大规模MIMO系统中基于溢出概率的鲁棒协作波束设计

Robust Coordinated Beamforming Design Based on Outage Probability for Massive MIMO

大规模多输入多输出(Massive MIMO)技术通过在基站端配置大规模天线能有效提升5G蜂窝系统容量。考虑信道估计误差对系统性能的影响,该文在多小区大规模MIMO系统中形成了用户信干噪比的非溢出概率约束下最小化系统功率的优化问题。针对非凸概率约束中下行波束难于求解的问题,该文根据矩阵迹的性质将优化问题中的非凸约束缩放,进而提出上下行对偶算法求解波束矢量。为进一步减少多小区系统中信令开销,基于大系统分析,提出了仅采用大尺度信息的分布式算法。仿真结果表明,所提的分布式算法与对偶算法相比,在保证用户信干噪比的概率约束时,降低了大规模MIMO系统中传输瞬时信道状态信息的开销,同时具有良好的鲁棒性。

Massive MIMO technique can effectively increase system capacity in the fifth Generation（5G） cellular network, where Base Station（BS） is equipped with a very large number of antennas. Considering the impact of channel estimation error on performance, the transmission power minimization problem is formulated subject to the non-outage probability constraints of each user＇s signal to interference plus noise ratio. In respect that the non-convex probability constraints make the downlink beamforming difficult to solve, Uplink-Downlink Duality Algorithm（UDDA） is proposed to design Coordinated Beam Forming（CBF） by using the property of trace of the matrix to scale the non-convex probability constraint. To reduce the signaling overhead in Massive MIMO system, a Distributed Algorithm based on Large System Analysis（DALSA） is proposed, which only needs the large-scale channel information. The simulation results show that DALSA, in the targeted SINR constraint, not only reduces instantaneous channel state information transmission overhead in Massive MIMO system, but also performs well in robustness compared with UDDA.