AN ADAPTIVE APPROACH TO ESTIMATE CHANNEL OF MIMO-OFDM SYSTEMS IN MULTIPATH FADING CHANNELS
Keywords:
BER, Kalman Filter, LMS, MIMO, OFDM, Rayleigh Fading Channel, RLS, SNR, OSTBAbstract
Channel estimation plays a crucial role in wireless communication as it significantly enhances system performance. MIMO-OFDM systems, which involve multiple antennas at the sender and receiver sides, utilize adaptive channel estimation techniques such as Least Mean Square, Recursive Least Square, and Kalman filtering. These techniques have been applied in the Rayleigh and Rician fading channels, with various diversity configurations like 2x1, 2x2, 2x3, and 2x4. Among these configurations, the high order diversity system, specifically 2x4, demonstrates the best performance in terms of bit error rate (BER). Simulation results indicate that Recursive Least Square outperforms Least Mean Square, while the Kalman filter surpasses both LMS and RLS techniques. The impact of Doppler shifts on different MIMO systems has been studied to analyze the system's time-varying environment, and throughput analysis has been conducted. Performance evaluation is based on bit error rate versus signal-to-noise ratio (SNR) and throughput versus SNR. In terms of computational complexity, the LMS algorithm is less complex than both the RLS and Kalman filter algorithms. The proposed method has been verified through simulations.
KeywordsReferences
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