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Uplink Spectral and Energy Efficiency of Cell-Free Massive MIMO With Optimal Uniform Quantization

Manijeh Bashar, Hien Quoc Ngo, Kanapathippillai Cumanan, Alister G. Burr, Pei Xiao, Emil Björnson, Erik G. Larsson

2020IEEE Transactions on Communications83 citationsDOIOpen Access PDF

Abstract

This paper investigates the performance of limited-fronthaul cell-free massive multiple-input multiple-output (MIMO) taking account the fronthaul quantization and imperfect channel acquisition. Three cases are studied, which we refer to as Estimate & Quantize, Quantize & Estimate, and Decentralized, according to where channel estimation is performed and exploited. Maximum-ratio combining (MRC), zero-forcing (ZF), and minimum mean-square error (MMSE) receivers are considered. The Max algorithm and the Bussgang decomposition are exploited to model optimum uniform quantization. Exploiting the optimal step size of the quantizer, analytical expressions for spectral and energy efficiencies are presented. Finally, an access point (AP) assignment algorithm is proposed to improve the performance of the decentralized scheme. Numerical results investigate the performance gap between limited fronthaul and perfect fronthaul cases, and demonstrate that exploiting relatively few quantization bits, the performance of limited-fronthaul cell-free massive MIMO closely approaches the perfect-fronthaul performance.

Topics & Concepts

Quantization (signal processing)MIMOTelecommunications linkSpectral efficiencyAlgorithmComputer scienceMaximal-ratio combiningMinimum mean square errorChannel (broadcasting)Electronic engineeringControl theory (sociology)MathematicsDecoding methodsTelecommunicationsEngineeringFadingArtificial intelligenceControl (management)StatisticsEstimatorAdvanced MIMO Systems OptimizationCooperative Communication and Network CodingMillimeter-Wave Propagation and Modeling
Uplink Spectral and Energy Efficiency of Cell-Free Massive MIMO With Optimal Uniform Quantization | Litcius