认知MIMO系统中基于博弈论的干扰对齐算法研究

Interference Alignment for Cognitive Radio MIMO Cognitive System Based on Game Theory

为消除用户间干扰,提高认知无线电多输入多输出(CR-MIMO)系统传输速率,给出一种基于博弈论的干扰对齐算法。该算法首先采用注水算法为主用户进行功率分配,同时设计次用户预编码使次用户信号落入主用户未分配功率的子信道。然后将次用户之间的多条干扰链路构成一个博弈群体进行求解,实现次用户之间的干扰对齐。此外,为最大化次用户传输速率,将次用户功率分配问题转换为布谷鸟鸟巢的选择问题,构造适应度函数,得到最优的功率分配方案。数值分析表明,该算法可以消除主次用户的干扰以及次用户之间的干扰,传输速率比最大信干噪比(Max-SINR)算法高2 b?s-1?Hz-2,同时,结合布谷鸟搜索算法进行功率分配后传输速率高于文献[13]。

To eliminate interference and improve the transmission rate of cognitive radio multiple-input multiple-output （CR-MIMO） systems, an interference alignment algorithm based on game theory is proposed. The algorithm uses water-filling algorithm for maximum the transmission rate of primary user. Meanwhile, the pre-coding matrix of secondary users is designed for the secondary user signal to fall into free sub-channel of the primary user. Multiple interference links are constituted into a game group to achieve interference alignment of secondary users. Moreover, the power allocation of secondary users is formulated as selection problem of cuckoo＇s nests, the optimal power allocation is obtained according to the fitness function. Numerical simulation results show that this algorithm can eliminate the interference between the primary user and secondary users and the interference among secondary users. Compared with the maximize-signal-to-interference-plus-noise-ratio algorithm （Max-SINR）, the interference alignment algorithm proposed can improve the transmission rate of secondary users about 2 b.s-l.Hz-2. Moreover, the transmission rate can also be improved by using cuckoo search algorithm for power distribution compared with the result presented elsewhere.