Research On Channel Equalization Of Communication Between WSN Nodes

As a new communication technology, wireless sensor network (WSN), gradually penetrated into all areas of life, which has vast applied prospects. Sensor node energy and computation ability is limited, once it is deployed, it cannot charge or replace. Furthermore, wireless transmission bandwidth is narrow between the nodes. Therefore, how to improve energy utilization and bandwidth utilization in data transmission is very important.In addition, the bad wireless sensor network communication environment and the severe inter-symbol interference caused by coupling effect and multiple access interference makes transmission characteristics of the communication channel very complex and the data communication between nodes not stable. In order to reduce the error rate and improve the quality of communication, it is necessary to use technology to the communication channel to compensate a balance and eliminate inter-symbol interference. Therefore, how to get efficient channel equalization under the limited condition of nodes energy and bandwidth for wireless sensor network is important.Firstly, the paper briefly introduces the wireless sensor network and the development status of existing wireless communication channel equalization. Secondly, the principle of equalization is described in detail. The realization of several typical blind equalization algorithms is analyzed and deduced. On this basis, this paper proposes an enhanced fractionally spaced constant modulus algorithm, then analyzes and deduces this algorithm. Finally, the paper compares the equalization performance of several typical blind equalization algorithm and enhanced algorithm by MATLAB simulation experiments. A large number of experimental analyses and performance comparisons prove that the enhanced algorithm can reduce noise amplification and sensitivity of the timing phase and eliminate inter-symbol interference. The enhanced algorithm has significantly improved the performance of the convergence rate, the residual mean square error, the robustness, and equalization, which has improved to some extent. It is more suitable for wireless sensor network of which the inter-symbol interference is serious.