A PSO-Based Hybrid Adaptive Equalization Algorithm for Asynchronous Cooperative Communications
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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.
KeywordsEqualization algorithm Particle swarm optimization Least mean square Rayleigh flat fading channel Asynchronous cooperative communications
This work was supported by the China Postdoctoral Science Foundation under Grant 2017M623129. The work was also supported in part by Natural Science Foundation of China and in part by the Fundamental Research Funds for the Central Universities under Grant JB180112, and also in part by the Program of Introducing Talents of Discipline to Universities under Grant B08038.
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