Optimal Reflection Coefficients for ASK Modulated Backscattering from Passive Tags

TL;DR

This paper derives optimal reflection coefficients for ASK modulated backscatter tags to maximize energy harvesting while satisfying communication constraints, improving backscatter system efficiency by around 13%.

Contribution

It provides a closed-form solution for optimal reflection coefficients considering practical energy harvesting models and constraints, with validation through extensive simulations.

Findings

Optimal reflection coefficients derived for maximum harvested power.

Proposed binary-ASK modulation design offers practical insights.

Achieved 13% gain over benchmark in simulations.

Abstract

This paper studies backscatter communication (BackCom) systems with a passive backscatter tag. The effectiveness of these tags is limited by the amount of energy they can harness from incident radio signals, which are used to backscatter information through the modulation of reflections. To address this limitation, we adopt a practical Constant-Linear-Constant (CLC) energy harvesting model that accounts for the harvester's sensitivity and saturation threshold, both of which depend on the input power. This paper aims to maximize this harvested power at a passive tag by optimally designing the underlying M-ary amplitude-shift keying (ASK) modulator in a monostatic BackCom system. Specifically, we derive the closed-form expression for the global optimal reflection coefficients that maximize the tag's harvested power while satisfying the minimum symbol error rate (SER) requirement, tag sensitivity, and reader sensitivity constraints. We also proposed optimal binary-ASK modulation design to gain novel design insights on practical BackCom systems with readers having superior sensitivity. We have validated these nontrivial analytical claims via extensive simulations. The numerical results provide insight into the impact of the transmit symbol probability, tag sensitivity constraint, and SER on the maximum average harvested power. Remarkably, our design achieves an overall gain of around 13% over the benchmark, signifying its utility in improving the efficiency of BackCom systems. Moreover, our proposed solution methodology for determining the maximum average harvested power is applicable to any type of energy harvesting model that exhibits a monotonic increasing relationship with the input power.