Joint Power Allocation and Optimal Antenna Selection for the Massive MIMO Systems with Imperfect CSI and the MRT Precoding

Nima Imani (), Abdolrasoul Sakhaei Gharagezlou () and Mahdi Nangir ()
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Nima Imani: University of Tabriz
Abdolrasoul Sakhaei Gharagezlou: University of Tabriz
Mahdi Nangir: University of Tabriz

Telecommunication Systems: Modelling, Analysis, Design and Management, 2025, vol. 88, issue 4, No 1, 10 pages

Abstract: Abstract One of the important challenges in massive multiple input multiple output (MIMO) systems is energy efficiency (EE) and spectral efficiency (SE). This paper deals with the massive MIMO system performance from the EE point of view. We assume there is an eavesdropper (EVA) which is equipped with an antenna among users and tries to disrupt the performance of system under study. The system receiver is also considered the maximum ratio transmit (MRT) precoding under the imperfect channel state information (CSI) for users and EVA. The purpose of optimization problem in this paper is to maximize the secure EE. Because there is an enormous number of antennas in massive MIMO systems, it is imperative to select a proper number of active antennas to send information, which causes to improve the secure EE by reducing the consumed power of circuits. In addition, the optimal power of users is calculated under two constraints which are the maximum transmission power and the minimum data rate. We solve the problem of secure EE maximization, which leads to calculation of the optimal power of users using the non-linear programming techniques and the Lagrange dual function method. Then, we design a practical novel algorithm that simultaneously calculates the optimal number of antennas and power of users. Finally, we evaluate the system performance improvement by implementing and simulation results.

Keywords: Secure Energy Efficiency (EE); Power Allocation; Massive Multiple-Input Multiple-Output (MIMO) Systems; Maximum Ratio Transmit (MRT) Precoding (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11235-025-01348-1

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