基于压缩感知的无线传感器网络数据传输跨层优化算法

Data transmission cross-layer optimization of wireless sensor networks based on compressive sensing

针对无线传感器网络中数据传输问题,提出一种基于压缩感知的数据传输跨层优化算法.首先,为了剔除原始数据时间、空间冗余性,构造一种时空动态感知矩阵,降低采样频率的同时使得传感器采集的数据包含全部有用的信息.其次,以最小传输数据量为目标,以链路容量、功率、路由选择为约束条件,建立跨层的优化模型,通过求解优化模型,得到最优的功率控制、链路容量和路由选择策略.仿真结果表明,所提算法能够降低数据传输量,克服传统数据传输算法中由于数据处理不均衡导致的网络拥塞问题.

A data transmission cross-layer optimization algorithm based on compressive sensing is proposed to solve the problems of data transmission in WSNs. Firstly, a spatiotemporal dynamic sensing matrix is constructed to exclude spatiotemporal redundancy of data, which reduces sampling frequency and makes sampled data contain all useful information. Then, according to the objective of the minimum transmission data, a cross-layer optimization model is established based on the constraint conditions of link capacity, power and routing selection. The optimal power control, link capacity and routing selection schemes are obtained by solving the optimization model. Simulation results show that the algorithm reduces the amount of data transmission, and overcomes the congestion caused by unbalanced data processing problems in the traditional algorithm.