Reputation-based power allocation for NOMA cognitive radio networks

• Main Authors: Li, Feng, Sun, Zhongming, Lam, Kwok-Yan, Zhang, Songbo, Sun, Lianzhong, Wang, Li
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Cognitive Radio Networks; Power Allocation
• Online Access: https://hdl.handle.net/10356/168432
• Institution: Nanyang Technological University

In this paper, a power optimization scheme based on user’s reputation in non-orthogonal multiple access (NOMA) Cognitive Radio Networks (CRN) is proposed. By combining NOMA and CRN, the spectrum utilization and network throughput can be further improved, in which secondary users can access the authorized spectrum without worrying about the co-channel interference. In NOMA systems, how to optimize the user power so as to realize the effective decoding in receivers and enhance the system capacity is a key issue. In this work, the concept of user reputation is introduced which denotes the spectrum sensing capability of a secondary user, depending on the ratio of the channel number sensed by the secondary user and the actual number of available channels provided by the primary systems. High user reputation means a precise spectrum sensing capability which leads to less channel collision and better network capacity. When the secondary users with qualified reputation level aim to access the idle channels, an optimal power allocation strategy is required to facilitate the decoding for the receivers in NOMA systems and maximize the overall system throughput. Due to the complexity of the objective functions achieved, the genetic algorithm, which has good performances in global searching is applied for ascertaining the final power solutions. Furthermore, numerical results are provided to evaluate the proposed method on system throughput, power level and access probability.