Nature Inspired Approach Toward Elimination of Nonlinearities in SWIPT Enabled Energy Harvesting Networks

Autor: Ajin R. Nair, S. Kirthiga
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: IEEE Access, Vol 10, Pp 100837-100856 (2022)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2022.3208157
Popis: The greatest challenge faced by the Simultaneous Wireless Information and Power Transfer (SWIPT) system during implementation is hardware impairment. This article proposes a bio-inspired digital pre-distortion scheme to overcome the high power amplifier nonlinearity and in-phase and quadrature imbalances in the SWIPT system. Here, the memory polynomial model characterises the high power amplifier. The digital pre-distortion algorithm uses the latest bio-inspired methods: Dingo Optimization, Jumping Spider Optimization, Seagull Optimization, Mexican Axolotl Optimization, and Black Widow Optimization. The power conversion efficiency, harvested energy, and rate energy region at the receiver side analyse the efficiency of bio-inspired digital pre-distortion enabled SWIPT. Among the various bio-inspired algorithms, the Seagull Optimisation Algorithm gave a maximum harvested energy of $35.95~\mu \text{W}$ , keeping a Bit Error Rate of $1.33 \times 10^{-6}$ for the 32-QAM scheme. The Seagull Optimisation Algorithm also showed a maximum improvement of 6.45% in power conversion efficiency compared to the conventional digital pre-distortion scheme.
Databáze: Directory of Open Access Journals