认知无线电网络中基于业务自适应的干扰对齐新机制探索

Investigation of traffic adaptation based interference alignment for cognitive radio networks

提出了一种基于自适应干扰对齐的认知无线电网络干扰协调新方法。这种方法采用基于离线搜索的干扰对齐模式优化和基于用户业务需求的自适应最佳模式选择,通过收发两端联合设计的干扰对齐算法实现主次用户的动态信道共享;为了简便有效地构造波束成形矩阵和干扰抑制矩阵,还推导出了一种干扰对齐的闭式解,并且证明了其适用条件;还对所提方法的可达自由度做了分析,得到一个下界。采用统计模型进行的仿真结果表明,所提出的自适应方法相对于修正的机会干扰对齐和固定模式的干扰对齐具有明显的自由度优势,因而可以有效提高认知用户的容量。由于所提出的方法运算复杂度不高,可望未来应用于低成本的认知终端。

A novel method of adaptive interference alignment （IA） was proposed for cognitive radio networks. The new IA scheme, which was chiefly characterized by off-line feasible set optimization and traffic load oriented adaptation, ena-bles dynamic sharing of channel resource among a pair of primary users and multiple pairs of secondary users. To effec-tively construct the beam-forming and interference suppression matrix for IA, then not only derive an adaptive closed-form algorithm, but its average degrees of freedom （d.o.f） were also analyzed with random traffic load model and a lower bound is given as well. The analysis is verified with statistic model simulation and the results show that the new method outperforms both modified opportunistic IA and fixed IA in average d.o.f and thus can significantly improve the sum capacity of cognitive users without introducing interference to the primary user. Moreover, due to its simplicity, the scheme is highly desirable to implement in low cost terminals.