Energy-Efficient Beamforming Design for Integrated Sensing and Backscatter Communication

This letter presents a novel energy efficiency (EE) beamforming optimization framework for an integrated sensing and backscatter communication (ISABC) system featuring multiple backscatter tags and multiple downlink users. Unlike existing ISABC models that mainly focus on either communication rate or transmit power, we formulate a fractional programming (FP) problem to maximize the EE by jointly optimizing the communication and sensing beamforming vectors under the constraints of power budget, reliable decoding conditions, and quality of service (QoS) requirements. To address this highly non-convex problem with nested fractional structures, we adopt a dual quadratic transform-based alternating optimization (AO) algorithm, which decouples the outer EE ratio and the inner signal-to-interference-plus-noise ratio (SINR), enabling efficient convex reformulation and solution. Numerical simulations verify that the proposed algorithm achieves up to 50% higher EE than the conventional Dinkelbach-based method while maintaining comparable computational complexity, demonstrating its effectiveness and practicality for green ISABC network design.