Adaptive Channel Estimation for STBC-OFDM Systems Based on Nature-Inspired Optimization Strategies

被引：0

作者：

D'Orazio, Leandro ^{[1
]}

Sacchi, Claudio ^{[2
]}

Donelli, Massimo ^{[2
]}

机构：

[1] SIEMENS SpA, Ind Sector, Viale Piero & Alberto Pirelli 10, I-20128 Milan, Italy

[2] Dept Informat Engn & Comp Sci DISI, I-38050 Trento, Italy

来源：

MULTIPLE ACCESS COMMUNICATIONS | 2010年 / 6235卷

关键词：

Multiple Input-Multiple Output (MIMO) systems; Orthogonal Frequency Division Multiplexing (OFDM); Channel Estimation; Genetic Algorithm; Particle Swarm Optimization; DIVERSITY;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we propose an adaptive channel estimation methodology for Space-Time Block-Coded (STBC) OFDM systems, aided by nature-inspired evolutionary optimization strategies, namely: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The use of GA and PSO allows at increasing the convergence of adaptive channel estimation to the optimal MMSE solution with respect to state-of-the-art optimization methodologies based on the concept of deterministic gradient. As a result, system performances are greatly improved, with a clear advantage taken by PSO, both in terms of channel estimation accuracy, implementation ease, and reduced computational effort.

引用

页码：188 / +

页数：3

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