Peak-to-Average Power Ratio Reduction Using New Swarm Intelligence Algorithm in OFDM Systems
| Autor: | Halaoui Mustapha, Asselman Adel, Elyaakoubi Ali, Ahyoud Saida, Amhaimar Lahcen, Attari kamal |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computational complexity theory Orthogonal frequency-division multiplexing Computer science Particle swarm optimization 02 engineering and technology Swarm intelligence Industrial and Manufacturing Engineering Reduction (complexity) 020303 mechanical engineering & transports 020901 industrial engineering & automation 0203 mechanical engineering Transmission (telecommunications) Artificial Intelligence Simulated annealing Algorithm Data transmission |
| Zdroj: | Procedia Manufacturing. 32:831-839 |
| ISSN: | 2351-9789 |
| DOI: | 10.1016/j.promfg.2019.02.291 |
| Popis: | The multicarrier modulation of orthogonal frequency division multiplexing (OFDM) is one of the best choices, which has lead to achieve significant advancement for high data rate transmission in wireless communication systems. However, OFDM suffer from some obstacles during data transmission, the main one is the high peak-to-average power ratio (PAPR), which leads to saturate the power amplifier, generate more interference and reduced resolution of nonlinear components like digital/analog converters. The partial transmit sequence (PTS) technique is a flexible and efficient way used to solve the PAPR problem for OFDM systems, but the main drawback of PTS technique is the high computational complexity caused by the exhaustive search of phase. Therefore, this paper proposed a reduced computational complexity PTS scheme, based on a straightforward strategy of Fireworks Algorithm (FWA) to reduce PAPR in WLAN/OFDM system. The FWA is a new swarm intelligence algorithm, able to achieve an effective optimization research with a low complexity phase weighting process implementation. The simulation results base on WLAN 802.11a standard confirmed the adequacy and the effectiveness of the proposed method (PTS-FWA) in PAPR reduction with less computational complexity even the number of sub-blocks is increased. Moreover it turns out from the results that the new scheme (PTS-FWA) performs very well and clearly outperforms the conventional algorithm like Genetic Algorithm (GA), particle swarm optimization (PSO) and simulated annealing (SA). |
| Databáze: | OpenAIRE |
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