Cell-free massive multiple-input multipleoutput(MIMO)is a promising technology for future wireless communications,where a large number of distributed access points(APs)simultaneously serve all users over the same time...Cell-free massive multiple-input multipleoutput(MIMO)is a promising technology for future wireless communications,where a large number of distributed access points(APs)simultaneously serve all users over the same time-frequency resources.Since users and APs may locate close to each other,the line-of-sight(Lo S)transmission occurs more frequently in cell-free massive MIMO systems.Hence,in this paper,we investigate the cell-free massive MIMO system with Lo S and non-line-of-sight(NLo S)transmissions,where APs and users are both distributed according to Poisson point process.Using tools from stochastic geometry,we derive a tight lower bound for the user downlink achievable rate and we further obtain the energy efficiency(EE)by considering the power consumption on downlink payload transmissions and circuitry dissipation.Based on the analysis,the optimal AP density and AP antenna number that maximize the EE are obtained.It is found that compared with the previous work that only considers NLo S transmissions,the actual optimal AP density should be much smaller,and the maximized EE is actually much higher.展开更多
针对视距(Line of Sight,LOS)和非视距(None-Line of Sight,NLOS)混合环境机动目标跟踪问题,提出一种基于"当前"统计模型(current statistical,CS)和无迹卡尔曼滤波(unscented Kalman filter,UKF)的交互式多模型方法(IMM-UKF-...针对视距(Line of Sight,LOS)和非视距(None-Line of Sight,NLOS)混合环境机动目标跟踪问题,提出一种基于"当前"统计模型(current statistical,CS)和无迹卡尔曼滤波(unscented Kalman filter,UKF)的交互式多模型方法(IMM-UKF-CS)。该方法在交互式多模型的框架内,利用CS在机动目标跟踪方面的优势,并选择具有较高跟踪精度且计算代价较低的UKF作为子滤波器。仿真结果表明:在LOS/NLOS混合环境中,IMM-UKF-CS具有较高的跟踪精度、较强的鲁棒性及较低的时间代价,具有良好的应用价值。展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 62171231in part by the Jiangsu Provincial Key Research and Development Program(No.BE2020084-1)。
文摘Cell-free massive multiple-input multipleoutput(MIMO)is a promising technology for future wireless communications,where a large number of distributed access points(APs)simultaneously serve all users over the same time-frequency resources.Since users and APs may locate close to each other,the line-of-sight(Lo S)transmission occurs more frequently in cell-free massive MIMO systems.Hence,in this paper,we investigate the cell-free massive MIMO system with Lo S and non-line-of-sight(NLo S)transmissions,where APs and users are both distributed according to Poisson point process.Using tools from stochastic geometry,we derive a tight lower bound for the user downlink achievable rate and we further obtain the energy efficiency(EE)by considering the power consumption on downlink payload transmissions and circuitry dissipation.Based on the analysis,the optimal AP density and AP antenna number that maximize the EE are obtained.It is found that compared with the previous work that only considers NLo S transmissions,the actual optimal AP density should be much smaller,and the maximized EE is actually much higher.
文摘针对视距(Line of Sight,LOS)和非视距(None-Line of Sight,NLOS)混合环境机动目标跟踪问题,提出一种基于"当前"统计模型(current statistical,CS)和无迹卡尔曼滤波(unscented Kalman filter,UKF)的交互式多模型方法(IMM-UKF-CS)。该方法在交互式多模型的框架内,利用CS在机动目标跟踪方面的优势,并选择具有较高跟踪精度且计算代价较低的UKF作为子滤波器。仿真结果表明:在LOS/NLOS混合环境中,IMM-UKF-CS具有较高的跟踪精度、较强的鲁棒性及较低的时间代价,具有良好的应用价值。
