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ChaoQun Wu
Heilongjiang Institute of Technology

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Signal Detection Based on Particle Swarm Optimization for MIMO-OFDM System ChaoQun Wu; Dan Zhao; JingPeng Gao
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In order to overcome the defects of the slow convergence rate of the traditional Genetic Algorithm and basic Particle Swarm Optimization drops into local optimum easily, an improved Particle Swarm Optimization algorithm based on hybrid algorithm is proposed and applied to the signal detection for MIMO-OFDM system. The algorithm optimizes the basic Particle Swarm Optimization algorithm and some problems were solved by means of Particle Swarm Optimization combined with Genetic Algorithm for signal detection. Through the theoretical analysis and the simulation research, this improved algorithm is superior to basic Particle Swarm Optimization algorithm 0.5dB under the same number of iterations and is better than traditional Genetic Algorithm 0.5dB under the same bit error rate. This algorithm improves the system signal detection performance effectively with less iteration and reduces the bit error rate. It has rapid speed of convergence and strong capability of global search. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.5105
A Joint Synchronization and Channel Estimation Algorithm for MIMO-OFDM System JingPeng Gao; DanFeng Zhao; ChaoQun Wu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

As conventional methods deal with channel estimation and synchronization separately, they can’t achieve the best performances because the unknown parameters will interfere with each other. Besides, the convergence speed is slow using expectation maximization algorithm. Thus in this paper, we propose a joint synchronization and channel estimation method in MIMO-OFDM systems. The algorithm achieves coarse estimation by using a preamble. Then by combining this algorithm with SAGE algorithm and using joint iteration technology, time-frequency synchronization and channel estimation is achieved. Consequently, the performance of the system is enhanced. Theoretical researches and simulation results show that the algorithm can obtain relatively perfect result of time-frequency synchronization and channel estimation with fewer iterative times. Meanwhile our algorithm can approach the ideal case of perfect channel estimation and synchronization with lower complexity. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3679
Co-Authors Dan Zhao DanFeng Zhao JingPeng Gao