NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

KHAN, Wali Ullah; Li, Xingwang; Ihsan, Asim; Khan, NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding; Menon, Varun G; Ahmed, Manzoor

doi:10.1109/TITS.2021.3091402

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Article (Scientific journals)

NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

KHAN, Wali Ullah; Li, Xingwang; Ihsan, Asim et al.

2022 • In IEEE Transactions on Intelligent Transportation Systems

Peer Reviewed verified by ORBi

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https://hdl.handle.net/10993/54130

DOI
10.1109/TITS.2021.3091402

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Keywords :

non-orthogonal multiple access (NOMA); Small-cell; Resource optimization

Abstract :

[en] To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non-orthogonal multiple access (NOMA)-enabled small-cell IoV network (SVNet). We aim to investigate the trade-off between system capacity and energy efficiency through a joint power optimization framework. In particular, we formulate a nonlinear multi-objective optimization problem under imperfect successive interference cancellation (SIC) detecting. Thus, the objective is to simultaneously maximize the sum-capacity and minimize the total transmit power of NOMA-enabled SVNet subject to individual IoV QoS, maximum transmit power and efficient signal detecting. To solve the nonlinear problem, we first exploit a weighted-sum method to handle the multi-objective optimization and then adopt a new iterative Sequential Quadratic Programming (SQP)-based approach to obtain the optimal solution. The proposed optimization framework is compared with Karush-Kuhn-Tucker (KKT)-based NOMA framework, average power NOMA framework, and conventional OMA framework. Monte Carlo simulation results unveil the validness of our derivations. The presented results also show the superiority of the proposed optimization framework over other benchmark frameworks in terms of system sum-capacity and total energy efficiency.

Disciplines :

Electrical & electronics engineering

Author, co-author :

KHAN, Wali Ullah ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

Li, Xingwang

Ihsan, Asim

Khan, NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

Menon, Varun G

Ahmed, Manzoor

External co-authors :

yes

Language :

English

Title :

NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

Alternative titles :

[en] NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

Publication date :

November 2022

Journal title :

IEEE Transactions on Intelligent Transportation Systems

ISSN :

1524-9050

eISSN :

1558-0016

Publisher :

Institute of Electrical and Electronics Engineers, New-York, United States - New York

Peer reviewed :

Peer Reviewed verified by ORBi

Focus Area :

Security, Reliability and Trust

Additional URL :

https://ieeexplore-ieee-org.proxy.bnl.lu/document/9468352

Available on ORBilu :

since 25 January 2023

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