Uplink Resource Allocation for RSMA-Aided Digital Twin-Assisted User-centric Cell-free Massive MIMO Systems

This paper investigates uplink radio resource optimization of a user-centric (UC) cell-free (CF) massive multiple-input multiple-output (mMIMO) system aided by the rate splitting multiple access (RSMA) technique subject to pilot contamination. We formulate problem to maximize the minimum spectral ef...

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Bibliographic Details
Published in:IEEE transactions on mobile computing pp. 1 - 17
Main Authors: Sarker, Manobendu, Hassan, Md. Zoheb, Kaddoum, Georges, Fapojuwo, Abraham O.
Format: Magazine Article
Language:English
Published: IEEE 2025
Subjects:
AP-UE association assignment
cell-free massive MIMO
centralized control
Channel estimation
Contamination
Decoding
decoding order design
digital twin
Massive MIMO
Mobile computing
NOMA
Optimization
Power demand
Resource management
RSMA
Spectral efficiency
transmit power allocation
Uplink
ISSN:1536-1233, 1558-0660
Online Access:Get full text
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Summary:This paper investigates uplink radio resource optimization of a user-centric (UC) cell-free (CF) massive multiple-input multiple-output (mMIMO) system aided by the rate splitting multiple access (RSMA) technique subject to pilot contamination. We formulate problem to maximize the minimum spectral efficiency (SE) problem by jointly addressing decoding order selection, power allocation, and access point (AP) - user equipment (UE) association assignment. The envisioned optimization exhibits two challenges. First, it requires global channel state information (CSI) for near-optimal performance, which incurs substantial overhead and data collection costs in large-scale CF networks. Second, the optimization is intractable due to its NP-hard and discrete non-linear programming nature. To address the CSI acquisition issue, we utilize a digital twin (DT) of the CF mMIMO system, leveraging its context-awareness to acquire global CSI with reduced overhead. To address computational intractiablity of the optimization problem, we decompose it into three sub-problems. The power allocation sub-problem is transformed into a second-order cone programming problem and solved by the bisection method. Additionally, we propose a computationally efficient heuristic approach for power allocation. Next, we propose an analytical method for the decoding order selection by ranking the channels in descending order of strength. Simulation results validate the ability of the proposed approach to attain the near-optimal performance. Subsequently, the AP-UE association assignment problem is solved by a heuristic approach to further improve the SE performance. Finally, we solve the original NP-hard problem in a unified manner via the block-coordinate descent algorithm. Simulation results underscore a substantial 61% improvement in the SE performance when integrating the RSMA technique into a UC CF mMIMO system.
ISSN:1536-1233
1558-0660
DOI:10.1109/TMC.2025.3604722