Abstract

Non-Orthogonal Multiple Access (NOMA) is a promising multiple access technique for the 5 th generation (5G) mobile communication systems. In this paper, an energy efficient power allocation scheme is derived for a general number of users per cluster multiple input multiple output (MIMO) downlink NOMA system. The proposed scheme idea is based on converting the difficult energy efficiency power allocation problem into an equivalent spectral efficiency power allocation problem and then dividing this equivalent problem into multiple simple cluster sum rate maximization problems. In addition, a user clustering scheme is proposed to maximize the NOMA system energy efficiency by first designing the detection vectors to convert the MIMO users channel matrices into their equivalent channel vectors and distribute the users on the clusters based on their equivalent channel gains. The users are clustered such that those with the largest equivalent channel gains are selected as cluster heads and the rest of users in each cluster are selected to maximize the equivalent channel gain difference between each other. Numerical results show that the proposed framework improves the system energy efficiency of the MIMO NOMA system at different values of the total transmit power, the minimum required date rates, the number of users per cluster and at different users' distance distribution scenarios.

Keywords:
Telecommunications link MIMO Noma Computer science Spectral efficiency Cluster analysis Channel (broadcasting) Efficient energy use Maximization Transmitter power output Mathematical optimization Computer network Mathematics Engineering Electrical engineering Transmitter

Metrics

4
Cited By
0.37
FWCI (Field Weighted Citation Impact)
18
Refs
0.65
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Advanced Wireless Communication Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Optical Wireless Communication Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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