# Multi-tone Signal Optimization for Wireless Power Transfer in the Presence of Wireless Communication Links

## TL;DR

This paper develops optimized multi-tone signals for wireless power transfer systems that account for non-linear energy harvesting models and coexistence with communication links, improving efficiency and reducing interference.

## Contribution

It introduces a second-order polynomial model for optimizing multi-tone signals across various energy harvesters and proposes globally optimal solution methods for the non-convex optimization problem.

## Key findings

- Significant improvement in power transfer efficiency demonstrated.
- Effective coexistence with communication links by constraining received power.
- Comparison shows superiority over existing methods.

## Abstract

In this paper, we study optimization of multi-tone signals for wireless power transfer (WPT) systems. We investigate different non-linear energy harvesting models. Two of them are adopted to optimize the multi-tone signal according to the channel state information available at the transmitter. We show that a second-order polynomial curve-fitting model can be utilized to optimize the multi-tone signal for any RF energy harvester design. We consider both single-antenna and multi-antenna WPT systems. In-band co-existing communication links are also considered in this work by imposing a constraint on the received power at the nearby information receiver to prevent its RF front end from saturation. We emphasize the importance of imposing such constraint by explaining how inter-modulation products, due to saturation, can cause high interference at the information receiver in the case of multi-tone signals. The multi-tone optimization problem is formulated as a non-convex linearly constrained quadratic program. Two globally optimal solution approaches using mixed-integer linear programming and finite branch-and-bound techniques are proposed to solve the problem. The achieved improvement resulting from applying both solution methods to the multi-tone optimization problem is highlighted through simulations and comparisons with other solutions existing in the literature.