Drone-Assisted IRS System in 5G and Beyond: Improving Reliability and Enhancing the Network Life Span

This paper proposes an drone-assisted intelligent reflecting surface (IRS) for device-to-device (D2D) communication in infrastructure-less scenarios. The aim of this paper is to enhance the reliability among D2D ground users (GUs) and extend the lifespan of 5G and beyond 5G (B5G) wireless communication system. This work may be applicable for packet delivery in bustling urban areas, especially where ground-to-ground (G2G) links are in deep fade. For modeling air-to-ground (A2G) links among GUs to IRS/drone and IRS/drone to GUs, we consider a height-dependent Nakagami-$m$ channel model for small-scale fading and height-dependent path-loss exponent for modeling large-scale fading. The lifespan of the network is improved by proposing height-dependent energy harvesting (EH) at drone. We derive the cumulative distribution function (CDF) of the signal-to-noise ratio (SNR) whenever the signal reaches the receiving node, either via drone or via IRS. We also develop the expression of spectral efficiency and derive a closed-form expression of an outage probability by taking the combined effect of the signal for the proposed scenario using decode-and-forward (DF) and amplify-and-forward (AF) relaying at the drone. Additionally, the statistical parameters such as mean, variance, and probability density function (PDF) of total noise are derived, which is useful at the receiver node for estimating the bit error rate (BER). The analytical result is validated with simulation results, and the work is compared with the existing state-of-the-art.