To reduce the peak-to-average power ratio (PAPR) in the orthogonal frequency division multiplexing (OFDM) transmission technique, several reduction approaches have been used. Among these is the selective mapping (SLM) scheme, and while having been highly adopted, its considerable computational complexity for optimum phase factors search is challenging for practical systems. To overcome this issue with SLM while still reducing the PAPR, a variety of optimization algorithms have been applied for optimal phase factors search. Limitations in all these algorithms include the need for specific parameters for peak performance and a decrease in effectiveness for complicated problems that have a significant number of variables. In this work, a novel optimization algorithm, called teaching-learning–based optimization (TLBO), featuring less computational effort and no algorithm-specific parameter requirement, is applied to reduce the PAPR of the OFDM signal. MATLAB simulation results demonstrate that the proposed TLBO-SLM method efficiently performs better than conventional SLM and previously applied optimization algorithms.
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HADJ ALI, T., HAMZA, A. Low-complexity PAPR reduction method based on the TLBO algorithm for an OFDM signal. Ann. Telecommun. 76, 19–26 (2021). https://doi.org/10.1007/s12243-020-00777-0
- Orthogonal frequency division multiplexing (OFDM)
- Peak-to-average power ratio (PAPR)
- Selective mapping (SLM)
- Teaching-learning based optimization (TLBO)