Resource Allocation for SWIPT in Multi-Service Wireless Networks

TL;DR

This paper introduces novel resource allocation strategies for SWIPT in multi-service wireless networks, aiming to enhance energy harvesting and data throughput while minimizing power consumption through innovative architectures and optimization techniques.

Contribution

It proposes a unique energy harvesting architecture without splitters, formulates optimization problems for energy and throughput maximization, and explores antenna selection techniques for improved energy efficiency.

Findings

Energy harvesting performance is improved with the proposed architecture.

Optimization solutions effectively balance data rate and energy harvesting.

Antenna selection enhances energy efficiency in multi-user networks.

Abstract

The novel resource allocation for simultaneous wireless information and power transfer (SWIPT) is presented as a means of not only helping to communicate and access information with increasing efficiency in the next generation of mobile data networks but also contributing to minimizing a network's overall power consumption by providing a green energy source. First, a unique architecture is proposed that harvests energy from an access point (AP) without the receiver needing a splitter. In the proposed system model, a portion of the spectrum is used for information decoding (ID) while the remaining portion is exploited for energy harvesting (EH) in an orthogonal frequency division multiple access (OFDMA) network. To investigate the performance gain, an optimization problem is formulated that maximizes the harvested energy of a multi-user single-cell OFDMA downlink (DL) network with SWIPT and also satisfies a minimum data-rate requirement for all users. A locally optimal solution for the underlying problem, which is essentially non-convex due to the coupling of the integer variable, is obtained by using optimization tools. Second, the proposed system model is improved in order to investigate the resource allocation problem of needing to maximize throughput based on the separated receiver architecture in an OFDMA multi-user multi-cell system that uses SWIPT. The resulting problem, which jointly optimizes the subcarrier assignment and power allocation, is a mixed-integer non-linear problem (MINLP) that is difficult to solve. Third, a state-of-the-art harvesting technique at the receiver that is based on receiver antenna selection with a co-located architecture is explored to optimize the energy efficiency (EE) of a SWIPT-enabled multi-cell multi-user OFDMA network. This is referred to as a Generalized Antenna-Switching Technique.