徐向艺, 薛瑞. 基于粒子群适应度控制的通信信道均衡优化算法[J]. 微电子学与计算机, 2015, 32(7): 138-141,146. DOI: 10.19304/j.cnki.issn1000-7180.2015.07.032
引用本文: 徐向艺, 薛瑞. 基于粒子群适应度控制的通信信道均衡优化算法[J]. 微电子学与计算机, 2015, 32(7): 138-141,146. DOI: 10.19304/j.cnki.issn1000-7180.2015.07.032
XU Xiang-yi, XUE Rui. Communication Channel Equalization Optimization Algorithm Based on Particle Swarm Adaptive Control[J]. Microelectronics & Computer, 2015, 32(7): 138-141,146. DOI: 10.19304/j.cnki.issn1000-7180.2015.07.032
Citation: XU Xiang-yi, XUE Rui. Communication Channel Equalization Optimization Algorithm Based on Particle Swarm Adaptive Control[J]. Microelectronics & Computer, 2015, 32(7): 138-141,146. DOI: 10.19304/j.cnki.issn1000-7180.2015.07.032

基于粒子群适应度控制的通信信道均衡优化算法

Communication Channel Equalization Optimization Algorithm Based on Particle Swarm Adaptive Control

  • 摘要: 非线性通信系统广泛应用在无线通信和网络通信中,非线性通信系统由于强干扰环境影响,信道均衡效果不好.提出一种基于粒子群适应度控制频段直扩配准的强干扰环境下非线性通信信道均衡控制算法.首先构建强干扰环境下的非线性通信系统信道模型,设计非线性MIMO输入均衡器模块、信道估计模块和信道盲均衡模块,采用最速梯度下降法进行信道抗干扰分析,采用大赫兹频段的移相键控直扩方法控制步长的变化速度和取值范围,基于粒子群适应度控制方法对通信信号进行卷积测度提取,实现信道均衡算法改进.仿真结果表明,采用该方法进行非线性通信信道均衡,具有较低的误比特率,均衡误差最少,剩余码间干扰低,抗干扰能力和收敛性优于传统方法.

     

    Abstract: The nonlinear communication system has been widely used in wireless communication and network communication, nonlinear communication system because of the influence of strong interference environment, channel equalization effect. A method based on particle swarm to control band straight under strong interference environment the extended registration nonlinear communication channel equalization control algorithm is proposed in this paper. Firstly, build the model of nonlinear communication system channel under strong interference environment, the design of nonlinear MIMO equalizer's input module, the channel estimation module and channel blind equalization module, uses the steepest gradient descent method for channel analysis of anti interference, the terahertz wave band phase shift keying direct sequence spread spectrum method step speed change and range control, particle swarm to control method of measure convolution extraction of communication signals, to achieve an improvement in channel equalization algorithm based on. Simulation results show that using the method of nonlinear communication channel equalization and has a lower bit error rate, balanced error at least, the residual inter symbol interference is low, anti-interference ability and convergence is superior to the traditional method.

     

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