Performance of a Relay-Assisted Hybrid FSO/RF Communication System

TL;DR

This paper analyzes the performance of a relay-assisted hybrid FSO/RF communication system, deriving new closed-form expressions for BER and outage probability under various atmospheric conditions, and compares fixed and adaptive gain relays.

Contribution

It is the first study to examine the impact of user number and atmospheric turbulence on hybrid FSO/RF systems, providing novel analytical expressions and performance insights.

Findings

Adaptive gain relay is less sensitive to user number.

Fixed gain relay performs better in worst-case scenarios.

Derived closed-form BER and outage probability expressions verified by simulations.

Abstract

This paper investigates performance of a relay assisted hybrid Free Space Optical / Radio Frequency (FSO/RF) communication system. The proposed structure is particularly recommended anywhere that direct RF communication between mobile users and base station is not possible due to atmospheric conditions. In this system, a multiuser RF link connects mobile users to relay and a FSO link connects relay to the base station. It is the first time that effect of number of users within the cell, on the performance of such structure, is investigated. Also it is the first time that performance of a dual hop hybrid FSO / RF system is investigated in Negative Exponential atmospheric turbulence. Considering wide range of atmospheric turbulence regimes, from moderate to saturated, for the first time, closed-form expressions are derived for Bit Error Rate (BER) and outage probability (P_out) of the proposed structure. MATLAB simulations verified accuracy of the derived expressions. Considering fixed and adaptive gain amplify and forward protocols at relay, it is shown that adaptive gain relay is less sensitive to the number of users within the cell. It is also shown that fixed gain relay, despite its low complexity, has better performance; because its gain is adjusted such that the performance be favorable even at the worst case scenario.