天作之合：智能分布式通信网络的实用压缩感知和网络编码
Match Made in Heaven: Practical Compressed Sensing and Network Coding for Intelligent Distributed Communication Networks
摘要：
基于网络编码和压缩感知范式分别带来的令人印象深刻的功能，将它们结合在一起的想法将在即将到来的5G网络中产生重大改进和影响。在这种情况下，本文的目的是评估这些关键技术在基于簇的无线传感器网络的有效性，在存在的时间和空间的相关性。我们的目标是实现更好的压缩增益，通过应用时间压缩，以及减少在网络中使用实域网络编码的传输总数进行的总负载按比例缩小。为了进一步减少传输的数量，簇头执行低复杂度的空间预编码，包括以一定的概率发送分组。此外，我们比较我们的方法与基准计划。正如预期的那样，我们在NS3模拟器上运行的数值结果表明，总体上我们的方案显着下降了所考虑的集群拓扑结构中的传输数据包的数量具有非常高的重建SNR。
英文摘要：
Based on the impressive features that network coding and compressed sensing paradigms have separately brought, the idea of bringing them together in practice will result in major improvements and influence in the upcoming 5G networks. In this context, this paper aims to evaluate the effectiveness of these key techniques in a cluster-based wireless sensor network, in the presence of temporal and spatial correlations. Our goal is to achieve better compression gains by scaling down the total payload carried by applying temporal compression as well as reducing the total number of transmissions in the network using real field network coding. In order to further reduce the number of transmissions, the cluster-heads perform a low complexity spatial pre-coding consisting of sending the packets with a certain probability. Furthermore, we compare our approach with benchmark schemes. As expected, our numerical results run on NS3 simulator show that on overall our scheme dramatically drops the number of transmitted packets in the considered cluster topology with a very high reconstruction SNR.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
