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Wireless Networks
Erschienen in: Wireless Networks 2/2021

02.01.2021

Uplink NOMA-based long-term throughput maximization scheme for cognitive radio networks: an actor–critic reinforcement learning approach

verfasst von: Hoang Thi Huong Giang, Tran Nhut Khai Hoan, Insoo Koo

Erschienen in: Wireless Networks | Ausgabe 2/2021

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Abstract

Non-orthogonal multiple access (NOMA) is one of the promising techniques for spectrum efficiency in wireless networks. In this paper, we consider an uplink NOMA cognitive system, where the secondary users (SUs) can jointly transmit data to the cognitive base station (CBS) over the same spectrum resources. Thereafter, successive interference cancellation is applied at the CBS to retrieve signals transmitted by the SUs. In addition, the energy-constrained problem in wireless networks is taken into account. Therefore, we assume that the SUs are powered by a wireless energy harvester to prolong their operations; meanwhile, the CBS is equipped with a traditional electrical supply. Herein, we propose an actor–critic reinforcement learning approach to maximize the long-term throughput of the cognitive network. In particular, by interacting and learning directly from the environment over several time slots, the CBS can optimally assign the amount of transmission energy for each SU according to the remaining energy of the SUs and the availability of the primary channel. As a consequence, the simulation results verify that the proposed scheme outperforms other conventional approaches (such as Myopic NOMA and OMA), so the system reward is always maximized in the current time slot, in terms of overall throughput and energy efficiency.
Vorheriger Artikel Spectral efficiency (SE) enhancement of NOMA system through iterative power assignment
Nächster Artikel Cooperative link scheduling for RSU-assisted dissemination of basic safety messages

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Metadaten
Titel
Uplink NOMA-based long-term throughput maximization scheme for cognitive radio networks: an actor–critic reinforcement learning approach
verfasst von
Hoang Thi Huong Giang
Tran Nhut Khai Hoan
Insoo Koo
Publikationsdatum
02.01.2021
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 2/2021
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-020-02520-y

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