Research On PAPR Reduction Optimization Algorithm In OFDM Systems

The orthogonal frequency division multiplexing (OFDM) is available to resist multipath fading, can eliminate Inter-Symbol Interference (ISI) and also has high rate of frequency utilization. It has been successfully applied in the current mobile communication systems, such as the digital audio and video broadcasting system. It has been one part of wireless local area network standard. So OFDM has been applied increasingly in the field of wireless communication. For the reason that OFDM system consists several orthogonal sub-carrier mutually, the signal which is overlaid in the time domain has high peak to average power ratio (PAPR). High PAPR value needs large linear range for amplifier, and limits the development of OFDM technique. In conclusion, the study of PAPR reduction technique has theoretical meaning and practical significance.At the first, the basic principle of the OFDM technique is introduced, while we compare the multicarrier modulation system with single carrier modulation system about performance. Next, the core technique of OFDM system is explained. The main content is to deeply analyze the reason of PAPR causing and PAPR have wide impact on the system performance. On the base of the above, many kinds of PAPR reduction technique are studied, which support theoretical foundation for the proposed PAPR reduction algorithm. For the partial transmit sequence (PTS) technique, searching the optimal phase factor can be seen as the global optimization problem, so it can be improved by the modern global optimization algorithm to achieve high PAPR reduced.On the basis of studying the modern optimization algorithms, combining the strong global search ability of genetic algorithm (GA) with the strong local search ability of simulated annealing algorithm (SA), the simulated annealing genetic algorithm (GSA) is introduced, which not only ensures the algorithm has strong global search capability, but also effectively avoids the algorithm converging to the local optimal solution. The simulated annealing genetic algorithm is applied to the partial transmit sequence algorithm, then GSA-PTS algorithm is proposed, which can solve the optimal phase factor, and can search the phase factor fast. The proposed algorithm can effectively reduce the peak to average ratio, and has advantages of fast convergence rate, low computing complexity and low bit to error ratio. In order to avoid breaking the diversity of population, the partheno-crossover is introduced, and then the PCGSA-PTS algorithm is put forward. Simulation results demonstrate the effectiveness of the proposed two algorithms.