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International Journal of Sensors, Wireless Communications and Control


ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

Research Article

Energy Efficiency and Resource Allocation Optimization with MIMONOMA and Backhaul Beam-forming in User-centric Ultra-dense Networks

Author(s): Ravi Mancharla*, Tasher Ali Sheikh and Yaka Bulo

Volume 12, Issue 7, 2022

Published on: 10 November, 2022

Page: [510 - 520] Pages: 11

DOI: 10.2174/2210327913666221021110816

Price: $65


Background: Non-orthogonal multiple access (NOMA) is viewed as the key multiple access technology for 5G and beyond networks, attracting the attention of academics and industries. NOMA and the multiple input multiple output (MIMO-NOMA) technology can improve a system’s throughput, latency, and energy efficiency (EE) in future-generation communication networks.

Objective: The objective of this paper is to achieve maximum EE by applying the Max-min Power Control Algorithm (MMPCA) through sub-channel optimization, resource allocation (RA) optimization, access point selection (APS), and user association. The EE results obtained with and without using MMPCA are compared to the RA optimization from a conventional water-filling algorithm (WFA).

Methods: This paper formulates a framework for user-centric (UC) joint resource allocation, such as backhaul connection via beam-forming and Access point (AP) to user connection via MIMO-NOMA. The user without interference is decoded using the NOMA principle. The MMPCA was also used to optimize cooperative power allocation, sub-channel allocation, and efficient user association. The RA for EE is framed as a mixed non-convex and non-linear function using successive convex approximation and sum ratio decoupling converted into convex and linear. A bisection method was used to achieve optimal RA, user association, and sub-channel assignment.

Results and Conclusion: The simulation shows energy efficiency (EE) improvement. Similarly, it is observed that MMPCA outperforms the WFA.

Keywords: MIMO-NOMA, beam-forming, resource allocation, user centric ultra-dense networks, EE, SE, AP, Max-min power algorithm.

Graphical Abstract
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