Analytical and learning‐based spectrum sensing time optimisation in cognitive radio systems

Abstract

PostprintThis is the accepted version of a paper published in IET Communications. This paper has been peerreviewed but does not include the final publisher proof-corrections or journal pagination.Citation for the original published paper (version of record):Analytical and learning-based spectrum sensing time optimisation in cognitive radio systems. AbstractIn this paper, the average throughput maximization of a secondary user by optimizing its spectrum sensing time is formulated, assuming that a prior knowledge of the presence and absence probabilities of the primary users is available. The energy consumed to find a transmission opportunity is evaluated, and a discussion on the impacts of the number of the primary users on the secondary user throughput and consumed energy are presented.In order to avoid the challenges associated with the analytical method, as a second solution, a systematic adaptive neural network-based sensing time optimization approach is also proposed. The proposed scheme is able to find the optimum value of the channel sensing time without any prior knowledge or assumption about the wireless environment. The structure, performance, and cooperation of the artificial neural networks used in the proposed method are explained in detail, and a set of illustrative simulation results is presented to validate the analytical results as well as the performance of the proposed learning-based optimization scheme. Index TermsCognitive radio, spectrum handover, artificial neural networks, maximum secondary user's throughput.

Joint optimisation of transmission and waiting times in cognitive radio

“…In this context, several studies are investigated. Some papers optimised sensing time (Liu, Liang, & Zhang, 2013;Shokri-Ghadikolaei, Abdi, & Nasiri-Kenari, 2013) independently and some considered a fixed duration frame and maximised the transmission efficiency by defining it as the ratio of transmission time to frame duration (Balieiro, Yoshioka, Dias, Cordeiro, & Cavalcanti, 2013;Chang & Senadji, 2012;Choi & Yoo, 2013;Errong PEI et al, 2013;Hosseini, Amindavar, & Nadarajah, 2014). In the previously mentioned studies, there is nothing about interference caused by PU returns.…”