base station 200a may include a baseband unit (BBU) 204a. The baseband unit 204a may include a processor 201a, a memory 202a, and a transceiver 203a. The network entity device 300 may include a processor 301, a memory 302, and a transceiver 303. Each of the processors 11a, 11b, 201a, and 301 may be configured to implement the described functions, processes, and / or methods. The layers of the radio interface protocol may be implemented in the processors 11a, 11b, 201a, and 301. Each of the memories 12a, 12b, 202a, and 302 stores various programs and information in terms of operation to operate the connected processors. The transceivers 13a, 13b, 203a, and 303 are operatively coupled to the connected processors to transmit and / or receive radio signals or wired signals. The UE 10a may communicate with the UE 10b through a sidelink. The base station 200a may be one of an eNB, a gNB, or other types of radio nodes.

[0066] Each of the processors 11a, 11b, 201a, and 301 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), other chip sets, logic circuits, and / or data processing devices. Each of the memories 12a, 12b, 202a, and 302 may include a read-only memory (ROM), a random access memory (RAM), a flash memory, a memory card, a storage medium, and / or other storage devices. Each of the transceivers 13a, 13b, 203a, and 303 may include a baseband circuit and a radio frequency (RF) circuit to process radio frequency signals. When the embodiments are implemented in software, the techniques herein may be implemented using modules, units, programs, functions, entities, etc. that perform the functions described herein. The modules may be stored in a memory and executed by the processor. The memory may be implemented inside the processor or external to the processor, and these memories may be communicatively coupled to the processor by various means known in the art.

[0067] The network entity device 300 may be a node in the CN. The CN may include an LTE CN or a 5G core (5GC), which includes a user plane function (UPF), a session management function (SMF), a mobility management function (AMF), a unified data management (UDM), a policy control function (PCF), a control plane (CP) / user plane (UP) separation (CUPS), an authentication server (AUSF), a network slice selection function (NSSF), and the network exposure function (NEF).

[0068] Refer to Figure 2, Base station 200b is an embodiment of the base station 200a, including a central controller (CC) 210, access points 211-1, 211-2, ... and 211-M. M is a positive integer. The central controller 210 can be implemented as a central unit (CU), and can include a BBU, such as BBU 204a, connected to the access points (AP) 211-1, 211-2, ... and 211-M. Each of the access points 211-1, 211-2, ... and 211-M can be implemented as integrated into a radio node, a remote unit (RU) or a remote radio head (RRH), and can include a transmission and reception point (TRP). The access points 211-1, 211-2, ... and 211-M may be located at different positions.

[0069] The central controller 210 receives wireless signals from a group of V user equipments (UEs) of group 100b through a set of M distributed radio nodes. V is a positive integer. The group of V user equipments includes user equipments 10-1, 10-2, 10-3 and... 10-V. The user equipments 10-1, 10-2, 10-3 and... 10-V may be located at different positions.

[0070] The technical problem considered belongs to the field of high-density connection and non-orthogonal multiple access (NOMA) in a CRAN system. For example, a CRAN network operating in time division duplex (TDD) mode, where channel estimation is performed through uplink pilot transmission.

[0071] Each coherence slot is separated between two uplink training instances, using orthogonal uplink pilots for uplink and downlink data transmission. An embodiment of the present disclosure deals with the uplink from V UEs to M single-antenna access points (APs). In each time slot, each AP independently performs uplink channel estimation.

[0072] The APs 211-1, 211-2, ... and 211-M are distributed within the coverage area and are managed by the central controller 210, which includes a centralized baseband unit (BBU) pool and processes operations of the physical layer and the media access control (MAC) layer, such as data decoding and encoding, scheduling, and power allocation. The APs are connected to the central controller 210 through a high-performance transmission link called the fronthaul. The fronthaul can be implemented through optical cables or high-bandwidth wireless channels. Figure 2 The system in Figure 2 includes the base station 200b and the UE, which is a simplified example of CRAN. The APs 211-1, 211-2, ... and 211-M perform channel estimation and the link-level transmission chain until equalization is achieved. The central controller 210 performs signal decoding, encoding, modulation, demodulation, scheduling, and MAC layer operations.

[0073] The present invention mainly includes two parts, namely, open-loop uplink power control based on power difference optimization and a new receiver scheme.

[0074] Open-loop uplink power control for NOMA in CRAN:

[0075] The steps of the open-loop uplink power control of the disclosed method are performed by the user equipment. Similarly, each user equipment 10-1, 10-2, 10-3, and... 10-V in the user equipment group can perform the open-loop uplink power control of the disclosed method. The user equipment may include MTC devices, but is not limited thereto. Each user equipment adjusts the transmission power so that the user equipment compensates for the path loss to the three APs under the best channel conditions. The resulting uplink transmission power can equivalently be derived from the uplink training signals of the user equipment 10-1, 10-2, 10-3, and... 10-V on the central controller 210.

[0076] Referring to Figure 3 , the non-orthogonal multiple access method is performed by the user equipment, such as user equipment 10a or user equipment 10b. The user equipment 10a and user equipment 10b are examples of the user equipment in the user equipment 10-1, 10-2, 10-3, and... 10-V. Similarly, each user equipment 10-1, 10-2, 10-3, and... 10-V in the user equipment group can perform Figure 3 the non-orthogonal multiple access method described in

[0077] The user equipment obtains power domain measurement values from the wireless signals of a group of distributed radio nodes (block 310). For example, the user equipment obtains a reference signal power value from the first radio node and obtains a reference signal power value from the second radio node and obtain a reference signal power value from a third radio node The subscript u indicates that the user equipment is user equipment u in the and The power domain measurement value of the wireless signal from the distributed radio node group includes the reference signal power value

[0078] The reference signal power value represents the power of the reference signal from the radio node. In the group of the AP211-1, 211-2,..., and 211-M, the first radio node, the second radio node, and the third radio node are three radio nodes with relatively strong signal strengths with respect to the user equipment u. Although the user equipment u obtains the reference signal power value from the three radio nodes in the example, the user equipment u can obtain the reference signal power value from two, three, or more radio nodes in the AP 211-1, 211-2,..., and 211-M and The user equipment obtains the power domain eigenvalue of the user equipment from the power domain measurement value (block 311). In an embodiment of the present disclosure, the power domain eigenvalue of the user is represented as ρ for the user equipment u

[0079] and is obtained from the following formula u :

[0080] and (1)

[0081]

[0082] where α u represents a priority-based coefficient, 0 ≤ α u ≤ 1;

[0083] is a power deviation used to control how the uplink transmission power changes as a function of the priority-based coefficient α u ;

[0084] ρ ULmax represents the maximum uplink power of the user equipment u. Therefore, the power domain eigenvalue of the user equipment is adjusted according to the priority of the user equipment

[0085] In an embodiment of the present disclosure, the where and α uThe asterisk "*" between them is the multiplication operator. The user equipment transmits the power domain eigenvalue for a multiple access procedure associated with the user equipment (block 312). In the disclosed embodiments, the user equipment transmits the power domain eigenvalue to the APs 211-1, 211-2, ..., and 211-M.

[0086] The first part of the present invention focuses on the uplink power control, which is particularly important in power domain NOMA applications. The present invention proposes an open-loop uplink power control based on three-dimensional power domain triangulation. Although the user equipment obtains reference signal power values from three radio nodes in the example, the user equipment may obtain the reference signal power values from two radio nodes, four radio nodes, or multiple radio nodes among the AP radio nodes 211-1, 211-2, ..., and 211-M, and obtain and transmit the power domain eigenvalue from the reference signal power values.

[0087] Based on the finally obtained power, i.e., the power domain eigenvalues of the user equipments 10-1, 10-2, 10-3, and... 10-V, the central controller 210 derives the detection weights to be used in the reception. The detection weights may be referred to as weighted channel gains. In addition to using maximum ratio combining (MRC), the central controller 210 also employs device-specific weighted vectors received on all APs and applies them to the wireless signals of the user equipments 10-1, 10-2, 10-3, and... 10-V. These device- and AP-specific weights are applied to the received encoded data represented by the wireless signals of the user equipments 10-1, 10-2, 10-3, and... 10-V. For each user equipment, the weights are derived to maximize the power difference relative to the interference, thereby improving the SINR during decoding and minimizing interference cancellation. In fact, for each device, the weights are used to determine the priority of the APs to improve the decoding conditions.

[0088] The proposed power control aims to ensure the power difference on the transmission side when necessary and enable unauthorized access. Since the power domain multiple access depends on power allocation, in some embodiments of the present disclosure, more power may be allocated to user equipments with high priority or low link reliability.

[0089] Each of the user equipments 10-1, 10-2, 10-3, and... 10-V listens to the reference signals (RS) of the three strongest APs and measures the RS power received from each AP, represented by and The user equipment u obtains the vector These measured values are then calculated by the user equipment u according to the formula (1) as the modulus of its measurement vector.

[0090] The uplink transmission power ρ of each user equipment among the user equipments 10-1, 10-2, 10-3,... 10-V u is calculated in dBm according to the formula (2).

[0091] Here 0 ≤ α u ≤ 1 represents a truth-based or priority-based coefficient. It can be set in steps of 0.1 from 0.0 to 1.0. is a power deviation used to control how the uplink transmission power changes as a function of the priority / reliability coefficient. In a specific case, the function is defined as The constant ρ ULmax is the maximum uplink power. and the asterisk "*" between α u is the standard multiplication operator.

[0092] This power control ensures that the transmission powers used by user equipments in closer geographical locations differ only as a function of their priority / reliability (P / R) coefficients. This means that user equipments in close proximity with similar priority / reliability metrics may use approximately the same uplink transmission power. This results in a fair distribution of throughput when using NOMA at the receiving end. On the other hand, if a user equipment characterized by a higher priority or lower reliability may use higher power, thus increasing the throughput when using NOMA for that specific user equipment. The impact of the proposed power control is as Figure 5 shown.

[0093] If the priority / reliability coefficient cannot be obtained, the user equipments 10-1, 10-2, 10-3,... 10-V can adopt a randomly generated power deviation. The user equipments 10-1, 10-2, 10-3,... 10-V create a power difference among user equipments in closer proximity without an actual metric to distinguish their traffic.

[0094] Optimizing the receiver for power-domain NOMA in CRAN:

[0095] One embodiment of the invention enables non-orthogonal access to a large number of MTC devices while using a reduced-complexity receiver that exploits the inherent macro-diversity described in CRAN. One of the main drawbacks of NOMA is the complexity of the receiver. SIC receivers are commonly used for power-domain NOMA. This receiver also has another key drawback, namely error propagation.

[0096] One embodiment of the invention addresses the problem by exploiting macro-diversity in a CRAN system to enable simple linear detection and, where possible, reduce interference cancellation iterations.

[0097] Reference Figure 4, a non-orthogonal multiple access method is executed in the central controller 210 of the base station 200b. The central controller 210 receives the wireless signals of the group of V user equipments (block 410) through the set of M distributed radio nodes (including APs 211-1, 211-2,..., and 211-M). The V user equipments may include the user equipments 10-1, 10-2, 10-3,..., and 10-V. The central controller 210 estimates the signal quality of each user equipment in the group of V user equipments (block 411), and classifies the group of V user equipments into a high signal quality subgroup and a low signal quality subgroup according to the estimated signal quality of each user equipment in the group of V user equipments (block 412). The signal quality of a user equipment in the group of V user equipments is obtained from the power domain eigenvalue of the user equipment u, and the power domain eigenvalue is determined based on the macro diversity associated with the user equipment u. In one embodiment, the signal quality may include signal-to-interference-plus-noise ratio (SINR), and the classification is based on the SINR threshold. Alternatively, the signal quality may include one of signal to noise ratio (SNR), reference signal receiving power (RSRP), reference signal received quality (RSRQ), radio link quality (RLQ), received signal strength indication (RSSI), or channel quality indicator (CQI). In one embodiment, when a user equipment in the group of V user equipments is in the classification process, the central controller 210 classifies the user equipment being processed into the high signal quality subgroup when the signal quality of the user equipment being processed is greater than the signal quality threshold, and classifies the user equipment being processed into the low signal quality subgroup when the signal quality of the user equipment is not greater than the signal quality threshold. Alternatively, when a user equipment in the group of V user equipments is in the classification process, the central controller 210 classifies the user equipment being processed into the high signal quality subgroup when the signal quality of the user equipment being processed is not less than the signal quality threshold, and classifies the user equipment being processed into the low signal quality subgroup when the signal quality of the user equipment is less than the signal quality threshold.

[0098] The central controller 210 decodes the wireless signals of the user equipments belonging to the low signal quality subgroup using a multi-user interference cancellation scheme (block 413), and decodes the wireless signals of the user equipments belonging to the high signal quality subgroup without using the multi-user interference cancellation scheme (block 414). The multi-user interference cancellation scheme may include one of successive interference cancellation (SIC) or parallel interference cancellation (PIC) schemes.

[0099] The central controller 210 may obtain the detection weights of each of the V user equipments in the group, and cluster the user equipments in the low signal quality subgroup into clusters according to the detection weights of each user equipment in the low signal quality subgroup. K-means clustering may be used to perform the clustering. The central controller 210 may decode the wireless signal of a specific user equipment belonging to the low signal quality subgroup by subtracting the wireless signals of one or more other user equipments in the same cluster as the specific user equipment.

[0100] In one embodiment of the present invention, the central controller 210 further generates a power difference between different user equipment signals at the receiving end through weighted coherent detection of the antennas of the plurality of APs. The weights associated with the user equipments 10-1, 10-2, 10-3 and... 10-V are generated from graph-based optimization to increase the distance between the user equipments 10-1, 10-2, 10-3 and... 10-V in the power domain.

[0101] The central controller 210 may still use SIC as an uplink receiver, such as the transceiver 203a and the processor 201a in the BBU 204a. In addition to performance improvement, the central controller 210 applies different detection weights to the user equipments for non-orthogonal multiple access to reduce SIC iterations. This is because after applying the detection weights on the APs, the distance between the user equipments in the power domain is increased.

[0102] In some cases where many user equipments are very close, SIC is still required. By utilizing the uplink power control proposed above, the achievable rate of each user equipment using the SIC receiver depends on the power deviation of the user equipment, which is based on the priority or link reliability of the user equipment. Therefore, even with the open-loop power control and license-free access of the disclosed method, the network can schedule user equipments in the power domain with enhanced fairness.

[0103] As described above, user equipment v is associated with a weight vector γ v =[γ v1 ,…,γ vMis associated, 0 ≤ γ vm ≤ 1, Similarly, the user equipment u is associated with the weight vector γ u = [γ u1 , …, γ uM , 0 ≤ γ um ≤ 1, where the variable m is an index representing one of the APs in the group of APs 211-1, 211-2, ..., and 211-M. 0 ≤ m ≤ M. The variables u and v are used as two user equipment indices. v is a variable representing the index of the user equipment v in the group of V user equipment, and the weight γ vm represents the importance value of the AP m in detecting the wireless signal from the user equipment v. u is a variable representing the index of the user equipment u in the group of V user equipment, and the weight γ um represents the importance value of the radio node m in detecting the wireless signal from the user equipment u when detecting the wireless signal from the user equipment u. The user equipment is different from the user equipment v.

[0104] The central controller 210 uses the weight vector to detect the wireless signals of the user equipment 10-1, 10-2, 10-3, and... 10-V. The weight vector is derived using a power domain optimization framework. The central controller 210 uses these weights at the receiver to increase the power difference between the wireless signal and interference for each user equipment. These weights can be interpreted as projections in the power domain. Therefore, the wireless signals from each user equipment are detected in the power domain subspace, where the user equipment achieves the best power difference with other interfering user equipment.

[0105] Since power domain NOMA depends on the differences of user equipment in the power domain, the power difference between user equipment will be maximized. Since the network, such as the base station 200b, does not intervene in the power control, increasing the power difference will be completed in the central controller 210 by weighted coherent detection at the receiving end.

[0106] The power domain optimization includes a density minimization problem, which can be described as follows:

[0107]

[0108] Subject to 0 ≤ γ um ≤ 1, (3)

[0110]

[0111] Wherein, v is a variable representing the index of the user equipment v among the group of V user equipments;

[0112] is the estimated channel coefficient between the user equipment u and the radio node m;

[0113] is the estimated channel coefficient between the user equipment v and the radio node m;

[0114] ‖‖ is the Euclidian Norm;

[0115] θ u is the signal quality threshold of the user equipment u;

[0116]

[0117] ρ ULmax represents the maximum uplink power of the user equipment u;

[0118] for the reference signal power value from the first radio node the reference signal power value from the second radio node and the reference signal power value from the third radio node

[0119] α u represents a priority-based coefficient, 0 ≤ α u ≤ 1; and

[0120] is a power deviation for controlling how the uplink transmit power varies as a function of the priority-based coefficient α u of;

[0121]

[0122] ρ ULmax represents the maximum uplink power of the user equipment v;

[0123] for the reference signal power value from the first radio node the reference signal power value from the second radio node and the reference signal power value from the third radio node

[0124] α v represents a priority-based coefficient, 0 ≤ α v ≤ 1; and

[0125] is a power deviation for controlling how the uplink transmit power varies as a function of the priority-based coefficient α v .

[0126] The central controller 210 determines the detection weight of the user equipment u based on the density minimization problem.

[0127] At the receiving end, the central controller 210 uses the derived weights to characterize the importance of each AP in detecting the wireless signal from the user equipment. The uplink wireless signal received by APm from the user equipment u is given by:[[]]

[0128]

[0129] where g um is the channel coefficient between the user equipment u and the APm; N m is the noise power; x u is the wireless signal transmitted from the user equipment u; and V is the set of V user equipments. To detect the signal of user u, the central processing unit applies the optimized detection weights in addition to conjugate beamforming at each AP.

[0130] Although the proposed power control can distinguish between closely located user equipments according to the traffic priority or link reliability of the user equipment, a low power domain distance may still occur between user equipments. This leads to the need to eliminate interference. However, not all user equipments perform SIC because the detection weights can contribute to the required power difference. Therefore, SIC is triggered only under conditions related to the low power domain distance of the user equipment, which is characterized by a lower bound of the achievable average SINR.

[0131] Figure 6 shows an embodiment of the disclosed NOMA method. Referring to Figure 6 , multiple user equipments modulate the transmit power according to the disclosed triangulation power control (block 510). The central controller 210 derives the detection weights for each of the user equipments 10-1, 10-2, 10-3… and 10-V (block 511).

[0132] The central controller 210 estimates the SINR of each user equipment after applying weighted maximum ratio combining (MRC), and forms a set of user equipments Δ called the high signal quality subgroup, and another set of user equipments called (Block 512). For example, the central controller 210 calculates the estimated SINR of the user equipment v ∈ V after the weighted MRC (SINR v ), denoted as SINR v . If SINR v ≥θ, the user equipment v is added to the set Δ representing the high signal quality subgroup, and if SINR v <θ, the user equipment v is added to the set representing the low signal quality subgroup . That is, multiple user equipments in the set Δ have SINR v ≥θ, where θ is the SINR threshold required to correctly decode the signal. The user equipments that do not verify the SINR lower bound criterion are assigned to the set Multiple user equipments in the set have SINR v <θ.

[0133] The central controller 210 decodes the wireless signals of multiple user equipments in the high signal quality subgroup without interference cancellation (Block 513). When decoding the signals of all user equipments in the high signal quality subgroup Δ, the central controller 210 takes a specific user equipment in the set Δ as the user equipment v, and obtains the decoded signal from the wireless signal of the user equipment v according to the following formula

[0134]

[0135] where the detection weight γ vm represents the importance value of the radio node m relative to the user equipment v in detecting the wireless signal from the user equipment v; and

[0136] is the estimated channel coefficient between the user equipment and the radio node m of v.

[0137] The central controller 210 iterates the step by taking another user equipment v in the set Δ as the user equipment.

[0138] The central controller 210 clusters multiple user equipments in the low signal quality subgroup into clusters according to the detection weights of the MTC devices (Block 514). The central controller 210 takes a user equipment in the set as the user equipment v, and according to the detection weight γ v =[γ v1 , …, γ vM , 0 ≤ γ vm ≤ 1, Cluster the user equipment v in the set and iterate the step by using another user equipment in the set as the user equipment v, so as to cluster multiple user equipments in the set into L clusters. L is a positive integer. In this step, K-mean can be used for clustering.

[0139] The central controller 210 decodes the radio signals of the multiple user equipments in the low signal quality subgroup by using interference cancellation of the clusters based on detection weights (block 515). For each user equipment in, before decoding the radio signal of the user equipment, the central controller 210 applies SIC by subtracting the radio signals of the user equipments in the same cluster. When detecting the signal of the user equipment in the k-th cluster C k the central controller 210 arranges the multiple user equipments according to the weights of the multiple user equipments. Among the multiple user equipments arranged in the k-th cluster C k for the radio signal in a given user equipment v with a position at rank (i), the radio signal of other user equipments is subtracted for decoding to generate the decoded signal of the user equipment v

[0140]

[0141] where Δ represents the high signal quality subgroup;

[0142] g wm is the channel coefficient between the user equipment w and the radio node m;

[0143] w is a user equipment index, indicating the user equipment w belonging to the set ; and

[0144] is the radio signal transmitted from the user equipment w.

[0145] Rank (i) refers to the rank of a user equipment among the arranged multiple user equipments. The central controller 210 iterates the step by using another user equipment in the k-th cluster C in the set as the user equipment v. k

[0146] Figure 7 ​Displays the results of the numerical simulation, which show the gain that the proposed invention can provide. The simulation compares the performance of a traditional SIC receiver and the non-orthogonal multiple access receiver of the disclosed power domain NOMA. The simulation utilizes a distributed antenna system comprising 40 single-antenna access points that serve 4 user equipments or mobile stations (MS) sharing the same time-frequency resources. The multiple APs and multiple user equipments are distributed within a disk with a radius of 100m. The proposed uplink power control employs randomly generated power offsets

[0147] Figure 7 Displays the average bit error rate achievable by multiple user equipments as a function of their decoding rank, with a comparison for only two active user equipments. A significant improvement in the bit error rate can be obtained using the present disclosure. This gain comes from the optimized receiver that exploits the macro diversity of the distributed antenna system. The proposed receiver applies AP- and user-specific weights to enhance the power difference between interference and useful signals.

[0148] Figure 8 Displays a comparison of the average bit error rate achievable by multiple user equipments as a function of their decoding rank when all user equipments are active. Again, a significant improvement in the bit error rate can be obtained using the present disclosure. Although the overall error rate deteriorates due to the increased connection density, the invention can effectively cope with higher interference.

[0149] Figure 9 Is a block diagram of an example system 700 for wireless communication according to one embodiment of the present disclosure. The embodiments described herein can be implemented into the system using any appropriately configured hardware and / or software. Figure 9 Illustrates that the system 700 includes a radio frequency (RF) circuit 710, a baseband circuit 720, a processing unit 730, a memory / storage 740, a display 750, a camera 760, sensors 770, and an input / output (I / O) interface 780, coupled to each other as shown. The processing unit 730 can include a circuit, for example, but not limited to, one or more single-core or multi-core processors. The processor can include any combination of a general-purpose processor and a dedicated processor, such as a graphics processor, an application processor. The processor is coupled to the memory / storage and is configured to execute instructions stored in the memory / storage to enable various applications and / or operating systems to run on the system.

[0150] The baseband circuit 720 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The processor may include a baseband processor. The baseband circuit may handle various radio control functions to enable communication with one or more radio networks via the radio frequency circuit. The radio control functions may include, but are not limited to, signal modulation, encoding, decoding, radio frequency shifting, etc. In some embodiments, the baseband circuit may provide communication compatible with one or more radio technologies. For example, in some embodiments, the baseband circuit may support communication with 5G NR, LTE, evolved universal terrestrial radio access network (EUTRAN), and / or other wireless metropolitan area network (WMAN), wireless local area network (WLAN), wireless personal area network (WPAN). Embodiments in which the baseband circuit is configured to support radio communication of more than one wireless protocol may be referred to as multi-mode baseband circuits.

[0151] In various embodiments, the baseband circuit 720 may include circuitry that operates with signals that are not strictly regarded as baseband frequencies. For example, in some embodiments, the baseband circuit may include circuitry that operates with signals having an intermediate frequency that is between the baseband frequency and the radio frequency. The radio frequency circuit 710 may implement communication with a wireless network using modulated electromagnetic radiation through a non-solid medium. In various embodiments, the radio frequency circuit may include switches, filters, amplifiers, etc. to facilitate communication with a wireless network. In various embodiments, the radio frequency circuit 710 may include circuitry for operating with signals that are not strictly considered to be at radio frequencies. For example, in some embodiments, the radio frequency circuit may include circuitry that operates with signals having an intermediate frequency that is between the baseband frequency and the radio frequency.

[0152] In various embodiments, the transmitter circuitry, control circuitry, or receiver circuitry of the user equipment (UE), eNB, or gNB discussed above may be embodied, in whole or in part, in one or more of a radio frequency circuit, a baseband circuit, and / or a processing unit. As used herein, "circuitry" may refer to, be part of, or include an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group), and / or a memory (shared, dedicated, or group), a combinational logic circuit, and / or other suitable hardware components that execute one or more software or firmware programs to provide the described functionality. In some embodiments, the electronic device circuitry may be implemented in one or more software or firmware modules, or functions associated with the circuitry may be implemented by one or more software or firmware modules. In some embodiments, some or all of the constituent components of the baseband circuit, the processing unit, and / or the memory / storage may be implemented together on a system on a chip (SOC). The memory / storage 740 may be used to load and store, for example, data and / or instructions for the system. The memory / storage of one embodiment may include any combination of suitable volatile memory (e.g., dynamic random access memory (DRAM)) and / or non-volatile memory (e.g., flash memory).

[0153] In various embodiments, the I / O interface 780 may include one or more user interfaces designed to enable a user to interact with the system and / or peripheral component interfaces designed to enable peripheral components to interact with the system. User interfaces may include, but are not limited to, a physical keyboard or keypad, a touchpad, speakers, a microphone, etc. Peripheral component interfaces may include, but are not limited to, non-volatile memory ports, universal serial bus (USB) ports, audio jacks, and power interfaces. In various embodiments, the sensor 770 may include one or more sensing devices to determine environmental conditions and / or location information related to the system. In some embodiments, the sensor may include, but is not limited to, a gyroscope sensor, an accelerometer, a proximity sensor, an ambient light sensor, and a positioning unit. The positioning unit may also be part of or interact with the baseband circuitry system and / or the RF circuitry system to communicate with a positioning network (e.g., global positioning system (GPS) satellites).

[0154] In various embodiments, the display 750 may include a display, such as a liquid crystal display and a touch screen display. In various embodiments, the system 700 may be a mobile computing device, such as, but not limited to, a laptop computer device, a tablet computer device, a netbook, an ultrabook, a smart phone, etc. In various embodiments, the system may have more or fewer components and / or a different architecture. In appropriate cases, the methods described herein may be implemented as a computer program. The computer program may be stored on a storage medium, such as a non-transitory storage medium.

[0155] Embodiments of the present disclosure are combinations of technologies / processes that can be adopted in 3GPP specifications to create a final product.

[0156] Those of ordinary skill in the art understand that each unit, algorithm, and step described and disclosed in the embodiments of the present disclosure is implemented using electronic hardware or a combination of software of a computer and electronic hardware. Whether these functions run in hardware or software depends on the application conditions and design requirements of the technical solution. Those of ordinary skill in the art can use different ways to implement the functions of each specific application, and such implementation methods should not exceed the scope of the present disclosure. Those of ordinary skill in the art can understand that since the working procedures of the above-mentioned systems, devices, and units are basically the same, the working procedures of the systems, devices, and units in the above-mentioned embodiments can be referred to. For the sake of convenience of description and simplification, these working procedures will not be described in detail.

[0157] It can be understood that the systems, devices, and methods disclosed in the embodiments of the present invention can be implemented in other ways. The embodiments are merely illustrative examples. The division of the mentioned units is only based on the division of logical functions, and there may be other division methods when implementing. It is possible that multiple units or elements are combined or integrated into another system. It is also possible that some features are omitted or skipped. On the other hand, the above-mentioned mutual coupling, direct coupling, or communication coupling is realized through some ports, devices, or units, whether indirectly or through communication in the form of electronics, mechanics, or other types.

[0158] The units mentioned above as separation elements for explanation may or may not be physically separated elements. The units mentioned above may or may not be physical units, that is, they may be set in one place or distributed on multiple network units. Some or all of the units may be used according to the purpose of the embodiment. In addition, each functional unit in each embodiment may be integrated into a processing unit, or physically independent, or integrated into a processing unit having two or more units.

[0159] If it is implemented in the form of software functional units and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution proposed by the present disclosure is essentially or partially implemented in the form of a software product. Or rather, a part of the technical solution beneficial to the prior art can be implemented in the form of a software product. The software product in the computer is stored in the storage medium and includes multiple instructions for a computing device (such as a personal computer, server, or network device) to execute all or part of the steps disclosed in the embodiments of the present disclosure. The storage medium includes a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a floppy disk, or other types of media capable of storing program codes.

[0160] The disclosed NOMA method mainly includes two parts, namely, open-loop uplink power control based on power difference optimization and a new receiver scheme.

[0161] The present invention solves the power-domain NOMA problem in CRAN. Utilizing the macro diversity of the CRAN, the disclosed method provides an efficient license-free uplink power-domain NOMA scheme. To avoid the need for closed-loop control, the previously disclosed method uses the macro diversity of the CRAN to create the power difference required for the efficient operation of NOMA. Macro diversity is the spatial and power-domain diversity associated with user equipment in a macro cell.

[0162] Although the present disclosure has been described in connection with the most practical and preferred embodiments, it should be understood that the present disclosure is not limited to the above-disclosed embodiments, but is intended to cover various combinations made without departing from the broadest scope of interpretation of the appended claims.

Claims

1. A non-orthogonal multiple access (NOMA) method, which can be executed in the central controller of a base station. Characterized in that, Comprising: Receiving wireless signals of a group of V user equipments (UEs) through a group of M distributed radio nodes, where V and M are positive integers; Estimating the signal quality of each user equipment in the group of V user equipments; Classifying the group of V user equipments into a high signal quality subgroup and a low signal quality subgroup according to the estimated signal quality of each user equipment in the group of V user equipments; And Using a multi-user interference cancellation scheme to decode the wireless signals of the user equipments belonging to the low signal quality subgroup; And Decoding the wireless signals of the user equipments belonging to the high signal quality subgroup without using the multi-user interference cancellation scheme; Wherein, the method further comprises: Obtaining the detection weight of each user equipment in the group of V user equipments; Clustering the user equipments in the low signal quality subgroup into multiple clusters according to the detection weights of each user equipment in the low signal quality subgroup; and Decoding the wireless signals of the specific user equipment belonging to the cluster in the low signal quality subgroup by subtracting the wireless signals of one or more other user equipments in the same cluster as the specific user equipment.

2. The non-orthogonal multiple access method according to claim 1, Characterized in that, The signal quality of a user equipment u in the group of V user equipments is obtained from the power domain eigenvalue of the user equipment u, and the power domain eigenvalue is determined according to the macro diversity associated with the user equipment u.

3. The non-orthogonal multiple access method according to claim 1, Characterized in that, The signal quality includes signal to interference plus noise ratio (SINR), and the classification is a classification based on the SINR threshold.

4. The non-orthogonal multiple access method according to claim 1, Characterized in that, The multi-user interference cancellation scheme includes successive interference cancellation (SIC).

5. The non-orthogonal multiple access method according to claim 1, Characterized in that, When processing a user equipment in the group of V user equipments in the classification, the method further comprises: When the signal quality of the user equipment is not lower than the signal quality threshold, classifying the processed user equipment into the high signal quality subgroup; and When the signal quality of the user equipment is lower than the signal quality threshold, classifying the processed user equipment into the low signal quality subgroup.

6. The non-orthogonal multiple access method according to claim 1, Characterized in that, The clustering is a clustering using k-means clustering.

7. The non-orthogonal multiple access method according to claim 1, Characterized in that, The detection weight of a user equipment u among the group of V user equipments includes a weight vector γ u = [γ u1 , …, γ uM , 0 ≤ γ um ≤ 1, m is a variable representing the index of a radio node among the group of M distributed radio nodes, 0 ≤ m ≤ M, u is a variable representing the index of a user equipment u among the group of V user equipments, and the weight γ um represents the importance value of radio node m relative to the user equipment u in detecting a wireless signal from the user equipment u.

8. The non-orthogonal multiple access method according to claim 7, It is characterized in that the detection weight of the user equipment u is determined based on the following density minimization problem: Constrained by and where v is a variable representing the index of the user equipment v in the group of V user equipments; is the estimated channel coefficient between the user equipment u and the radio node m; is the estimated channel coefficient between the user equipment v and the radio node m; ‖‖ is the Euclidean Norm; θ u is the signal quality threshold of the user equipment u; ρ ULmax represents the maximum uplink power of the user equipment u; Reference signal power value from a first radio node Reference signal power value from a second radio node and reference signal power value from a third radio node α u represents a priority-based coefficient, where 0 ≤ α u ≤ 1; and is a power deviation for controlling how the uplink transmit power varies as a function of the priority-based coefficient α u ; ρ ULmax represents the maximum uplink power of the user equipment v; Reference signal power value from the first radio node Reference signal power value from the second radio node And reference signal power value from the third radio node α v represents a priority-based coefficient, where 0 ≤ α v ≤ 1; and is a power deviation for controlling how the uplink transmit power varies as a function of the priority-based coefficient α v as described above.

9. The non-orthogonal multiple access method according to claim 8, It is characterized in that the radio signal of the signal from the user equipment u received from the radio node m is obtained by the following method: where g um is the channel coefficient between the user equipment u and the radio node m; N m is the noise power; x u is a wireless signal transmitted from the user equipment u; and V is the group of V user equipments.

10. The non-orthogonal multiple access method according to claim 9, It is characterized in that further comprising: decoding the radio signal of a specific user equipment belonging to the high signal quality subgroup to generate a decoded signal: Among them, the detection weight γ vm represents the importance value of the radio node m relative to the user equipment v in detecting the wireless signal from the user equipment v; and is the estimated channel coefficient between the user equipment and the radio node m as described above.

11. The non-orthogonal multiple access method according to claim 10, It is characterized in that further comprising: Decode the wireless signals of multiple user devices in the k-th cluster C among the multiple clusters k wherein the multiple user devices in the k-th cluster C k are arranged according to the detection weights of the multiple user devices, and the wireless signal of a given user device v with rank v(i) among the multiple user devices arranged in the k-th cluster C k is decoded by subtracting the wireless signals of other user devices to generate the decoded signal of the user device v where Δ represents the high signal quality subgroup; g wm is the channel coefficient between the user equipment w and the radio node m; w is a user equipment index, indicating the user equipment w belonging to the set ; and is a wireless signal transmitted from the user equipment w.

12. A base station, It is characterized in that comprising: a transceiver; and a processor, connected to the transceiver and configured to perform the following steps, including: receiving radio signals from a group of V user equipments (UE) through a group of M distributed radio nodes, where V and M are positive integers; estimating the signal quality of each user equipment in the group of V user equipments; classifying the group of V user equipments into a high signal quality subgroup and a low signal quality subgroup according to the estimated signal quality of each user equipment in the group of V user equipments; and decoding the radio signals of the user equipments belonging to the low signal quality subgroup using a multi-user interference cancellation scheme; and decoding the radio signals of the user equipments belonging to the high signal quality subgroup without using the multi-user interference cancellation scheme; wherein, the steps further include: obtaining the detection weight of each user equipment in the group of V user equipments; clustering the user equipments in the low signal quality subgroup into multiple clusters according to the detection weight of each user equipment in the low signal quality subgroup; and decoding the radio signal of the specific user equipment belonging to the cluster in the low signal quality subgroup by subtracting the radio signals of one or more other user equipments in the same cluster as a specific user equipment.

13. The base station according to claim 12, It is characterized in that the signal quality of a user equipment u in the group of V user equipments is obtained from the power domain eigenvalue of the user equipment u, and the power domain eigenvalue is determined according to the macro diversity associated with the user equipment u.

14. The base station according to claim 12, It is characterized in that the signal quality includes the signal to interference-plus-noise ratio (SINR), and the classification is a classification based on the SINR threshold.

15. The base station according to claim 12, It is characterized in that the multi-user interference cancellation scheme includes successive interference cancellation (SIC).

16. The base station according to claim 12, wherein, when processing one user equipment among the group of V user equipments in the classification, the processor further performs: when the signal quality of the user equipment is not lower than the signal quality threshold, classifying the user equipment being processed into the high signal quality subgroup; and when the signal quality of the user equipment is lower than the signal quality threshold, classifying the user equipment being processed into the low signal quality subgroup.

17. The base station according to claim 12, wherein, the clustering is performed using k - means clustering.

18. The base station according to claim 12, wherein, The detection weight of a user equipment u among the V user equipments in the group includes a weight vector γ u = [γ u1 , …, γ uM , 0 ≤ γ um ≤ 1, m is a variable representing the index of a radio node among the M distributed radio nodes in the group, 0 ≤ m ≤ M, u is a variable representing the index of a user equipment u among the V user equipments in the group, and the weight γ um represents the importance value of the radio node m relative to the user equipment u when detecting a wireless signal from the user equipment u.

19. The base station according to claim 12, wherein, the detection weight of the user equipment u is determined based on the following density minimization problem: Constrained by and where v is a variable representing the index of the user equipment v among the group of V user equipments; is the estimated channel coefficient between the user equipment u and the radio node m; is the estimated channel coefficient between the user equipment v and the radio node m; ‖‖ is the Euclidian Norm; θ u is the signal quality threshold of the user equipment u; ρ UL max represents the maximum uplink power of the user equipment u; Reference signal power value from a first radio node Reference signal power value from a second radio node And reference signal power value from a third radio node α u represents a priority-based coefficient, where 0 ≤ α u ≤ 1; and is a power deviation used to control how the uplink transmission power varies as a function of the priority-based coefficient α u ; ρ UL max represents the maximum uplink power of the user equipment v; Reference signal power value from the first radio node Reference signal power value from the second radio node And reference signal power value from the third radio node α v represents a priority-based coefficient, where 0 ≤ α v ≤ 1; and is a power deviation that controls how the uplink transmit power varies as a function of the priority-based coefficient α v as described above.

20. The base station according to claim 19, wherein, the radio signal of the user equipment u received from the radio node m is obtained by the following method: where g um is the channel coefficient between the user equipment u and the radio node m; N m is the noise power; x u is a wireless signal transmitted from the user equipment u; and V is the group of V user equipments.

21. The base station according to claim 20, wherein, the processor further performs: decoding the radio signal of a specific user equipment belonging to the high signal quality subgroup to generate a decoded signal: wherein, the detection weight γ vm represents an importance value of the radio node m with respect to the user equipment v in detecting a radio signal from the user equipment v; and is the estimated channel coefficient between the user equipment and the radio node m.

22. The base station according to claim 21, wherein, the processor further performs: Decode the wireless signals of multiple user equipments in the k-th cluster C among the multiple clusters k wherein the multiple user equipments in the k-th cluster C k are arranged according to the detection weights of the multiple user equipments, and the wireless signal of a given user equipment v with rank v(i) among the multiple user equipments arranged in the k-th cluster C k is decoded by subtracting the wireless signals of other user equipments to generate the decoded signal of the user equipment v where Δ represents the high signal quality subgroup; g wm is the channel coefficient between the user equipment w and the radio node m; w is a user equipment index, representing the user equipment w belonging to the set ; and is a wireless signal transmitted from the user device w.

23. A chip, wherein, comprising: a processor configured to call and run a computer program stored in a memory, so that a device installed with the chip executes the method according to any one of claims 1 to 11.

24. A computer - readable storage medium storing a computer program, wherein, the computer program causes a computer to execute the method according to any one of claims 1 to 11.

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