Pilot design optimization of OTFS system based on genetic algorithm

Abstract

The Orthogonal Time Frequency Space (OTFS) system has attracted significant research attention due to its superior performance in handling time-frequency doubly dispersive channels in high-mobility scenarios. As key reference signals for channel estimation, the design of pilots in the delay-Doppler (DD) domain crucially influences the final estimation accuracy. To address the issues of limited estimation accuracy and poor adaptability in existing pilot distribution schemes, this paper proposes a pilot distribution scheme based on a genetic algorithm. This scheme leverages reasonable channel prior information and efficiently searches for the optimal pilot positions and quantity in the DD domain through a genetic optimization process, aiming to minimize the channel estimation mean square error. In this process, a multi-objective fusion fitness function is designed and optimized jointly with the pilot count to balance channel estimation performance against pilot overhead; prior-fused initialization and selection operations are employed to narrow the search space and improve computational efficiency; an adaptive adjustment mechanism for crossover and mutation probabilities is introduced to balance global exploration and local exploitation; and elite retention coupled with local fine-tuning is applied to accelerate convergence and avoid premature stagnation. Simulation results demonstrate that the proposed scheme improves channel estimation performance compared to traditional pilot distribution methods, without significantly increasing computational time.