Optimal Planning for Heterogeneous Smart Radio Environments

TL;DR

Two optimization methods are proposed, full coverage minimum cost (FCMC) and maximum budget-constrained coverage (MBCC), that address key cost and coverage objectives by considering both physical characteristics and scalable costs of each component, influenced by factors such as NCR amplification gain and RIS dimensions.

Abstract

Smart Radio Environment (SRE) is a central paradigms in 6G and beyond, where integrating SRE components into the network planning process enables optimized performance for high-frequency Radio Access Network (RAN). This paper presents a comprehensive planning framework utilizing realistic urban scenarios and precise channel models to analyze diverse SRE components, including Reconfigurable Intelligent Surface (RIS), Network-Controlled Repeater (NCR), and advanced technologies like Simultaneous transmitting and reflecting RIS (STAR RIS) and trisectoral NCR (3SNCR). We propose two optimization methods, full coverage minimum cost (FCMC) and maximum budget-constrained coverage (MBCC), that address key cost and coverage objectives by considering both physical characteristics and scalable costs of each component, influenced by factors such as NCR amplification gain and RIS dimensions. Extensive numerical results demonstrate the significant impact of these models in enhancing network planning efficiency for high-density urban environments.

Figures (9)

• Figure 1: Network topology with a single fixed BS, and/or devices, achieved with (a) MBCC model, given fixed budget of $B=2$ units, (b) MBCC model, given fixed budget of $B=4$ units, and (c) FCMC model. The price of each is assumed to be 1 unit and each is 2 units.
• Figure 2: Illustrative scheme of different components
• Figure 3: Average Coverage probability (achieved with MBCC optimization model) vs the total available budget. The used configurations are the default as in Table \ref{['tab:SimParam_1']}.
• Figure 4: Average Coverage probability vs dimension, where the total available budget is constrained to $B=8$ units.
• Figure 5: Average Coverage probability (achieved with MBCC optimization model) vs amplification gain, where the total available budget is constrained to $B=8$ units. Configurations according to table \ref{['tab:SimParam_1']}.