Re-thinking polynomial optimization: Efficient programming of reconfigurable radio frequency (RF) systems by convexification

Abstract

Reconfigurable radio frequency (RF) system has emerged as a promising avenue to achieve high communication performance while adapting to versatile commercial wireless environment. In this paper, we propose a novel technique to optimally program a reconfigurable RF system in order to achieve maximum performance and/or minimum power. Our key idea is to adopt an equation-based optimization method that relies on general-purpose, non-convex polynomial performance models to determine the optimal configurations of all tunable circuit blocks. Most importantly, our proposed approach guarantees to find the globally optimal solution of the non-convex polynomial programming problem by solving a sequence of convex semi-definite programming (SDP) problems based on convexification. A reconfigurable RF front-end example designed for WLAN 802.11g demonstrates that the proposed method successfully finds the globally optimal configuration, while other traditional techniques often converge to local optima.