The impact of secondary user mobility and primary user activity on spectrum sensing in cognitive vehicular networks

Abstract

In cognitive vehicular networks, unlicensed secondary users heavily depend on spectrum sensing to find unused spectrum bands for communications. The performance study of existing spectrum sensing algorithms often overlooks the impact of secondary user mobility. Many of them assume secondary users stationary or with low mobility. In this paper, we investigate the joint impact of secondary user mobility and primary user activity on spectrum sensing for highly dynamic cognitive vehicular networks. We assume that each vehicle is equipped with a cognitive radio for spectrum sensing. The main contribution of this work is to investigate mathematical models for missdetection probability and expected overlapping time duration for spectrum sensing. The proposed method incorporates velocity of secondary user, activity of primary user, initial distance between primary and secondary users and their transmission ranges. In ordered to corroborate the analysis, numerical results obtained from simulations are presented. It is noted that the speed of the vehicular secondary user and the activity of primary user have significant impact on miss-detection probability, but not on false alarm probability. Furthermore, transmission range, velocity and initial separation distance have huge impact on expected overlapping time duration.Index Terms-Cognitive vehicular networks, spectrum sensing performance, miss-detection probability, secondary user mobility.

Performance optimisation of cooperative spectrum sensing in mobile cognitive radio networks

“…According to (12) and (13), g(d, φ) can be confirmed as a continuous and strictly monotonic function with respect to d and φ. Hence, the PDF of R 2 can be deduced as…”

“…The probability distribution and mathematical expectation of the PU signal power were theoretically derived by considering the SU mobility. Amin et al investigated the joint impact of the SU mobility and PU activity on spectrum sensing for highly dynamic cognitive vehicular networks and CRNs, and derived mathematical models for the performance and expected overlapping time duration for spectrum sensing, respectively, in [12,13]. In [14], Marino et al addressed the spectrum-sensing design problem in the presence of PU-SU relative mobility.…”

A survey of cognitive radio handoff schemes, challenges and issues for industrial wireless sensor networks (CR-IWSN)

“…To evaluate the performance of spectrum sensing in CRN; sensing range of SU, PU activity, and PU transmission range, as well as velocity of nodes are important factors that should be considered. Authors in Rawat et al (2015) consider the impact of SU mobility including the activities of a PU on spectrum sensing performance and develop mathematical models for both probability of miss-detection and expected overlapping time duration in cognitive vehicular networks. In IWSNs scenario, all of these parameters can be determine before a spectrum handoff scheme is designed or obtained during the implementation of the protocol e.g.…”

“…The result in 2 shows a scenario of the signal being detected correctly, while results in 3 and 4 are for scenario of signal being missed detected and for a case of false alarm respectively (Zhang et al, 2016). A mathematical model for probability of miss-detection was developed in (Rawat et al, 2015) to evaluate the performance of a sensing algorithm. However, since September 10 2010, focus has shifted from client sensing to database geo location using beacons; and when beacons are used advanced information such as channel quality can be obtained.…”

An intelligent approach for resource allocation in the cognitive radio vehicular ad hoc network

“…So, for the detection performance to be enhanced, various spectrum sensing techniques were proposed in the CR‐VANET. In Rawat et al, the authors evaluated the miss detection probability considering the velocity of the VSU, sensing range of the VSU, and the protecting ranges of the PUs. Xu et al used maximum likelihood ratio detection scheme for local wideband spectrum sensing in orthogonal frequency division multiplexing–based CR‐VANET in which the global decision was made using the OR fusion rule with square‐law selection scheme .…”