Optimisation of Intelligent Reflecting Surfaces in 5G & Beyond Access and Backhaul Networks

With 5G and beyond networks, energy consumption and operational costs go up because of a focus on network densification. New technologies are needed for better resource management. In spite of the access network’s ability to handle large amounts of traffic, the backhaul network has slowed cellular network growth and efficiency. Even though passive fibre-optic networks are generally available in the backhaul network, capital expenditures and indirect operating costs hamper ultradense deployments. The use of mmWave links as a backhaul management option in the light of network softwarization (Software Defined Networking, SDN) may be
one way to combat the above issue, but this may not be the best solution since there is a possibility of NLOS communication in the mmWave backhaul link due
to various obstacles, such as densely situated base stations and transceivers located at low heights, such as street lights. Essentially, the above-mentioned issue can
be resolved by using Intelligent Reflecting Surfaces (IRS), also known as software-controlled metasurfaces, on the backhaul side, which will allow signals to travel from
the source base station to the destination base station even in the absence of LOS links (mmwave links). Part I of this thesis examined the benefits of adding IRS
channels along with backhaul mmWave channels. The MILP optimisation model is designed to minimise backhaul networks’ total power consumption and to guarantee
maximum service to their users. Based on the MILP results, using IRS channels together with mmWave channels can reduce both static and dynamic backhaul power
if a certain number of mmWave channels is blocked simultaneously. In our study range and input parameters, the number of active elements within an IRS can further optimize dynamic backhaul power. The IRS can also be deployed in minimum numbers through mmWave channels to optimize the number of users served.