In this paper,we optimize the spectrum efficiency(SE)of uplink massive multiple-input multiple-output(MIMO)system with imperfect channel state information(CSI)over Rayleigh fading channel.The SE optimization problem i...In this paper,we optimize the spectrum efficiency(SE)of uplink massive multiple-input multiple-output(MIMO)system with imperfect channel state information(CSI)over Rayleigh fading channel.The SE optimization problem is formulated under the constraints of maximum power and minimum rate of each user.Then,we develop a near-optimal power allocation(PA)scheme by using the successive convex approximation(SCA)method,Lagrange multiplier method,and block coordinate descent(BCD)method,and it can obtain almost the same SE as the benchmark scheme with lower complexity.Since this scheme needs three-layer iteration,a suboptimal PA scheme is developed to further reduce the complexity,where the characteristic of massive MIMO(i.e.,numerous receive antennas)is utilized for convex reformulation,and the rate constraint is converted to linear constraints.This suboptimal scheme only needs single-layer iteration,thus has lower complexity than the near-optimal scheme.Finally,we joint design the pilot power and data power to further improve the performance,and propose an two-stage algorithm to obtain joint PA.Simulation results verify the effectiveness of the proposed schemes,and superior SE performance is achieved.展开更多
In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things(IoT) and ensure the system stability,an adaptive resource allocation algorithm is proposed,which dyna...In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things(IoT) and ensure the system stability,an adaptive resource allocation algorithm is proposed,which dynamically assigns the network bandwidth and priority among components according to their signals' frequency domain characteristics.A remote sensed and controlled unmanned ground vehicle(UGV) path tracking test-bed was developed and multiple UGV's tracking error signals were measured in the simulation for performance evaluation.Results show that with the same network bandwidth constraints,the proposed algorithm can reduce the accumulated and maximum errors of UGV path tracking by over 60% compared with the conventional static algorithm.展开更多
基金supported by the Fundamental Research Funds for the Central Universities of NUAA(No.kfjj20200414)Natural Science Foundation of Jiangsu Province in China(No.BK20181289).
文摘In this paper,we optimize the spectrum efficiency(SE)of uplink massive multiple-input multiple-output(MIMO)system with imperfect channel state information(CSI)over Rayleigh fading channel.The SE optimization problem is formulated under the constraints of maximum power and minimum rate of each user.Then,we develop a near-optimal power allocation(PA)scheme by using the successive convex approximation(SCA)method,Lagrange multiplier method,and block coordinate descent(BCD)method,and it can obtain almost the same SE as the benchmark scheme with lower complexity.Since this scheme needs three-layer iteration,a suboptimal PA scheme is developed to further reduce the complexity,where the characteristic of massive MIMO(i.e.,numerous receive antennas)is utilized for convex reformulation,and the rate constraint is converted to linear constraints.This suboptimal scheme only needs single-layer iteration,thus has lower complexity than the near-optimal scheme.Finally,we joint design the pilot power and data power to further improve the performance,and propose an two-stage algorithm to obtain joint PA.Simulation results verify the effectiveness of the proposed schemes,and superior SE performance is achieved.
基金Supported by Natural Science Foundation of Tianjin (No. 07JCZDJC05800)Science and Technology Supporting Plan of Tianjin (No. 09ZCKFGX29200)
文摘In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things(IoT) and ensure the system stability,an adaptive resource allocation algorithm is proposed,which dynamically assigns the network bandwidth and priority among components according to their signals' frequency domain characteristics.A remote sensed and controlled unmanned ground vehicle(UGV) path tracking test-bed was developed and multiple UGV's tracking error signals were measured in the simulation for performance evaluation.Results show that with the same network bandwidth constraints,the proposed algorithm can reduce the accumulated and maximum errors of UGV path tracking by over 60% compared with the conventional static algorithm.
