The 3GPP standard defines the requirements for next-generation wireless networks,with particular attention to Ultra-Reliable Low-Latency Communications(URLLC),critical for applications such as Unmanned Aerial Vehicles...The 3GPP standard defines the requirements for next-generation wireless networks,with particular attention to Ultra-Reliable Low-Latency Communications(URLLC),critical for applications such as Unmanned Aerial Vehicles(UAVs).In this context,Non-Orthogonal Multiple Access(NOMA)has emerged as a promising technique to improve spectrum efficiency and user fairness by allowing multiple users to share the same frequency resources.However,optimizing key parameters–such as beamforming,rate allocation,and UAV trajectory–presents significant challenges due to the nonconvex nature of the problem,especially under stringent URLLC constraints.This paper proposes an advanced deep learning-driven approach to address the resulting complex optimization challenges.We formulate a downlink multiuser UAV,Rate-Splitting Multiple Access(RSMA),and Multiple Input Multiple Output(MIMO)system aimed at maximizing the achievable rate under stringent constraints,including URLLC quality-of-service(QoS),power budgets,rate allocations,and UAV trajectory limitations.Due to the highly nonconvex nature of the optimization problem,we introduce a novel distributed deep reinforcement learning(DRL)framework based on dual-agent deep deterministic policy gradient(DA-DDPG).The proposed framework leverages inception-inspired and deep unfolding architectures to improve feature extraction and convergence in beamforming and rate allocation.For UAV trajectory optimization,we design a dedicated actor-critic agent using a fully connected deep neural network(DNN),further enhanced through incremental learning.Simulation results validate the effectiveness of our approach,demonstrating significant performance gains over existing methods and confirming its potential for real-time URLLC in next-generation UAV communication networks.展开更多
Rate-splitting multiple access(RSMA)can cope with a wide range of propagation conditions in multigroup multicast communications through rate splitting optimization.To breakthrough the grouprate limited bottleneck,reco...Rate-splitting multiple access(RSMA)can cope with a wide range of propagation conditions in multigroup multicast communications through rate splitting optimization.To breakthrough the grouprate limited bottleneck,reconfigurable intelligent surface(RIS)technique can be introduced to assist wireless communications through enhancing the channel quality.In RIS-aided RSMA multigroup multicasting,how to provide fair and high-quality multiuser service under power and spectrum constraints is essential.In this paper,we propose a max-min fair RIS-aided rate-splitting multiple access(MMF-RISRSMA)scheme for multigroup multicast communications,where the rate fairness is obtained by maximizing the minimum group-rate.In doing so,we jointly optimize the beamformers,the rate splitting vector at the transmitter,as well as the phase shifts at RIS.To solve it,we divide the original optimization problem into two subproblems and alternately optimize the variables.The beamforming and rate splitting optimization subproblem is solved by using the successive convex approximation technique.The phase shift optimization subproblem is solved through the penalty function method to achieve a rank-one locally optimal solution.Simulations demonstrate that the proposed MMF-RIS-RSMA scheme can obtain significant performance gain in terms of the minimum group-rate.展开更多
Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a c...Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a cognitive radio-inspired rate-splitting multiple access(CR-RSMA)system in which a primary user's(PU's)quality of service(QoS)requirements must be guaranteed.Without introducing intolerable interference to deteriorate the PU's outage performance,the SU conducts rate-splitting to transmit its signal to the base-station through the direct link and IRS reflecting channels.For the IRS-assisted CR-RSMA(IRS-CR-RSMA)scheme,we derive the optimal transmit power allocation,target rate allocation,and successive interference cancellation decoding order to enhance the outage performance of the SU.The closed-form expression for the SU's outage probability achieved by the IRS-CR-RSMA scheme is derived.Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed IRS-CR-RSMA scheme over the CR-RSMA scheme.展开更多
Integrated Sensing And Communication(ISAC)is regarded as a promising technology for facilitating the rapid advancement of Sixth-Generation(6G)due to its concurrent transmission of information and environmental sensing...Integrated Sensing And Communication(ISAC)is regarded as a promising technology for facilitating the rapid advancement of Sixth-Generation(6G)due to its concurrent transmission of information and environmental sensing capabilities.Rate-Splitting Multiple Access(RSMA),through the utilization of Successive Interference Cancellation(SIC)and Rate-Splitting(RS)at the transceiver,can fulfill the sensing requirement and supersede individual radar sequence to mitigate the interference between communication and sensing.This paper investigates the transceiver design of the RSMA-assisted ISAC in a Network-Assisted Full-Duplex(NAFD)cell-free Massive Multiple-Input Multiple-Output(mMIMO)system.We first derive the expressions of the communication achievable data rate and radar sensing Signal to Interference plus Noise Ratio(SINR).Subsequently,an optimization problem is formulated to maximize the communication achievable data rate,subject to both radar sensing constraints and fronthaul constraints,an effective algorithm based on sparse beamforming scheme and Semi-Definite Relaxation(SDR)is then proposed to acquire the near-optimal transceiver.Numerical results demonstrate that the application of RSMA technology in ISAC systems can significantly enhance system performance,and reveal that Dual-Functionalities Radar-Communication(DFRC)scheme can achieve higher data rate than the traditional scheme.展开更多
This paper investigates the resource allocation for rate-splitting multiple access(RSMA)enabled multibeam satellite communication systems.Specifically,we minimize the total unmet user rate,which denotes the difference...This paper investigates the resource allocation for rate-splitting multiple access(RSMA)enabled multibeam satellite communication systems.Specifically,we minimize the total unmet user rate,which denotes the difference between the users’rate requirement and the practical achievable rate,as well as the total transmit power of the satellite by optimizing the precoding,power allocation,and rate allocation,under the per-feed power and rate constraints.To solve the non-convex optimization problem,a twostage scheme is proposed.In particular,in the first stage,we present a precoding scheme by maximizing the signal-to-leakage-plus-noise ratio of each beam to eliminate the inter-beam interference.In the second stage,we introduce auxiliary variables to obtain an upper bound on the objective function under the given precoding matrix and transform the rate constraints of the original problem into second-order cones(SOC)and linear matrix inequations(LMI).Then,the successive convex approximation(SCA)technique is used to obtain suboptimal power and rate allocation solutions.Moreover,the initial feasible solution for power allocation is provided by using the standard interior point method.Finally,numerical results verify the superiority of our proposed solution compared to the benchmark methods in terms of objective function values.展开更多
基金supported by the Deputyship of Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number RI-44-0291.
文摘The 3GPP standard defines the requirements for next-generation wireless networks,with particular attention to Ultra-Reliable Low-Latency Communications(URLLC),critical for applications such as Unmanned Aerial Vehicles(UAVs).In this context,Non-Orthogonal Multiple Access(NOMA)has emerged as a promising technique to improve spectrum efficiency and user fairness by allowing multiple users to share the same frequency resources.However,optimizing key parameters–such as beamforming,rate allocation,and UAV trajectory–presents significant challenges due to the nonconvex nature of the problem,especially under stringent URLLC constraints.This paper proposes an advanced deep learning-driven approach to address the resulting complex optimization challenges.We formulate a downlink multiuser UAV,Rate-Splitting Multiple Access(RSMA),and Multiple Input Multiple Output(MIMO)system aimed at maximizing the achievable rate under stringent constraints,including URLLC quality-of-service(QoS),power budgets,rate allocations,and UAV trajectory limitations.Due to the highly nonconvex nature of the optimization problem,we introduce a novel distributed deep reinforcement learning(DRL)framework based on dual-agent deep deterministic policy gradient(DA-DDPG).The proposed framework leverages inception-inspired and deep unfolding architectures to improve feature extraction and convergence in beamforming and rate allocation.For UAV trajectory optimization,we design a dedicated actor-critic agent using a fully connected deep neural network(DNN),further enhanced through incremental learning.Simulation results validate the effectiveness of our approach,demonstrating significant performance gains over existing methods and confirming its potential for real-time URLLC in next-generation UAV communication networks.
基金supported in part by the Project of International Cooperation and Exchanges NSFC under Grant No.61860206005in part by the National Natural Science Foundation of China under Grant No.62201329,No.62171262in part by Shandong Provincial Natural Science Foundation under Grant ZR2021YQ47。
文摘Rate-splitting multiple access(RSMA)can cope with a wide range of propagation conditions in multigroup multicast communications through rate splitting optimization.To breakthrough the grouprate limited bottleneck,reconfigurable intelligent surface(RIS)technique can be introduced to assist wireless communications through enhancing the channel quality.In RIS-aided RSMA multigroup multicasting,how to provide fair and high-quality multiuser service under power and spectrum constraints is essential.In this paper,we propose a max-min fair RIS-aided rate-splitting multiple access(MMF-RISRSMA)scheme for multigroup multicast communications,where the rate fairness is obtained by maximizing the minimum group-rate.In doing so,we jointly optimize the beamformers,the rate splitting vector at the transmitter,as well as the phase shifts at RIS.To solve it,we divide the original optimization problem into two subproblems and alternately optimize the variables.The beamforming and rate splitting optimization subproblem is solved by using the successive convex approximation technique.The phase shift optimization subproblem is solved through the penalty function method to achieve a rank-one locally optimal solution.Simulations demonstrate that the proposed MMF-RIS-RSMA scheme can obtain significant performance gain in terms of the minimum group-rate.
基金supported in part by National Natural Science Foundation of China under Grant 62071202in part by Shandong Provincial Natural Science Foundation under Grants ZR2020MF009,ZR2020MF075in part by Shandong Key Laboratory of Intelligent Buildings Technology undert Grant SDIBT202004.
文摘Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a cognitive radio-inspired rate-splitting multiple access(CR-RSMA)system in which a primary user's(PU's)quality of service(QoS)requirements must be guaranteed.Without introducing intolerable interference to deteriorate the PU's outage performance,the SU conducts rate-splitting to transmit its signal to the base-station through the direct link and IRS reflecting channels.For the IRS-assisted CR-RSMA(IRS-CR-RSMA)scheme,we derive the optimal transmit power allocation,target rate allocation,and successive interference cancellation decoding order to enhance the outage performance of the SU.The closed-form expression for the SU's outage probability achieved by the IRS-CR-RSMA scheme is derived.Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed IRS-CR-RSMA scheme over the CR-RSMA scheme.
基金supported by the National Natural Science Foundation of China under Grant 62171126.
文摘Integrated Sensing And Communication(ISAC)is regarded as a promising technology for facilitating the rapid advancement of Sixth-Generation(6G)due to its concurrent transmission of information and environmental sensing capabilities.Rate-Splitting Multiple Access(RSMA),through the utilization of Successive Interference Cancellation(SIC)and Rate-Splitting(RS)at the transceiver,can fulfill the sensing requirement and supersede individual radar sequence to mitigate the interference between communication and sensing.This paper investigates the transceiver design of the RSMA-assisted ISAC in a Network-Assisted Full-Duplex(NAFD)cell-free Massive Multiple-Input Multiple-Output(mMIMO)system.We first derive the expressions of the communication achievable data rate and radar sensing Signal to Interference plus Noise Ratio(SINR).Subsequently,an optimization problem is formulated to maximize the communication achievable data rate,subject to both radar sensing constraints and fronthaul constraints,an effective algorithm based on sparse beamforming scheme and Semi-Definite Relaxation(SDR)is then proposed to acquire the near-optimal transceiver.Numerical results demonstrate that the application of RSMA technology in ISAC systems can significantly enhance system performance,and reveal that Dual-Functionalities Radar-Communication(DFRC)scheme can achieve higher data rate than the traditional scheme.
文摘This paper investigates the resource allocation for rate-splitting multiple access(RSMA)enabled multibeam satellite communication systems.Specifically,we minimize the total unmet user rate,which denotes the difference between the users’rate requirement and the practical achievable rate,as well as the total transmit power of the satellite by optimizing the precoding,power allocation,and rate allocation,under the per-feed power and rate constraints.To solve the non-convex optimization problem,a twostage scheme is proposed.In particular,in the first stage,we present a precoding scheme by maximizing the signal-to-leakage-plus-noise ratio of each beam to eliminate the inter-beam interference.In the second stage,we introduce auxiliary variables to obtain an upper bound on the objective function under the given precoding matrix and transform the rate constraints of the original problem into second-order cones(SOC)and linear matrix inequations(LMI).Then,the successive convex approximation(SCA)technique is used to obtain suboptimal power and rate allocation solutions.Moreover,the initial feasible solution for power allocation is provided by using the standard interior point method.Finally,numerical results verify the superiority of our proposed solution compared to the benchmark methods in terms of objective function values.
