QoS-Driven Resource Block Allocation and Unicast–Broadcast Mode Switching in Dense 6G Networks: A Fluid Model Approach

Abstract

This article addresses the planning and allocation of spectral resource blocks for unicast (UC) and Multicast-Broadcast Single Frequency Network (MB-SFN) transmissions in dense Sixth-Generation (6G) cellular networks, where the choice of transmission mode directly influences spectral efficiency and Quality of Service (QoS). The objective is to identify the conditions under which the intercellular cooperation inherent to MB-SFN becomes more efficient than the UC mode for spectral resource block utilization under QoS constraints. To this end, we conduct a comparative performance analysis based on: i) Monte Carlo (MC) simulations, used as a numerical benchmark to accurately capture complex radio interactions, and ii) a fluid analytical framework, based on a continuous approximation of the network in which the discrete structure of base stations is replaced by a homogeneous surface density. Within this framework, we derive analytical expressions for the Signal-to-Interference-plus-Noise Ratio (SINR), enabling a tractable characterization of aggregate interference. Resource block allocation expressions are then proposed for both modes, incorporating SINR and outage probability as QoS constraints. The main contribution of this paper lies in deriving, using the fluid framework, an explicit analytical expression for the critical user threshold that characterizes the switch from UC mode to MB-SFN mode, beyond which the latter becomes more spectrum-efficient. The switching decision highlights the duality between the two modes: MB-SFN is constrained by the minimum SINR with resource consumption independent of the number of users, whereas UC mode depends on the average SINR and consumption proportional to the number of users. An in-depth analysis of the combined effect of network parameters is also conducted, highlighting their interactions and their influence on the switching threshold. Finally, the strong agreement with MC simulations validates the accuracy of the fluid framework, providing an effective analytical tool for optimizing adaptive transmission strategies.