Rate-Splitting Multiple Access in Multi-cell Dense Networks: A Stochastic Geometry Approach
Qiao Zhu, Zhihong Qian, Bruno Clerckx, and Xue Wang

TL;DR
This paper evaluates the benefits of Rate-Splitting Multiple Access (RSMA) in multi-cell dense networks using stochastic geometry, demonstrating its superiority over other schemes and providing analytical tools for system optimization.
Contribution
It introduces a stochastic geometry-based analytical framework for RSMA in multi-cell dense networks, including performance metrics and energy efficiency optimization.
Findings
RSMA significantly improves sum-rate performance over NOMA and SDMA.
Optimal power splitting ratio maximizes sum-rate in RSMA.
Increasing antennas and base station density enhances spectral efficiency.
Abstract
In this paper, the potential benefits of applying the Rate-Splitting Multiple Access (RSMA) in multi-cell dense networks are explored. Using tools of stochastic geometry, the sum-rate of RSMA-enhanced multi-cell dense networks is evaluated mathematically based on a Moment Generating Function (MGF) based framework to prove that RSMA is a general and powerful strategy for multi-antenna downlink systems. Further elaboration of the systematic performance metrics is undertaken by developing analytical expressions for area spectral efficiency and sum-rate in the RSMA-enhanced multi-cell dense networks. Based on the tractable expressions, we then offer an optimization framework for energy efficiency in terms of the number of antennas. Additionally, simulation results are shown to verify the accuracy of our analytical results and provide some insightful insights into system design.…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Advanced MIMO Systems Optimization · Satellite Communication Systems
