基于遗传算法的三单播网络对齐及优化

针对三单播有向无循环网络,考虑无法得知网络内部拓扑图结构,且内部节点数量无法估量的情况.应用渐近干扰对齐技术研究各用户发送不同数据流m,n,p时的预编码矩阵,联合应用图论中的最短路径遗传算法和网络线性性质,分析其预编码网络对齐(precoding-based network alignment,PBNA)的可行性条件,该条件最终可简化为2个方程,实际检验复杂度较低,且每对单播会话能够达到1/2的自由度.

Network alignment and optimization for three unicast network based on genetic algorithms

This paper considers the 3 unicast problem of directed acyclic network, the internal network topology structure not being known, and the number of internal nodes immeasurable. When different data streams m, n, p are sent by each user, these precoding matrixes are studied by using the asymptotic interference alignment technique, further, the set of feasibility conditions for precoding-based network alignment (PBNA) can be reduced to 2 by using two shortest path genetic algorithm and graph-related properties. Significantly reduced computational complexities are obtained and achieved 1/2 degrees of freedom (DOF) of the individual source-destination.