无线网络节点信号节能传输轨迹仿真

摘要

Sensor nodes trajectory fitting is a very challenging issue due to the high energy consumption on frequency transmission for sensor nodes localization in Wireless Sensor Networks (WSN),a new method for nodes trajectory fitting is proposed based on the low rank matrix recovery algorithm (LRMR),which includes the reducing of energy consumption by sparse sampling of node tracking information.While the LRMR algorithm is modified to improve operating speed by the local coarse optimization on single low rank matrix and noise matrix,and by the global fine optimization on the elements in recovery matrix subtly.The method of trajectory fitting includes structuring sparse matrix of location information and recovering the location information matrix by LRMR algorithm.The simulation results show that the method based on modified LRMR algorithm is feasible and can obtain stable recovery effect under different sampling proportions,where the modified LRMR algorithm is superior to the existing LRMR algorithms on operating time.%在无线传感器网络(WSN)节点轨迹拟合中,由于频繁传输传感器节点的位置信息会增加网络能量消耗,为解决上述问题,提出一种低秩矩阵恢复算法(LRMR)的节点轨迹拟合方法,即对轨迹信息进行稀疏采样来降低信息传输量以达到节能目的,并研究一种改进的LRMR算法以提高运行速度,即在迭代中对单一低秩矩阵与噪声矩阵作局部粗寻优,对恢复矩阵中的元素作全局细寻优.轨迹拟合方法包括构造采样节点位置信息的稀疏矩阵,可采用改进LRMR算法进行恢复.仿真结果表明,基于改进LRMR的节点轨迹拟合方法是切实可行的,在不同的采样比例下都可取得稳定的恢复效果,改进的LRMR算法在运行时间上优于现有的LRMR算法,为信号传输节能设计提供了依据.