Channel Estimation in OFDM System Using Walrus Optimization Algorithm

This paper proposes a novel nature-inspired approach, namely the Walrus Optimization Algorithm (WaOA), for the accurate estimation of channels in wireless communication systems. The approach does not require prior statistical knowledge of the channel. This study introduces the WaOA, a novel bio-inspired metaheuristic approach, to optimize channel estimation in OFDM systems without relying on prior statistical channel knowledge. A series of simulations are conducted in MATLAB to evaluate the effectiveness of the proposed Walrus Optimization Algorithm based channel estimation (WaOA-CE) algorithm in terms of BER and Mean Square Error (MSE) criteria, and to compare it with conventional methodologies such as Minimum Mean Square Error (MMSE) and Least Squares (LS) algorithms. It shows that the algorithm performs very competitively compared to the MMSE algorithm and achieves significantly superior results compared to the LS algorithm. The requirement of the MMSE algorithm for prior knowledge of channel statistics either reduces its practical usability or leads to high computational complexity. Therefore, the proposed WaOA-CE is an effective and promising alternative to overcome the challenges of channel estimation.