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首页> 外文期刊>Wireless personal communications: An Internaional Journal >A PSO-Based Hybrid Adaptive Equalization Algorithm for Asynchronous Cooperative Communications
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A PSO-Based Hybrid Adaptive Equalization Algorithm for Asynchronous Cooperative Communications

机译:一种基于PSO的混合自适应均衡算法,用于异步协作通信

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摘要

This paper proposes an adaptive equalization algorithm for asynchronous cooperative communications in ad hoc networks, where amplify-and-forward relays are adopted, each of which is equipped with single antenna. Adaptive equalization technique is carried out at the destination node in this paper to remove inter-symbol interference, which is caused by the retransmissions of the asynchronous relays. Least mean squares (LMS) has been regarded as an effective adaptive method, but it has difficulty in obtaining the optimal solution. In this paper, we present a hybrid adaptive scheme by combining particle swarm optimization (PSO) with conventional LMS algorithm, where PSO is utilized to search the optimal solution during the iterative process, and LMS is employed to avoid the local convergence, which is usually caused in PSO. Numerical simulation results show that, the proposed scheme outperforms conventional LMS algorithm in convergence performance over Rayleigh flat fading channel, and meanwhile, a signal-noise-ratio gain of 6 dB or so is obtained when BER is 10(-3).
机译:本文提出了一种自适应均衡算法,用于临时网络中的异步协作通信,其中采用放大和前进继电器,每个都配备有单天线。自适应均衡技术在本文中的目的节点处执行以去除符号间干扰,这是由异步继电器的重传引起的。最小均方(LMS)被认为是有效的自适应方法,但它难以获得最佳解决方案。在本文中,我们通过将粒子群优化(PSO)与传统的LMS算法组合,其中PSO用于在迭代过程中搜索最佳解决方案,使用LMS来避免局部会聚,这通常是在PSO引起。数值模拟结果表明,该方案优于瑞利扁平衰落通道的收敛性能中的常规LMS算法,同时,当BER为10(-3)时,获得6dB偶数的信噪比增益。

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