Multiple Access in Cognitive Radio Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

计算机科学 认知无线电 计算机网络 信道接入方式 光谱效率 可扩展性 多频时分多址 正交频分复用 接入网 多路复用 钥匙(锁) 频道(广播) 分布式计算 无线 电信 MIMO-OFDM 计算机安全 数据库
作者
Safaa Gamal,Mohamed Rihan,S. Hussin,Adel Zaghloul,A. Abdelaziz Salem
出处
期刊:IEEE Access [Institute of Electrical and Electronics Engineers]
卷期号:9: 95569-95584 被引量:44
标识
DOI:10.1109/access.2021.3095142
摘要

Due to the increasingly complicated communication scenarios and network architectures as well as growing traffic demands for high speed connectivity, dynamic spectrum allocation in fifth generation (5G) networks becomes insufficient to guarantee the satisfaction of main network requirements in terms of spectrum efficiency (SE), scalability, delay, and energy efficiency (EE). Enormous multiple access schemes and cognitive radio (CR) network scenarios come to fulfill these requirements and enhance network functionalities. With multiple access schemes, users are able to transmit their data streams simultaneously under maximum capacity constraints. On the other hand, vacant spectrum holes are exploited in an opportunistic manner via CR and software defined radio. In order to exploit these spectrum holes as well as meeting different network requirements, several multiple access techniques have been presented that have been initiated through the adoption of orthogonal multiple access (OMA) scheme. Additionally, non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) are presented to achieve a promising multiplexing gain as well as to address the inefficient spectrum utilization incurred with OMA schemes. However, such multiplexing gain is limited as it depend on the channel conditions. Accordingly, a generalized multiple access scheme has been presented recently, namely rate splitting multiple access (RSMA), to further enhance the SE. In this paper, we provide a comprehensive study regarding the key multiple access schemes presented for CRNs to further enhance the use of spectral resources, and additionally highlights the key implementation challenges and the enabling techniques addressed to overcome it. We have given a special attention to the enhances provided by RSMA as compared with OMA, SDMA, and NOMA techniques. Finally, some open issues are spotted to shed lights on the need for further studies and future research efforts.
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