Research Repository

Performance Analysis of Physical Layer Network Coding in Massive MIMO Systems with M-QAM Modulations

Okyere, Bismark and Musavian, Leila and Mumtaz, Rao (2021) 'Performance Analysis of Physical Layer Network Coding in Massive MIMO Systems with M-QAM Modulations.' IEEE Transactions on Vehicular Technology. ISSN 0018-9545

[img]
Preview
Text
TVT_Journal_Paper_For_Publication_No_Bio.pdf - Accepted Version

Download (419kB) | Preview

Abstract

In this paper, we develop a practical approach for deploying Physical Layer Network Coding (PNC) in multi-user M-Ary Quadrature Amplitude Modulation (M-QAM) Massive Multiple-Input Multiple-Output (MIMO) systems. We formulate a PNC mapping scheme as a function of clusters of estimated summation and difference (SD) of the transmitted symbols from user pairs. Utilizing existing linear detection schemes, such as Zero Forcing (ZF) and Minimum Mean Square Error (MMSE), a cluster of SD symbols are detected using an SD linearly transformed channel matrix. Furthermore, utilizing Maximum a Posteriori (MAP) soft decoding, the SD symbols are mapped to the PNC symbols, leveraging on the PNC symbol that maximizes the likelihood function. For each variant of M-QAM, we derive and simplify a specialization of the generalized PNC mapping function. The error performance results, through simulation, reveal that the proposed PNC scheme achieves twice the spectral efficiency in Massive MIMO, without changing the latter's underlying framework and without any degradation in the bit-error-rate (BER). In fact, our investigation has proved that the BER of the proposed Massive MIMO and PNC is slightly better than that of the conventional Massive MIMO. The feasibility of deploying our proposed PNC scheme in Massive MIMO systems paves way for NC applications to be realized in cellular systems.

Item Type: Article
Uncontrolled Keywords: Massive MIMO, Physical Layer Network Coding, End-to-end simulation
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 19 May 2021 17:02
Last Modified: 19 May 2021 17:15
URI: http://repository.essex.ac.uk/id/eprint/30313

Actions (login required)

View Item View Item