Two-Timescale Optimization for Intelligent Reflecting Surface Aided D2D Underlay Communication

TL;DR

This paper proposes a two-timescale optimization method for IRS-aided D2D underlay communication to enhance D2D rates while reducing channel training overhead, balancing performance and feedback complexity.

Contribution

It introduces a novel two-timescale optimization scheme that decouples IRS phase shift adaptation from beamforming and power control, improving system performance with lower CSI overhead.

Findings

Outperforms baseline schemes in D2D ergodic rate.

Achieves a good trade-off between performance and CSI overhead.

Closed-form solutions enable efficient iterative optimization.

Abstract

The performance of a device-to-device (D2D) underlay communication system is limited by the co-channel interference between cellular users (CUs) and D2D devices. To address this challenge, an intelligent reflecting surface (IRS) aided D2D underlay system is studied in this paper. A two-timescale optimization scheme is proposed to reduce the required channel training and feedback overhead, where transmit beamforming at the base station (BS) and power control at the D2D transmitter are adapted to instantaneous effective channel state information (CSI); and the IRS phase shifts are adapted to slow-varying channel mean. Based on the two-timescale optimization scheme, we aim to maximize the D2D ergodic rate subject to a given outage probability constrained signal-to-interference-plus-noise ratio (SINR) target for the CU. The two-timescale problem is decoupled into two sub-problems, and the two sub-problems are solved iteratively with closed-form expressions. Numerical results verify that the two-timescale based optimization performs better than several baselines, and also demonstrate a favorable trade-off between system performance and CSI overhead.