'Institute of Electrical and Electronics Engineers (IEEE)'
Abstract
peer reviewedIn this paper, we study the resource allocation
problem in multi-RIS-aided outdoor-to-indoor communications.
Specifically, we aim to provide geographical fairness to ensure
that users in different hotspot areas in a smart city can be served
regardless of their location. We consider a scenario where RISs
are deployed to extend coverage to indoor users in different buildings where there is limited network accessibility. This design is
crucial in smart cities in the context of emergency communication
and ubiquitous connectivity since it ensures service availability
to as many users as possible independently of the locations.
Thus, to achieve geographical fairness, we formulate a max-min
fairness problem to maximize the minimum number of users
served by each RIS by jointly optimizing the active precoding
and RIS-based beamforming subject to power and quality of
service constraints. The geographical location of users is directly
linked to the RIS which means that users are served by the RIS
closest to them. In this case, we ensure that a certain number of
users can be supported by each RIS. The formulated problem
is a mixed integer non-linear program, which is challenging to
solve directly using methods of convex optimization. Accordingly,
we propose an efficient successive convex approximation-based
alternating optimization algorithm to tackle the complexity of the
formulated problem. The presented results show the performance
gain of the proposed design in providing geographical fairness
compared to the relevant benchmark schemes.U-AGR-7046 - C20/IS/14773976/RISOTTI - OTTERSTEN Björ