Spectrum sensing, spectrum monitoring, and security in cognitive radios

Spectrum sensing is a key function of cognitive radios and is used to determine whether a primary user is present in the channel or not. In this dissertation, we formulate and solve the generalized likelihood ratio test (GLRT) for spectrum sensing when both primary user transmitter and the secondary user receiver are equipped with multiple antennas. We do not assume any prior information about the channel statistics or the primary user’s signal structure. Two cases are considered when the secondary user is aware of the energy of the noise and when it is not. The final test statistics derived from GLRT are based on the eigenvalues of the sample covariance matrix. In-band spectrum sensing in overlay cognitive radio networks requires that the secondary users (SU) periodically suspend their communication in order to determine whether the primary user (PU) has started to utilize the channel. In contrast, in spectrum monitoring the SU can detect the emergence of the PU from its own receiver statistics such as receiver error count (REC). We investigate the problem of spectrum monitoring in the presence of fading where the SU employs diversity combining to mitigate the channel fading effects. We show that a decision statistic based on the REC alone does not provide a good performance. Next we introduce new decision statistics based on the REC and the combiner coefficients. It is shown that the new decision statistic achieves significant improvement in the case of maximal ratio combining (MRC). Next we consider the problem of cooperative spectrum sensing in cognitive radio networks (CRN) in the presence of misbehaving radios. We propose a novel approach based on the iterative expectation maximization (EM) algorithm to detect the presence of the primary users, to classify the cognitive radios, and to compute their detection and false alarm probabilities. We also consider the problem of centralized binary hypothesis testing in a cognitive radio network (CRN) consisting of multiple classes of cognitive radios, where the cognitive radios are classified according to the probability density function (PDF) of their received data (at the FC) under each hypotheses

Cognitive radio enabled multi-channel access for vehicular communications

Abstract—The IEEE 1609.4 standard has been proposed to provide multi-channel operations in wireless access for vehicular environments (WAVE), where all the channels are periodically synchronized into control and service intervals. The communication device in each vehicle will stay at the control channel for negotiation and contention during the control interval, and thereafter switch to one of the service channels for data transmission in the service interval. The inefficiency of WAVE system comes from the fact that half of the time intervals of the service channels remain idle since all the stations are performing message contention within the control channel. In this paper, the cognitive radio-enabled multi-channel access (CREM) protocol is proposed to increase the channel utilization of IEEE 1609.4 standard. Based on the concept of cognitive radio, the vehicular stations are categorized into primary stations with safety-related messages and secondary stations with non-safety information to be delivered. Prioritized channel access is designed in the proposed CREM scheme in order to increase the transmission opportunity of primary stations. Moreover, extended time intervals are granted for primary stations to ensure reliability for data transmission. The enhanced CREM (CREM-E) protocol is proposed to further opportunistically increase the channel utilization of secondary stations. Simulation results show that the proposed CREM-E scheme outperforms the existing IEEE 1609.4 protocol with enhanced channel utilization and smaller waiting time intervals. I