结合频域均衡(FDE)研究了在频率选择性衰落信道下基于虚拟 MIMO-STBC 的无线传感器网络的功率分配(PA)方案。利用从目标簇反馈回信源簇的信道状态信息,在协同传输节点总发送功率一定的情况下,通过最大化信宿节点接收到数据的信噪比推导出了一种基于滤波器组频域加权的 PA 方案。仿真结果表明,在系统一定的误码率要求下,采用这种 PA 方案的无线传感器网络所需要的发射功率要少于等 PA 方案所需要的发射功率,从而减少了无线传感器网络的能耗。
提出了一种基于分布式空时分组编码的译码转发(DSTBC-DF)的新的协同分集方案,设计了适合协同分簇多跳无线传感网的网络协议,并讨论了协同同步情况,分析了协同分集方案的性能和协同分簇无线传感网的能量效率。理论分析与 Mento Carlo 仿真的结果验证了这一新方案的有效性:相比传统的方案,不但实现简单,而且通过合理的协议设计有效地解决了协同同步问题,实现了完全的分集增益,有更高的能量效率,网络系统能耗明显降低。
A novel statistical method based on particle filtering is presented for multiple vehicle acoustic signals separation problem in wireless sensor network. The particle filtering method is able to deal with non-Gaussian and nonlinear models and non-stationary sources. Using some instantaneously mixed observations of several real-world vehicle acoustic signals, the proposed statistical method is compared with a conventional non-stationary Blind Source Separation algorithm and attractive simulation results are achieved. Moreover, considering the natural convenience to transmit particles between sensor nodes, the algorithm based on particle filtering is believed to have potential to enable the task of multiple vehicles recognition collaboratively performed by sensor nodes in distributed wireless sensor network.
