In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,th...In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.展开更多
In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose ...In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.展开更多
This paper considers the problem of joint beamformer design for a two-tier wireless network,whereby a set of cache-enabled access points(APs)are connected to the base station(BS)via wireless backhaul links.The APs can...This paper considers the problem of joint beamformer design for a two-tier wireless network,whereby a set of cache-enabled access points(APs)are connected to the base station(BS)via wireless backhaul links.The APs can prefetch and store the files requested by users,to serve users directly in the access links.Thus low-latency transmissions are enabled as the transmission in the backhaul links is saved.However,due to the limited cache capacity,not all requested files can be stored in the APs,some of the non-cached APs then should be utilized as long as their transmission delays in the access and backhaul links can be well addressed.Two delay optimal beamformer design(DOBD)problems are formulated to minimize the overall delay incurred in the backhaul and access link transmissions via a joint optimization of the beamformer at the BS and APs.We consider the DOBD problem under non-fragment and fragment caching policies,both involving nonconvex link rate constraints.The semi-definite relaxation(SDR)and sequential convex approximation(SCA)schemes are adopted to approximate the nonconvex problems into convex ones,which are then iteratively solved.Numerical results demonstrate the convergence and improved transmission delay performance of the proposed scheme under various network settings.展开更多
An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVD...An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVDR）, the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.展开更多
针对工作于underlay模式的认知无线网络(CRN,Cognitive Radio Network)上行功率控制问题,本文提出一种基于多天线波束赋形,由认知基站和认知用户联合优化的分布式上行功率控制算法.联合优化的具体步骤为认知基站通过求解最大广义特征值...针对工作于underlay模式的认知无线网络(CRN,Cognitive Radio Network)上行功率控制问题,本文提出一种基于多天线波束赋形,由认知基站和认知用户联合优化的分布式上行功率控制算法.联合优化的具体步骤为认知基站通过求解最大广义特征值问题完成多天线波束赋形优化;认知用户先将非线性功率优化问题转换为几何规划凸优化问题,再使用梯度法完成分布式发送功率优化;认知基站和认知用户交替优化,实现网络效用最大化.数值仿真显示,同只优化认知用户功率的上行功率控制算法相比,认知基站和认知用户联合优化的上行功率控制算法不仅能得到更大的网络效用值,而且对主用户的干扰具有鲁棒性.展开更多
基金supported by the National Key R&D Program of China under Grant 2019YFB1803400partly by National Natural Science Foundation of China under Grant 62071394.
文摘In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.
基金supported in part by the National Natural Science Foundation of China under Grants 61971126 and 61921004ZTE CorporationState Key Laboratory of Mobile Network and Mobile Multimedia Technology.
文摘In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.
基金National Key Research and Development Program of China(2022YFB2702302)Natural Science Foundation of China(62171278)Natural Science Foundation of China(62101327)。
文摘This paper considers the problem of joint beamformer design for a two-tier wireless network,whereby a set of cache-enabled access points(APs)are connected to the base station(BS)via wireless backhaul links.The APs can prefetch and store the files requested by users,to serve users directly in the access links.Thus low-latency transmissions are enabled as the transmission in the backhaul links is saved.However,due to the limited cache capacity,not all requested files can be stored in the APs,some of the non-cached APs then should be utilized as long as their transmission delays in the access and backhaul links can be well addressed.Two delay optimal beamformer design(DOBD)problems are formulated to minimize the overall delay incurred in the backhaul and access link transmissions via a joint optimization of the beamformer at the BS and APs.We consider the DOBD problem under non-fragment and fragment caching policies,both involving nonconvex link rate constraints.The semi-definite relaxation(SDR)and sequential convex approximation(SCA)schemes are adopted to approximate the nonconvex problems into convex ones,which are then iteratively solved.Numerical results demonstrate the convergence and improved transmission delay performance of the proposed scheme under various network settings.
文摘针对无线信号易受信道影响的难题,将智能反射面(Intelligent Reflecting Surface,IRS)被动波束赋形和基站(Base Station,BS)3D波束赋形进行联合设计。为最大化加权和速率,首先基于投影梯度下降法和加权均方误差等效原理,提出了一种多用户交替优化算法(Multi-User Alternative Optimization,MU-AO),其具有普适性。其次,基于高信噪比(Signal-to-Noise Ratio,SNR)近似原理,提出了一种多用户三级优化算法(Multi-User Three Stage Optimization,MUTSO),通过计算次优组合解来降低计算复杂度。最后,基于BS天线下倾角预定义策略,提出了一种多用户基于直射链路优化算法(Multi-User Direct-Link Based Optimization,MU-DLBO),能够实现复杂度与性能的均衡。实验表明,所提算法均能有效提升系统加权和速率,体现了联合波束赋形的有效性。
基金supported by the National Science&Technology Pillar Program(2013BAF07B03)Zhejiang Provincial Natural Science Foundation of China(LY13F010009)
文摘An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVDR）, the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.
文摘针对工作于underlay模式的认知无线网络(CRN,Cognitive Radio Network)上行功率控制问题,本文提出一种基于多天线波束赋形,由认知基站和认知用户联合优化的分布式上行功率控制算法.联合优化的具体步骤为认知基站通过求解最大广义特征值问题完成多天线波束赋形优化;认知用户先将非线性功率优化问题转换为几何规划凸优化问题,再使用梯度法完成分布式发送功率优化;认知基站和认知用户交替优化,实现网络效用最大化.数值仿真显示,同只优化认知用户功率的上行功率控制算法相比,认知基站和认知用户联合优化的上行功率控制算法不仅能得到更大的网络效用值,而且对主用户的干扰具有鲁棒性.
