Cell-free (CF) massive multiple-input multiple-output (MIMO) systems are expected to implement advanced cooperative communication techniques to let geographically distributed access points jointly serve user equipments. Building on the \emph{Team Theory}, we design the uplink team minimum mean-squared error (TMMSE) combining under limited data and flexible channel state information (CSI) sharing. Taking into account the effect of both channel estimation errors and pilot contamination, a minimum MSE problem is formulated to derive unidirectional TMMSE, centralized TMMSE and statistical TMMSE combining functions, where CF massive MIMO systems operate in unidirectional CSI, centralized CSI and statistical CSI sharing schemes, respectively. We then derive the uplink spectral efficiency (SE) of the considered system. The results show that, compared to centralized TMMSE, the unidirectional TMMSE only needs nearly half the cost of CSI sharing burden with neglectable SE performance loss. Moreover, the performance gap between unidirectional and centralized TMMSE combining schemes can be effectively reduced by increasing the number of APs and antennas per AP.
翻译:考虑到频道估计误差和试点污染的影响,预计将采用先进的合作通信技术,使地理分布的接入点能够共同为用户设备服务。我们以memph{Team Theory}为基础,设计上行团队最小平均差数(TMMSE),结合有限的数据和灵活的频道国家信息共享;考虑到频道估计误差和试点污染的影响,设计出最低 MSE问题,以产生单向TMSE、集中的TMMSE和统计性的TMMSE组合功能,其中CF大型MIS系统分别在单向 CSI、集中的CSI和统计性CSI共享计划运作。然后我们得出所考虑的系统的高链效率(SE),结果显示,与集中的TMMSE相比,单向TMSE仅仅需要近一半的CSI分担可忽略的SE性能损失的费用。此外,单向和集中的TMSE组合计划之间的性能差距可以通过增加AP的数量和每个AP天线有效地缩小。