Abstract :
[en] In this paper, we investigate the performance of the rate-splitting multiple access (RSMA) framework in a mmWave cell-free massive multiple-input multiple-output (CF-mMIMO) system assisted by multiple reconfigurable intelligent surfaces (RISs). We consider the practical scenario of low-resolution digital-to-analog converters (DACs) at the distributed access points (APs) to reduce hardware complexity and power consumption. Our main objective is to maximize the minimum rate among the users by jointly optimizing the precoding vectors at each AP, the common rates, and the reflection coefficients of RISs. The resultant non-convex optimization problem is then solved using alternating optimization and successive convex approximation-based methods. Numerical results demonstrate the superior performance of the proposed RSMA-based scheme over traditional methods across several deployment scenarios, with performance gains from RIS deployment notably improved in hotspot scenarios.
Funding text :
This work has been supported by the Smart Networks and Services Joint Undertaking (SNS JU) project TERRAMETA under the European Union's Horizon Europe research and innovation programme under Grant Agreement No 101097101, including top-up funding by UK Research and Innovation (UKRI) under the UK government's Horizon Europe funding guarantee.
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