认知无线电网络的干扰信道学习算法

Interference Channel Learning Algorithm in Cognitive Radio Networks

认知无线电网络的信道受到干扰情况下,学习性能不好,导致信道失衡。传统的认知无线电网络的干扰信道学习算法采用多模盲均衡宽带压缩频谱联合特征识别算法,当干扰强度较大时,学习均衡性能不好。提出一种基于线性预编码设计的协作频谱共享的认知无线电网络的干扰信道学习算法。通过协作中继方式在服务PU的同时获得传输机会,并给出了PU/SU联合优化的预编码矩阵进行算法改进,采用Jakes功率谱,组成新的云计算联合服务器接收端和发射端节点定位训练序列,将PU、SU预编码矩阵设计问题分解,采用干扰信道学习算法,得到正交通信信道载波均衡控制方程,实现干扰信道的学习算法改进。仿真结果表明,本文算法能有效提高信道学习性能,抗干扰能力增强,吞吐率比传统方法提高35%,展示较好的网络通信性能。

The channel of cognitive radio network interference case, learning performance is not good, leading to channel im?balance. Interference channel learning algorithm in cognitive radio network with the traditional multi modulus blind equal?ization broadband compressed spectrum combined with feature recognition algorithm, when the interference power is larger, learning the equalization performance is not good. Propose a cooperative spectrum sharing interference channel design of Linear Precoding based on cognitive radio networks learning algorithm. Through the cooperative relay mode in the service of PU and obtain the transmission opportunity, and gives the joint optimization of PU/SU precoding matrix improved algo?rithm, using Jakes power spectrum calculation, combined with the server receives the end and the transmitting end node lo?calization training sequence to form a new cloud, PU, SU precoding matrix design problem decomposition, using the inter?ference channel study algorithm, obtained positive communication channel carrier equilibrium control equation, realization of improved learning algorithm of interference channels. The simulation results show that this algorithm can effectively im?prove the channel, learning performance, enhance the ability of anti jamming, throughput increases 35%compared with the traditional method shows better performance, network communication.