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Adeeb Salh
Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
Computer Science & IT Electrical & Electronics Engineering

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Adaptive Antenna Selection and Power Allocation in Downlink Massive MIMO Systems Adeeb Salh; Lukman Audah; Nor Shahida M Shah; Shipun A Hamzah
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (14.4 KB) | DOI: 10.11591/ijece.v7i6.pp3521-3528

Abstract

Massive multi-input, multi-output (MIMO) systems are an exciting area of study and an important technique for fifth-generation (5G) wireless networks that support high data rate traffic. An increased number of antenna arrays at the base station (BS) consumes more power due to a higher number of radio frequency (RF) chains, which cannot be neglected and becomes a technical challenge. In this paper, we investigated how to obtain the maximal data rate by deriving the optimal number of RF chains from a large number of available antenna arrays at the BS when there is equal power allocation among users. Meanwhile, to mitigate inter-user-interference and to compute transmit power allocation, we used the precoding scheme zero forcing beamforming (ZFBF). The achievable data rate is increased because the algorithm of ZFBF enables the choosing of the maximum power in relation to the optimal antenna selection. We conclude that the transmit power allocation  allows the use of less number of RF chains which provides the maximum achievable data rate depending on the optimal RF chain at the BS.
Maximizing Energy Efficiency for Consumption Circuit Power in Downlink Massive MIMO Wireless Networks Adeeb Salh; Lukman Audah; Nor Shahida M. Shah; Shipun A. Hamzah
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.194 KB) | DOI: 10.11591/ijece.v7i6.pp2977-2985

Abstract

Massive multi-input–multi-output (MIMO) systems are crucial to maximizing energy efficiency (EE) and battery-saving technology. Achieving EE without sacrificing the quality of service (QoS) is increasingly important for mobile devices. We first derive the data rate through zero forcing (ZF) and three linear precodings: maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE). Performance EE can be achieved when all available antennas are used and when taking account of the consumption circuit power ignored because of high transmit power. The aim of this work is to demonstrate how to obtain maximum EE while minimizing power consumed, which achieves a high data rate by deriving the optimal number of antennas in the downlink massive MIMO system. This system includes not only the transmitted power but also the fundamental operation circuit power at the transmitter signal. Maximized EE depends on the optimal number of antennas and determines the number of active users that should be scheduled in each cell. We conclude that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRTbecause the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas.
Co-Authors Lukman Audah Nor Shahida M Shah Nor Shahida M. Shah Shipun A Hamzah Shipun A. Hamzah