Scalable Cell-Free Massive MIMO with Multiple CPUs

Feiyang Li, Qiang Sun, Xiaodi Ji and Xiaomin Chen
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Feiyang Li: School of Information Science and Technology, Nantong University, Nantong 226019, China
Qiang Sun: School of Information Science and Technology, Nantong University, Nantong 226019, China
Xiaodi Ji: School of Information Science and Technology, Nantong University, Nantong 226019, China
Xiaomin Chen: School of Information Science and Technology, Nantong University, Nantong 226019, China

Mathematics, 2022, vol. 10, issue 11, 1-17

Abstract: In this paper, we consider the uplink of a scalable cell-free massive MIMO (CF-M-MIMO) system where user equipments (UEs) are served only by a subset of access points (APs). All APs are physically divided into predetermined “real clusters”, which are linked to different cooperative central processing units (CPUs). Based on the cooperative nature of the considered communications framework, we assume that each UE is affiliated with a “virtual cluster”, which is associated with some APs coming from different real clusters. Thanks to the degrees of cooperation among multiple CPUs, the uplink spectral efficiencies (SEs) of four different levels are analyzed. To achieve system scalability, the CF-M-MIMO system with multiple CPUs is introduced, which leads to lower SE. To this end, we design a joint combining method based on statistical channel state informations (CSIs), which not only has low complexity but also improves the SE of the system. Simulation results indicate that the average rate of our proposed method can be improved by about 30%.

Keywords: cell-free massive MIMO; clustering; multiple CPUs; spectral efficiency; system scalability (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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