e-space
Manchester Metropolitan University's Research Repository

Reconfigurable Intelligent Surface Enabled IoT Networks in Generalized Fading Channels

Makarfi, Abubakar and Rabie, Khaled and Kaiwartya, Omprakash and S. Badarneh, Osamah and Li, Xingwang and Kharel, Rupak (2020) Reconfigurable Intelligent Surface Enabled IoT Networks in Generalized Fading Channels. In: IEEE International Conference on Communications (ICC) 2020, 07 June 2020 - 11 June 2020, Dublin, Ireland.

[img]
Preview

Download (385kB) | Preview

Abstract

This paper studies an Internet-of-Things (IoT) network employing a reconfigurable intelligent surface (RIS) over generalized fading channels. Inspired by the promising potential of RIS-based transmission, we investigate a RIS-enabled IoT network with the source node employing a RIS-based access point. The system is modelled with reference to a receivertransmitter pair and the Fisher-Snedecor F model is adopted to analyse the composite fading and shadowing channel. Closedform expressions are derived for the system with regards to the average capacity, average bit error rate (BER) and outage probability. Monte-Carlo simulations are provided throughout to validate the results. The results investigated and reported in this study extend early results reported in the emerging literature on RIS-enabled technologies and provides a framework for the evaluation of a basic RIS-enabled IoT network over the most common multipath fading channels. The results indicate the clear benefit of employing a RIS-enabled access point, as well as the versatility of the derived expressions in analysing the effects of fading and shadowing on the network. The results further demonstrate that for a RIS-enabled IoT network, there is the need to balance between the cost and benefit of increasing the RIS cells against other parameters such as increasing transmit power, especially at low SNR and/or high to moderate fading/shadowing severity.

Impact and Reach

Statistics

Downloads
Activity Overview
2Downloads
15Hits

Additional statistics for this dataset are available via IRStats2.

Altmetric

Actions (login required)

Edit Item Edit Item