A Further Exploration of Multi-Slot Based Spectrum Sensing

Zhu, Jia; Cao, Hongsong; Mu, Junsheng

doi:10.3390/s19163497

Cited by 1 publication

(1 citation statement)

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“…Moreover, Zhu et al 14 have shown that for the multi‐slot‐dependent cooperative spectrum sensing (CSS), the majority voting mechanism among the several SUs accomplishes the best sensing performance under the decision fusion rule. Furthermore, because of the fading issues of the channel, among the PUs and SUs, the lone SU performance, with the use of an energy detector, is sometimes restricted.…”

Section: Introductionmentioning

confidence: 99%

Multi‐slot‐based dynamic clustering in cognitive radio network

Singh

Ranjan

2022

Int J Communication

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Summary The current work investigates the performance of multi‐slot‐based dynamic clustering in a cognitive radio network. For the spectrum sensing, every secondary user utilizes the multi‐slots of sensing time frame and combines the decisions of every multi‐slot, using the OR logic scheme, to get the sub‐local decision. The channel state information of the connections among the secondary users and access points present on the network's access points has been used to cluster the secondary users. To form the clusters, the secondary users with higher quality reporting channels for a specific access point have been chosen. Therefore, the clusters formed, in each iteration, with their respective access points, are dynamic in nature. Every secondary user in a cluster detects the availability of a primary user, makes a decision, and forwards it to its corresponding access point, via the reporting‐channel. Each access point employs the OR rule to merge the decisions of secondary users in the respective clusters, to make a local decision. Finally, the local decisions of all access points have been directed to fusion center, making the final decision about primary user's accessibility. The performance of multi‐slot‐based dynamic clustering has been studied relative to the different parameters, like detection probability, number of clusters, number of multi‐slots, secondary users, and access points. Further, the performance evaluation and comparisons of a multi‐slot‐based cognitive radio network with a single slot, cluster‐based cognitive radio network with non‐clustered, and multi‐slot‐based dynamic cluster with individual multi‐slots as well as dynamic clustering, have been done.

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Section: Introductionmentioning

confidence: 99%