Abstract

Modern mobile telecommunication systems are using MIMO combined with OFDM, which is known as MIMO-OFDM systems, to provide robustness and higher spectrum efficiency. The major challenge in this scenario is to obtain an accurate channel estimation to detect information symbols, once the receiver must have the channel state information to equalize and process the received signal. Channel estimation is an essential task in MIMO-OFDM systems for coherent demodulation and data detection. Also designing pilot tones that affect the channel estimation performance is an important issue for these systems. For this reason, in this study we propose a Hybrid optimization algorithm (HBFOMCS) based on Bacterial Foraging Optimization (BFO) and Modified Cuckoo Search algorithm (MCS) to optimize placement of the pilot tones that are used for Least Square (LS) channel estimation in MIMO-OFDM systems. Simulation results show that designing pilot tones using the hybrid algorithm outperforms other considered placement strategies in terms of high system performance and low computational complexity.

Keywords:

BFO algorithm , channel estimation, hybrid algorithm , LS channel estimation , MCS algorithm , MIMO OFDM,

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Competing interests

The authors have no competing interests.

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