Energy-Efficient Resource Allocation in Multiuser OFDM Systems with Wireless Information and Power Transfer

TL;DR

This paper proposes an iterative resource allocation algorithm for multiuser OFDM systems that maximizes energy efficiency while satisfying data rate and power transfer requirements, leveraging nonlinear fractional programming and dual decomposition.

Contribution

It introduces a novel algorithm that optimally allocates resources in multiuser OFDM systems for simultaneous wireless information and power transfer, considering practical constraints.

Findings

The algorithm achieves maximum energy efficiency in simulations.

Energy efficiency and system capacity improve with multiple users.

Wireless power transfer benefits from optimized resource allocation.

Abstract

In this paper, we study the resource allocation algorithm design for multiuser orthogonal frequency division multiplexing (OFDM) downlink systems with simultaneous wireless information and power transfer. The algorithm design is formulated as a non-convex optimization problem for maximizing the energy efficiency of data transmission (bit/Joule delivered to the users). In particular, the problem formulation takes into account the minimum required system data rate, heterogeneous minimum required power transfers to the users, and the circuit power consumption. Subsequently, by exploiting the method of time-sharing and the properties of nonlinear fractional programming, the considered non-convex optimization problem is solved using an efficient iterative resource allocation algorithm. For each iteration, the optimal power allocation and user selection solution are derived based on Lagrange dual decomposition. Simulation results illustrate that the proposed iterative resource allocation algorithm achieves the maximum energy efficiency of the system and reveal how energy efficiency, system capacity, and wireless power transfer benefit from the presence of multiple users in the system.