Enhanced Max-Min SINR for Uplink Cell-Free Massive MIMO Systems

TY - GEN

T1 - Enhanced Max-Min SINR for Uplink Cell-Free Massive MIMO Systems

AU - Bashar, Manijeh

AU - Cumanan, Kanapathippillai

AU - Burr, Alister G.

AU - Debbah, Merouane

AU - Ngo, Hien Quoc

N1 - Funding Information: The work of K. Cumanan and A. G. Burr was supported by H2020-MSCA-RISE-2015 under grant number 690750. The work on which this paper is based was carried out in collaboration with COST Action CA15104 (IRACON). Publisher Copyright: © 2018 IEEE.

PY - 2018/7/27

Y1 - 2018/7/27

N2 - In this paper, we consider the max-min signal-to- interference plus noise ratio (SINR) problem for the uplink transmission of a cell-free Massive multiple-input multiple-output (MIMO) system. Assuming that the central processing unit (CPU) and the users exploit only the knowledge of the channel statistics, we first derive a closed-form expression for uplink rate. In particular, we enhance (or maximize) user fairness by solving the max-min optimization problem for user rate, by power allocation and choice of receiver coefficients, where the minimum uplink rate of the users is maximized with available transmit power at the particular user. Based on the derived closed-form expression for the uplink rate, we formulate the original user max-min problem to design the optimal receiver coefficients and user power allocations. However, this max-min SINR problem is not jointly convex in terms of design variables and therefore we decompose this original problem into two sub- problems, namely, receiver coefficient design and user power allocation. By iteratively solving these sub-problems, we develop an iterative algorithm to obtain the optimal receiver coefficient and user power allocations. In particular, the receiver coefficients design for a fixed user power allocation is formulated as generalized eigenvalue problem whereas a geometric programming (GP) approach is utilized to solve the power allocation problem for a given set of receiver coefficients. Numerical results confirm a three-fold increase in system rate over existing schemes in the literature.

AB - In this paper, we consider the max-min signal-to- interference plus noise ratio (SINR) problem for the uplink transmission of a cell-free Massive multiple-input multiple-output (MIMO) system. Assuming that the central processing unit (CPU) and the users exploit only the knowledge of the channel statistics, we first derive a closed-form expression for uplink rate. In particular, we enhance (or maximize) user fairness by solving the max-min optimization problem for user rate, by power allocation and choice of receiver coefficients, where the minimum uplink rate of the users is maximized with available transmit power at the particular user. Based on the derived closed-form expression for the uplink rate, we formulate the original user max-min problem to design the optimal receiver coefficients and user power allocations. However, this max-min SINR problem is not jointly convex in terms of design variables and therefore we decompose this original problem into two sub- problems, namely, receiver coefficient design and user power allocation. By iteratively solving these sub-problems, we develop an iterative algorithm to obtain the optimal receiver coefficient and user power allocations. In particular, the receiver coefficients design for a fixed user power allocation is formulated as generalized eigenvalue problem whereas a geometric programming (GP) approach is utilized to solve the power allocation problem for a given set of receiver coefficients. Numerical results confirm a three-fold increase in system rate over existing schemes in the literature.

KW - Cell-free Massive MIMO

KW - Convex optimization

KW - Generalized eigenvalue problem

KW - Geometric programming

KW - Max-min SINR problem

UR - http://www.scopus.com/inward/record.url?scp=85050980445&partnerID=8YFLogxK

U2 - 10.1109/ICC.2018.8422577

DO - 10.1109/ICC.2018.8422577

M3 - Conference contribution

AN - SCOPUS:85050980445

SN - 9781538631805

T3 - IEEE International Conference on Communications

BT - 2018 IEEE International Conference on Communications, ICC 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Conference on Communications, ICC 2018

Y2 - 20 May 2018 through 24 May 2018

ER -