基于容量最大化的非迭代干扰对齐优化算法

Non-iterative Interference Alignment optimization algorithm based on maximum capacity

现有分布式迭代干扰对齐算法没有考虑基站与用户终端处理能力的差异,使得基站和用户端都具有较高的计算复杂度和系统开销。针对下行链路和上行链路分别提出一种基于容量最大化准则的非迭代干扰对齐优化算法。所提算法在基站端使用基于容量最大化准则的优化方法求解发送预编码矩阵或接收抑制矩阵,在用户端使用迫零准则生成接收抑制矩阵或随机生成发送预编码矩阵。分析和仿真结果表明,所提的2种算法基站端的计算复杂度和系统开销与现有算法相当,但用户端的计算复杂度和系统开销大大降低,并且可以获得与最大信干噪比(Max-SINR)算法相当的系统性能。

The existing distributed iterative Interference Alignment(IA) algorithms do not take the processing capacities of the base stations and the user equipment into account, which makes the base stations and the user equipment have both high computational complexity and high system overheads. A non-iterative IA optimization algorithm based on maximum capacity is proposed for the downlink and uplink, respectively. With the proposed algorithm, the base stations could obtain the transmitting pre-coding matrix or the receiving suppressing matrix by the optimal method based on maximum capacity, and the user equipment could obtain the receiving suppressing matrix by zero force method and randomly generate the transmitting pre-coding matrix. Analysis and simulation results show that, with the proposed algorithm, the computational complexity and system overheads at the base station are the same as the existing algorithms, but at the user equipment, they can be greatly decreased. Furthermore, the proposed algorithm can achieve a good performance similar with that of the Maximum Signal-to-Interference-and- Noise Ratio(Max-SINR) algorithm.