An Efficient Contention-Window Based Reporting for Internet of Things Features in Cognitive Radio Networks

Abstract

Internet of things (IoT) is a new challenging paradigm for connecting heterogeneous networks. However, an explosive increase in the number of IoT cognitive users requires a mass of sensing reporting; thus, it increases complexity of the system. Moreover, bandwidth utilization, reporting time, and communication overhead arise. To realize spectrum sensing, how to collect sensing results by reducing the communication overhead and the reporting time is a problem of major concern in future wireless networks. On the other hand, cognitive radio is a promising technology to access the spectrum opportunistically. In this paper, we propose a contention-window based reporting approach with a sequential fusion mechanism. The proposed reporting scheme reduces the reporting time and the communication overhead by collecting sensing results from the secondary users with the highest reliability at a fusion center by utilizing Dempster-Shafer evidence theory. The fusion center broadcasts the sensing results once a global decision requirement is satisfied. Through simulations, we evaluate the proposed scheme in terms of percentage of the number of reporting secondary users, error probability, percentage of reporting, and spectral efficiency. As a result, it is shown that the proposed scheme is more effective than a conventional order-less sequential reporting scheme.

Smart Wireless Sensor Technology for Healthcare Monitoring System Using Cognitive Radio Networks

“…By 2021, nearly 50 billion cellular devices will be linked, necessitating a significant amount of spectrum [17]. The CR-based paradigm is explored for a routing mechanism in [18], whereas the contention window-based mechanism is explored in [19]. In [20], a channel-hopping mechanism is designed where secondary users can avail the network without clock synchronization at the global level.…”

Novel Analytical Framework for harnessing Cognitive Radio Resource Optimization in 5G Networks

“…Kakalou et al [17] have used the concept of an environmental map of radio considering the heterogeneous environment for the cognitive radio network. Khan et al [18] have used the evidence theory for formulating effective feature extraction schemes over cognitive radio for obtaining better spectral efficiency. Liu et al [19] have used a wavelet filter to perform optimization for improving the data transmission rate for the unlicensed user using an intelligent search algorithm.…”

Multi-Tag Selection in Cognitive Ambient Backscatter Communications for Next-Generation IoT Networks

“…In CR networks, sensing the primary system and reporting the sensing results to a secondary fusion node are important issues. Accordingly, there are several studies on the performance improvements in primary sensing [38] and reporting [39]. Recently, there are also a few studies on ABC systems under CR environments [40][41][42].…”