一种新的基于MQAM的PLNC去噪映射算法

New Physical Layer Network Coding Denoising Mapping Algorithm Based on MQAM

物理层网络编码(Physical Layer Network Coding,PLNC)在高阶幅度和相位调制中存在星座点模糊现象。针对这一问题提出了一种物理层网络编码去噪映射算法。在该算法中,中继节点对接收信号进行星座点重新布局,按一定规律将星座点合并,经过处理后的信号星座点降低了一半,进而下行链路的调制阶数也降低了一半,星座图相邻点之间的欧氏距离变大,系统误码率性能得到提高;且中继节点只需解调-重映射-调制,处理复杂度低。通过计算机仿真验证了该算法的有效性。

To overcome the problem of constellation points ambiguity in physical layer network coding(PLNC),this paper proposed a new QAM-based PLNC de-noising mapping scheme.In this scheme,the relay node rearranges the M-QAM constellation mapping,and merges the points of constellation according to a certain rule.Comparing with traditional scheme,this design reduces the number of constellation points nearly a half,which increases the Euclidean distance between adjacent points in the constellation,thus improves the BER performance.In addition,the relay node only needs demodulation-remapping-modulation,which significantly reduces the processing complexity.Simulation results show the effectiveness of our scheme.