Optimization of Wireless Relaying With Flexible UAV-Borne Reflecting Surfaces

Abstract

This paper presents a theoretical framework to analyze the performance of integrated unmanned aerial vehicle (UAV)-intelligent reflecting surface (IRS) relaying system in which IRS provides an additional degree of freedom combined with the flexible deployment of full-duplex UAV to enhance communication between ground nodes.Our framework considers three different transmission modes: (i) UAV-only mode, (ii) IRS-only mode, and (iii) integrated UAV-IRS mode to achieve spectral and energy-efficient relaying. For the proposed modes, we provide exact and approximate expressions for the end-to-end outage probability, ergodic capacity, and energy efficiency (EE) in closed-form. We use the derived expressions to optimize key system parameters such as the UAV altitude and the number of elements on the IRS considering different modes. We formulate the problems in the form of fractional programming (e.g. single ratio, sum of multiple ratios or maximization-minimization of ratios) and devise optimal algorithms using quadratic transformations. Furthermore, we derive an analytic criterion to optimally select different transmission modes to maximize ergodic capacity and EE for a given number of IRS elements. Numerical results validate the derived expressions with Monte-Carlo simulations and the proposed optimization algorithms with the solutions obtained through exhaustive search. Insights are drawn related to the different communication modes, optimal number of IRS elements, and optimal UAV height.

Intelligent Reflecting Surfaces Assisted UAV Communications for IoT Networks: Performance Analysis

“…In [16], an IRS was mounted on a UAV where both transmit to a gUE that performs selection combining to select the bestreceived signal with three transmission modes: UAV only, IRS only, and IRS-assisted UAV. Based on this set up, closed-form expressions for the outage probability and the ergodic capacity were derived.…”

“…The aforementioned research contributions, except for [16], considered either distance-based path loss with Rician fading or dual-slope height path loss models with spatial channel models for the UAV-gUE link. In [16], an elevation angle dependent path loss exponent with a probability of LoS was utilized with an excess path loss component for the BS-UAV and UAV-gUE links. The considered probability of LoS is based on the UAV-gUE link [18] which may not apply to the BS-UAV link.…”

“…Furthermore, this mode of operation can be categorized based on whether the IRS is assisting the UAV [12] or the user on the ground [14], [15] as follows: open-Air -gUE or aUE-IRS-assisted UAV communications. In the second mode of operation (i.e., mounted), an IRS is mounted on a UAV to enhance the communication links [16], [17], [20], while in the last mode of operation (i.e., carried), an IRS is carried by the UAV [13].…”

Capacity Analysis of IRS-Based UAV Communications with Imperfect Phase Compensation

“…In addition to being considered separately, the synergy of IRSs and UAVs is considered as a promising solution for supporting reliable wireless communications in future generations such as the sixth generation (6G) and beyond [4], [12]. Fig.…”

A D2D assisted multi‐hop data dissemination protocol for inter‐UAV communication

“…Future Internet of Things (IoT) will use mobile nodes such as unmanned aerial vehicles (UAVs) equipped with sensors to efficiently collect data from different geographical areas. 1,2 UAVs offer two advantages in this regard: one is to collect data from a wide range of area due to their mobility, and second is to sense data from areas where installing sensors may be difficult. [3][4][5] Due to cost of placing UAVs, they may only be placed at strategic points for data collection.…”