As a promising physical layer technique, nonorthogonal multiple access(NOMA) can admit multiple users over the same space-time resource block, and thus improve the spectral efficiency and increase the number of access...As a promising physical layer technique, nonorthogonal multiple access(NOMA) can admit multiple users over the same space-time resource block, and thus improve the spectral efficiency and increase the number of access users. Specifically, NOMA provides a feasible solution to massive Internet of Things(IoT) in 5G and beyond-5G wireless networks over a limited radio spectrum. However, severe co-channel interference and high implementation complexity hinder its application in practical systems. To solve these problems, multiple-antenna techniques have been widely used in NOMA systems by exploiting the benefits of spatial degrees of freedom. This study provides a comprehensive review of various multiple-antenna techniques in NOMA systems, with an emphasis on spatial interference cancellation and complexity reduction. In particular, we provide a detailed investigation on multiple-antenna techniques in two-user, multiuser, massive connectivity, and heterogeneous NOMA systems.Finally, future research directions and challenges are identified.展开更多
The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the c...The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the current 5G networks have not achieved the promised 5G goals, including the projected 2000 times EE improvement over the legacy 4G Long Term Evolution (LTE) networks. This paper provides a comprehensive survey of Artificial Intelligence (AI)-enabled MA techniques, emphasizing their roles in Spectrum Sensing (SS), Dynamic Resource Allocation (DRA), user scheduling, interference mitigation, and protocol adaptation. In particular, we systematically analyze the progression of traditional and modern MA schemes, from Orthogonal Multiple Access (OMA)-based approaches like Time Division Multiple Access (TDMA) and Frequency Division Multiple Access (FDMA) to advanced Non-Orthogonal Multiple Access (NOMA) methods, including power domain-NOMA, Sparse Code Multiple Access (SCMA), and Rate Splitting Multiple Access (RSMA). The study further categorizes AI techniques—such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Federated Learning (FL), and Explainable AI (XAI)—and maps them to practical challenges in Dynamic Spectrum Management (DSM), protocol optimization, and real-time distributed decision-making. Optimization strategies, including metaheuristics and multi-agent learning frameworks, are reviewed to illustrate the potential of AI in enhancing energy efficiency, system responsiveness, and cross-layer RA. Additionally, the review addresses security, privacy, and trust concerns, highlighting solutions like privacy-preserving ML, FL, and XAI in 6G and beyond. By identifying research gaps, challenges, and future directions, this work offers a structured resource for researchers and practitioners aiming to integrate AI into 6G MA systems for intelligent, scalable, and secure wireless communications.展开更多
Although Successive Interference Cancellation(SIC)decoding is widely adopted in Nonorthogonal Multiple Access(NOMA)schemes for the recovery of user data at acceptable complexity,the imperfect SIC would cause Error Pro...Although Successive Interference Cancellation(SIC)decoding is widely adopted in Nonorthogonal Multiple Access(NOMA)schemes for the recovery of user data at acceptable complexity,the imperfect SIC would cause Error Propagation(EP),which can severely degrade system performance.In this work,we propose an SIC-free NOMA scheme in pulse modulation based Visible Light Communication(VLC)downlinks,including two types of users with different data rate requirements.Low bit-rate users adopt on-off keying,whereas high bit-rate ones use Multiple Pulse Position Modulation(MPPM).The soft decision decoding scheme is exploited by high bit-rate users to decode MPPM signals,which could fundamentally eliminate the detrimental effect of EP;the scheme is also easier and faster to execute compared with the conventional SIC decoding scheme.Expressions of the symbol error rate and achievable data rate for two types of users are derived.Results of the Monte Carlo simulation are provided to confirm the correctness of theoretical results.展开更多
Non-orthogonal multiple access(NOMA)is considered as one of the key technologies for the fifth generation(5G)wireless communications.The integration of NOMA and device-to-device(D2D)communications has recently attract...Non-orthogonal multiple access(NOMA)is considered as one of the key technologies for the fifth generation(5G)wireless communications.The integration of NOMA and device-to-device(D2D)communications has recently attracted wide attention.In this paper,a relaying D2D communications assisted with cooperative relaying systems using NOMA(DRC-NOMA)is considered.We analyze the ergodic sum-rate for the proposed system and then derive the closed-form expressions.In addition,an optimal power allocation strategy maximizing the ergodic sum-rate is proposed based on these analysis results.Numerical results show the good agreement between the results of analysis and Monte Carlo method.The proposed DRC-NOMA has a great improvement of the ergodic sum-rate in the small regime of average channel gain of D2D pair.展开更多
The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance th...The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction.Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS.According to their distance to the UAV,the users are divided into the close users and remote users.The UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received power.We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement.However,the problem is non-convex.Therefore,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,respectively.We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.展开更多
Managing massive data flows effectively and resolving spectrum shortages are two challenges that smart grid communication networks(SGCN)must overcome.To address these problems,we provide a combined optimization approa...Managing massive data flows effectively and resolving spectrum shortages are two challenges that smart grid communication networks(SGCN)must overcome.To address these problems,we provide a combined optimization approach that makes use of cognitive radio(CR)and non-orthogonal multiple access(NOMA)technologies.Our work focuses on using user pairing(UP)and power allocation(PA)techniques to maximize energy efficiency(EE)in SGCN,particularly within neighbourhood area networks(NANs).We develop a joint optimization problem that takes into account the real-world limitations of a CR-NOMA setting.This problem is NP-hard,nonlinear,and nonconvex by nature.To address the computational complexity of the problem,we use the block coordinate descent(BCD)method,which breaks the problem into UP and PA subproblems.Initially,we proposed the zebra-optimization user pairing(ZOUP)algorithm to tackle the UP problem,which outperforms both orthogonal multiple access(OMA)and non-optimized NOMA(UPWO)by 78.8%and13.6%,respectively,at a SNR of 15 dB.Based on the ZOUP pairs,we subsequently proposed the PA approach,i.e.,ZOUPPA,which significantly outperforms UPWO and ZOUP by 53.2%and 25.4%,respectively,at an SNR of 15 dB.A detailed analysis of key parameters,including varying SNRs,power allocation constants,path loss exponents,user density,channel availability,and coverage radius,underscores the superiority of our approach.By facilitating the effective use of communication resources in SGCN,our research opens the door to more intelligent and energy-efficient grid systems.Our work tackles important issues in SGCN and lays the groundwork for future developments in smart grid communication technologies by combining modern optimization approaches with CR-NOMA.展开更多
基金the National Natural Science Founda-tion of China(No.61871344)the Zhejiang Provincial Natural Science Foundation of China(No.LR20F010002)+1 种基金the National Science and Technology Major Project of China(No.2018ZX03001017-002)the National Key R&D Programof China (No. 2018YFB1801104)。
文摘As a promising physical layer technique, nonorthogonal multiple access(NOMA) can admit multiple users over the same space-time resource block, and thus improve the spectral efficiency and increase the number of access users. Specifically, NOMA provides a feasible solution to massive Internet of Things(IoT) in 5G and beyond-5G wireless networks over a limited radio spectrum. However, severe co-channel interference and high implementation complexity hinder its application in practical systems. To solve these problems, multiple-antenna techniques have been widely used in NOMA systems by exploiting the benefits of spatial degrees of freedom. This study provides a comprehensive review of various multiple-antenna techniques in NOMA systems, with an emphasis on spatial interference cancellation and complexity reduction. In particular, we provide a detailed investigation on multiple-antenna techniques in two-user, multiuser, massive connectivity, and heterogeneous NOMA systems.Finally, future research directions and challenges are identified.
文摘The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the current 5G networks have not achieved the promised 5G goals, including the projected 2000 times EE improvement over the legacy 4G Long Term Evolution (LTE) networks. This paper provides a comprehensive survey of Artificial Intelligence (AI)-enabled MA techniques, emphasizing their roles in Spectrum Sensing (SS), Dynamic Resource Allocation (DRA), user scheduling, interference mitigation, and protocol adaptation. In particular, we systematically analyze the progression of traditional and modern MA schemes, from Orthogonal Multiple Access (OMA)-based approaches like Time Division Multiple Access (TDMA) and Frequency Division Multiple Access (FDMA) to advanced Non-Orthogonal Multiple Access (NOMA) methods, including power domain-NOMA, Sparse Code Multiple Access (SCMA), and Rate Splitting Multiple Access (RSMA). The study further categorizes AI techniques—such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Federated Learning (FL), and Explainable AI (XAI)—and maps them to practical challenges in Dynamic Spectrum Management (DSM), protocol optimization, and real-time distributed decision-making. Optimization strategies, including metaheuristics and multi-agent learning frameworks, are reviewed to illustrate the potential of AI in enhancing energy efficiency, system responsiveness, and cross-layer RA. Additionally, the review addresses security, privacy, and trust concerns, highlighting solutions like privacy-preserving ML, FL, and XAI in 6G and beyond. By identifying research gaps, challenges, and future directions, this work offers a structured resource for researchers and practitioners aiming to integrate AI into 6G MA systems for intelligent, scalable, and secure wireless communications.
基金supported by the National Key Research and Development Program of China(No.2017YFB0403403)the Natural Science Foundation of Guangdong Province(No.2015A030312006).
文摘Although Successive Interference Cancellation(SIC)decoding is widely adopted in Nonorthogonal Multiple Access(NOMA)schemes for the recovery of user data at acceptable complexity,the imperfect SIC would cause Error Propagation(EP),which can severely degrade system performance.In this work,we propose an SIC-free NOMA scheme in pulse modulation based Visible Light Communication(VLC)downlinks,including two types of users with different data rate requirements.Low bit-rate users adopt on-off keying,whereas high bit-rate ones use Multiple Pulse Position Modulation(MPPM).The soft decision decoding scheme is exploited by high bit-rate users to decode MPPM signals,which could fundamentally eliminate the detrimental effect of EP;the scheme is also easier and faster to execute compared with the conventional SIC decoding scheme.Expressions of the symbol error rate and achievable data rate for two types of users are derived.Results of the Monte Carlo simulation are provided to confirm the correctness of theoretical results.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61701201,U1805262,61871446 and 62071247the Natural Science Foundation of Jiangsu Province(No.BK20170758),Six talent peaks project in Jiangsu Province.
文摘Non-orthogonal multiple access(NOMA)is considered as one of the key technologies for the fifth generation(5G)wireless communications.The integration of NOMA and device-to-device(D2D)communications has recently attracted wide attention.In this paper,a relaying D2D communications assisted with cooperative relaying systems using NOMA(DRC-NOMA)is considered.We analyze the ergodic sum-rate for the proposed system and then derive the closed-form expressions.In addition,an optimal power allocation strategy maximizing the ergodic sum-rate is proposed based on these analysis results.Numerical results show the good agreement between the results of analysis and Monte Carlo method.The proposed DRC-NOMA has a great improvement of the ergodic sum-rate in the small regime of average channel gain of D2D pair.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 62271099。
文摘The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction.Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS.According to their distance to the UAV,the users are divided into the close users and remote users.The UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received power.We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement.However,the problem is non-convex.Therefore,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,respectively.We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.
文摘Managing massive data flows effectively and resolving spectrum shortages are two challenges that smart grid communication networks(SGCN)must overcome.To address these problems,we provide a combined optimization approach that makes use of cognitive radio(CR)and non-orthogonal multiple access(NOMA)technologies.Our work focuses on using user pairing(UP)and power allocation(PA)techniques to maximize energy efficiency(EE)in SGCN,particularly within neighbourhood area networks(NANs).We develop a joint optimization problem that takes into account the real-world limitations of a CR-NOMA setting.This problem is NP-hard,nonlinear,and nonconvex by nature.To address the computational complexity of the problem,we use the block coordinate descent(BCD)method,which breaks the problem into UP and PA subproblems.Initially,we proposed the zebra-optimization user pairing(ZOUP)algorithm to tackle the UP problem,which outperforms both orthogonal multiple access(OMA)and non-optimized NOMA(UPWO)by 78.8%and13.6%,respectively,at a SNR of 15 dB.Based on the ZOUP pairs,we subsequently proposed the PA approach,i.e.,ZOUPPA,which significantly outperforms UPWO and ZOUP by 53.2%and 25.4%,respectively,at an SNR of 15 dB.A detailed analysis of key parameters,including varying SNRs,power allocation constants,path loss exponents,user density,channel availability,and coverage radius,underscores the superiority of our approach.By facilitating the effective use of communication resources in SGCN,our research opens the door to more intelligent and energy-efficient grid systems.Our work tackles important issues in SGCN and lays the groundwork for future developments in smart grid communication technologies by combining modern optimization approaches with CR-NOMA.
