GSA based PSO-PTS model for PAPR reduction in OFDM and MIMO-OFDM Systems
Demand of wireless communication is increasing rapidly due to their significant use in daily life scenario. This increased demand has led towards the urge of efficient communication to meet the user requirements. Currently, Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing (MIMO-OFDM) has gained attraction from research community, and industries to improve the communication. The MIMO-OFDM technique helps to mitigate the interference among multiple users and improves the communication performance. However, during transmission, the power consumption remains a challenging task which increases Peak to Average Power Ratio (PAPR). This increment in PAPR reduces the communication quality. Several techniques have been reported recently but these techniques suffer from computational complexity and fail to achieve the desired performance. In order to overcome these issues, we present a novel hybrid optimization scheme by combining Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The PSO scheme helps to achieve the optimal solution and GSA helps to minimize the search operation using local search mechanism. We have conducted an experimental study which shows a significant improvement in PAPR reduction. Moreover, a comparative study is also presented which shows that proposed approach achieves better performance when compared with existing techniques of PAPR reduction in MIMO-OFDM systems.