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Link-Layer Capacity of NOMA Under Statistical Delay QoS Guarantees

Yu, Wenjuan and Musavian, Leila and Ni, Qiang (2018) 'Link-Layer Capacity of NOMA Under Statistical Delay QoS Guarantees.' IEEE Transactions on Communications. ISSN 0090-6778

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Abstract

In this paper, we study the achievable link-layer rate, namely, effective capacity (EC), under the per-user statistical delay quality-of-service (QoS) requirements, for a downlink nonorthogonal multiple access (NOMA) network with M users. Specifically, the M users are assumed to be divided into multiple NOMA pairs. Conventional orthogonal multiple access (OMA) then is applied for inter-NOMA-pairs multiple access. Focusing on the total link-layer rate for a downlink M-user network, we prove that OMA outperforms NOMA when the transmit signalto- noise ratio (SNR) is small. On the contrary, simulation results show that NOMA prevails over OMA at high values of SNR. Aware of the importance of a two-user NOMA network, we also theoretically investigate the impact of the transmit SNR and the delay QoS requirement on the individual EC performance and the total link-layer rate for a two-user network. Specifically, for delay-constrained and delay-unconstrained users, we prove that for the user with the stronger channel condition in a twouser network, NOMA prevails over OMA when the transmit SNR is large. On the other hand, for the user with the weaker channel condition in a two-user network, it is proved that NOMA outperforms OMA when the transmit SNR is small. Furthermore, for the user with the weaker channel condition, the individual EC in NOMA is limited to a maximum value, even if the transmit SNR goes to infinity. To confirm these insightful conclusions, the closed-form expressions for the individual EC in a two-user network, by applying NOMA or OMA, are derived for both users and then confirmed using Monte Carlo simulations.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 09 Aug 2018 15:20
Last Modified: 09 Aug 2018 15:20
URI: http://repository.essex.ac.uk/id/eprint/22813

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