Advanced Nonlinear Optimization Techniques in SWIPT: A Review

With an emphasis on nonlinear models for energy harvesting (EH), this article examines nonlinear approaches in advanced optimization for simultaneous wireless information and power transfer (SWIPT). The SWIPT technology suffers from optimizing system performance due to its non-linearity EH complicated nature. In this review, the aim is to investigate the current trends in the field of nonlinear optimization in SWIPT and assess the efficiency of these technologies as well as their performances, challenges and limitations. The obtained findings reveal that there has been a clear shift towards using non-linear optimization approaches that have greater accuracy when it comes to modelling EH processes compared to traditional linear methods which have been used for a long time. These techniques show superior energy efficiency (EE), data rate, and security improvements. However, significant computational complexity is involved while trying to model accurately such hybrid communication systems which integrate machine learning (ML) algorithms or Intelligent Reflecting Surfaces (IRS). This paper has three main objectives, the first is to conduct a literature review on advanced nonlinear optimization techniques employed in SWIPT to trace their evolution, the second is to critically assess the effectiveness and performance of various non-linear optimization techniques in order to improve SWIPT system capabilities, and the third is synthesizing the challenges and difficulties encountered in applying nonlinear optimization techniques in SWIPT and derives new ideas that can fully leverage all benefits offered by SWIPT in future wireless networks such as developing low-complexity algorithms, refining nonlinear EH models using empirical data and advanced simulations, simplifying integrations with IRS and ML