基于复杂多主体协作体制的WSN动态组网与干扰对齐研究

本项目从无线传感器网络（WSN）的系统模型和网络容量出发，研究具有复杂多主体特征的WSN动态组网模型与协作干扰对齐策略。主要研究内容包括：基于多主体系统社团结构的动力演化分析法，研究WSN节点的渐近行为，获取社团动态构造方案，建立出WSN的普适性的分层协作动态组网模型；基于组网模型，研究分布式波束赋形，将发射预编码矩阵的闭式解转换为对总体最小二乘和利己、利他贝叶斯均衡问题的研究，获得全局信道信息未知情况下的协作干扰对齐策略；在此基础之上，研究接收端干扰子空间和约束判定算法，考虑当发射预编码矩阵的下降域和可行域交集为空时的Karush-Kuhn-Tucker条件最优解，从而获取认知协作干扰对齐策略。通过对本项目的研究，将建立出WSN中具有普适意义的动态组网模型，并可望最大化网络吞吐量及提高频谱利用率。本项目的研究将对WSN的组网模型与干扰对齐的理论研究和实际应用具有十分重要的意义。

Based on system model and capacity of the wireless sensor network(WSN), this project focus on dynamic network model and interference alignment for WSN. The major investigation of this project as follows. Based on dynamic evolution of community structure for multi-agent systenm, we consider the asymptotic behavior of the WSN nodes, obtain the dynamic structure of node community, establish universal and hierarchical dynamic network model of WSN. Under this network model, we study on the distributed beamforming, and achieve interference alignment scheme without global channel statement by translating the closed-form solution for the transmit precoding matrix into the problem of total least square and egoistic, altruistic Bayesian Games. Based on the interference alignment scheme, we research receive interference subspace and the constraint decision algorithm, consider the intersection of drop and feasible region of the transmit precoding matrix is null set, and the optimal solution of the transmit preceding matrix under Karush-Kuhn-Tucker condition. This project will establish an universal dynamic network model of WSN, maximize network capacity and frequency efficiency. The research of the project will obtain significant development for network model and interference alignment of the WSN.