Optimization of pilot pattern in ACO-OFDM systems channel estimation based on compressed sensing

The application of asymmetrically clipped optical-orthogonal frequency division multiplexing (ACO-OFDM) in free-space optical (FSO) communication system can increase the system channel capacity, while the use of channel estimation technology can ensure that ACO-OFDM has better performance. Since the channel estimation performance is directly affected by the selection of pilot patterns, especially when using compressed sensing (CS), it has been a major task in OFDM transmission schemes. In order to improve the channel reconstruction accuracy, a hybrid optimization algorithm based on genetic algorithm (GA) and particle swarm optimization (PSO) algorithm is proposed for two types of pilot design criterion. Simulation results show that compared with other three algorithms, the proposed algorithm has faster convergence speed and lower convergence value. With the pilots designed by the proposed algorithm, the system can achieve higher channel reconstruction accuracy.