L. F. Abanto-Leon, G. H. A. Sim, M. Hollick, A. Boonkajay and F. Adachi, "SWAN: Swarm-Based Low-Complexity Scheme for PAPR Reduction," GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020, pp. 1-7, doi: 10.1109/GLOBECOM42002.2020.9322272.
Abstract:
Cyclically shifted partial transmit sequences (CS-PTS) has conventionally been used in SISO systems for PAPR reduction of OFDM signals. Compared to other techniques, CS-PTS attains superior performance. Nevertheless, due to the exhaustive search requirement, it demands excessive computational complexity. In this paper, we adapt CS-PTS to operate in a MIMO framework, where singular value decomposition (SVD) precoding is employed. We also propose SWAN, a novel optimization method based on swarm intelligence to circumvent the exhaustive search. SWAN not only provides a significant reduction in computational complexity, but it also attains a fair balance between optimality and complexity. Through simulations, we show that SWAN achieves near-optimal performance at a much lower complexity than other competing approaches.
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Funding Info:
This research is funded by the Deutsche Forschungsgemeinschaft (DFG) within the B5G-Cell project in SFB 1053 MAKI, and the LOEWE initiative (Hesse, Germany) within the emergenCITY centre. For the work at A*STAR, there was no specific funding for research done.