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Smart city article details
| Title | Embedded Cr Assisted Noma For Iot Resource Allocation: A Case Study Of Vehicle Networks |
|---|---|
| ID_Doc | 22679 |
| Authors | Zheng M.; Zhou J.; Pu G.; Wang R.; Peng W. |
| Year | 2023 |
| Published | IEEE Vehicular Technology Conference |
| DOI | http://dx.doi.org/10.1109/VTC2023-Fall60731.2023.10333503 |
| Abstract | As an extension of the Internet of things (IoT), Internet of vehicles (IoV) paradigm plays a crucial role in advancing the development of smart cities. IoV relies on vehicular communication, enabling real-time interactions between vehicles, roadside infrastructure, and pedestrians. The main goal of IoV is not only to enhance road safety services but also to support time-sensitive IoT applications. In this context, cellular vehicle-to-everything (C-V2X) communication emerges as a prominent technology for achieving IoV goals. However, C-V2X communication system faces great challenges due to spectrum scarcity and the requirement for low-latency communication in high mobility and dynamic channel conditions. To meet these challenges, cognitive radio (CR)-inspired nonorthogonal multiple access (NOMA) has emerged as a promising solution to enhance the system capacity and spectrum efficiency. In this paper, we propose a novel CR paradigm, which utilizes the spectrum holes in an embedded mode. Namely, the secondary users (SUs) are allowed to access the holes released by idle primary users (PUs) without degrading the performance of active PUs. In addition, considering the channel aging phenomenon, we perform channel prediction to reduce the performance degradation. An online learning-based scheme that enables real-time resource allocation within the embedded CR assisted NOMA framework is then designed. Simulation results demonstrate superior performance gain of the proposed scheme. When compared with the conventional NOMA, the assistance of CR brings around threefold capacity gain, and when compared with the random allocation scheme, the capacity is increased by 21%. © 2023 IEEE. |
| Author Keywords | cellular vehicle-to-everything; channel aging; cognitive radio; Internet of things; nonorthogo-nal multiple access |
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