Dynamic Spectrum Access (DSA)/Cognitive Radio (CR) has emerged as an effective paradigm to solve problem of inefficient spectrum utilization. Spectrum sensing is the key in DSA/CR. Spectrum sensing decisions can be utilized to accurately estimate the primary channel activity statistics (PAS) like mean of idle/busy period, Duty cycle etc. Such estimated statistics can be used by CR to improve performance. However, when the secondary user (SU) is mobile, estimating these statistics becomes challenging. Taking this into account, this work provides a thorough review on the estimation of PAS for mobile SUs, considering vehicular scenario. The random way-point based mobility model is adopted for modelling SU mobility. Specifically, this work provides a set of closed form expressions for the estimated statistics under SU mobility as a function of the true PAS, SU velocity, initial distance between PU and SU, PU's protection range (R), SU's sensing range (S).

With the rapid development of intelligent transportation systems, vehicular devices are getting connected with each other. However, this leads to the problem of spectrum scarcity. Dynamic spectrum access (DSA)/cognitive radio (CR) has emerged as an effective solution to solve the problem of inefficient spectrum utilization. Spectrum sensing is the key in DSA/CR system. In cognitive vehicular networks (CVNs), spectrum sensing becomes more complex and challenging and that often leads to a loss in performance detection. Due to the effect of channel fading/shadowing and due to secondary user (SU) mobility, individual SUs may not be able to detect the existence of primary user (PU). In this paper, we propose a weighted cooperative spectrum sensing (weighted-CSS) framework for accurate detection of PU in CVNs. The weights are calculated from the probability of PU being inside the SU's sensing range and SU being outside the PU's protection range (inside probability). The calculated weight for SU indicates the reliability in the signal received by SU. The framework contains two stages. In the first stage, inside probability is calculated at each SU and the inside probability and the energy signal received from PU are sent to a base station (BS). In the second stage, BS assigns a weight to each SU based on the inside probability and makes a decision by combining the information received from SUs. Numerical results indicate that, on an average, the proposed framework performs ≈15% better than the conventional local spectrum sensing.

In contrast with the traditional cryptography, physical layer security has attracted the attention of many researchers having aim at reinforcing the security of communication systems. As far as vehicular communication is concerned, it is challenging to maintain secure and reliable communication between the connected vehicles due to the density, mobility, and dynamic network topology. This paper considers a vehicle to infrastructure communication in which a legitimately fixed transmitter equipped with a single antenna transmits a confidential message to a legitimate mobile receiver equipped with multiple antennas in the presence of a passive mobile eavesdropper. In such a single input multiple output wireless system, the receiver performs the maximal ratio combining technique assuming constant vehicle speed. We assume that the antennas are closely spaced and depending upon the imperfect channel state information (CSI), we derive the closed-form expressions for the average outage probability, secrecy outage probability, and average secrecy outage rate over the uniform, exponential, and arbitrary correlated Nakagami- m channels for dual antenna branches. In order to gain insight we also perform the high SNR asymptotic analysis of the outage probability and secrecy outage probability. Simulations are conducted to validate the accuracy of our derived analytic expressions. The computation error analysis is carried out to provide the suitability of the correlation type at the legitimate receiver side. Our findings suggest that the performance of the case with exponential channel correlation is better than those for the uniform and arbitrary. Numerical results show the joint effect of vehicle mobility and the antenna correlation on secrecy performance. Moreover, we also observed that the imperfect knowledge of the CSI degrades the security of the confidential messages severely under the effect of mobility.

In this work, energy detection‐based spectrum sensing for multiple antenna receiver under the effect of mobility is investigated by considering L number of correlated antenna branches. The authors consider the uniform, exponential and arbitrarily correlation among the antenna branches based on the spacing between them. The moment generating function (MGF) approach is applied to obtain the statistical knowledge of the received signal to noise ratio because the Laplace domain behaviour will help to derive the closed‐form expressions using simple algebraic operations. They derived the closed‐form expressions for the detection probability over Nakagami‐ m fading, in terms of Lauricella and Confluent Hypergeometric function for maximal ratio combining (MRC) and equal gain combining (EGC) diversity techniques under the effect of vehicle mobility. Monte‐Carlo simulation is carried out to validate the derived analytical expressions. The results show that the degradation in detection performance due to fading correlation can be reduced by choosing the appropriate diversity scheme and by increasing the number of antennas. Furthermore, they also found that at high fading parameter ( ) value, the low value of the probability of false alarm and highly correlated fading, MRC works better than EGC for high relative velocity.