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

TY - JOUR

T1 - Uplink Spectral and Energy Efficiency of Cell-Free Massive MIMO with Optimal Uniform Quantization

AU - Bashar, Manijeh

AU - Ngo, Hien Quoc

AU - Cumanan, Kanapathippillai

AU - Burr, Alister G.

AU - Xiao, Pei

AU - Bjornson, Emil

AU - Larsson, Erik G.

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2021/1/1

Y1 - 2021/1/1

N2 - 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 EstimateQuantize, QuantizeEstimate, 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.

AB - 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 EstimateQuantize, QuantizeEstimate, 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.

KW - Bussgang decomposition

KW - C-RAN

KW - cell-free massive MIMO

KW - energy efficiency

KW - optimal uniform quantization

KW - quantization

UR - http://www.scopus.com/inward/record.url?scp=85099765060&partnerID=8YFLogxK

U2 - 10.1109/TCOMM.2020.3028305

DO - 10.1109/TCOMM.2020.3028305

M3 - Article

AN - SCOPUS:85099765060

SN - 0090-6778

VL - 69

SP - 223

EP - 245

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

IS - 1

M1 - 9212395

ER -