Estimation of Primary Traffic Statistics Based on Spectrum Sensing

Cognitive Radio (CR) systems can benefit from the knowledge of the activity statistics of primary channels, which can use this information to intelligently adapt their spectrum use to the operating environment and work more efficiently and reduce interference on primary users. Particularly relevant statistics are the minimum, mean and variance of the on/off period durations, the channel duty cycle and the governing distribution. The main aim of this thesis is to improve the estimation of the primary user statistics under different environments. At the beginning of operation, the CR does not have any information about the primary traffic statistics. Spectrum sensing is one of the key methods to obtain this knowledge. Unfortunately, the estimation of primary traffic statistics based on spectrum sensing suffers from some flaws, which are investigated in detail in this thesis. In general, two main working environments for the CRs can be identified based on the primary signal power, namely low and high signal-to-noise ratio (SNR) at the secondary users. For the high SNR scenario, an analytical model to link the sensing period with the observed spectrum occupancy and quantify its impact is proposed. Simulation results show that the proposed model captures with reasonable accuracy the spectrum occupancy observed at the CR. Moreover, the effect of the sample size (number of on/off periods) on the estimated accuracy is studied as well. Closed form expressions to estimate the statistics of the primary channel to a certain desired level of accuracy are derived to link such sample size with the accuracy of the observed primary activity statistics. The accuracy of the obtained analytical results is validated and corroborated with both simulation and experimental results, showing a perfect agreement. For the low SNR scenario, both local and cooperative estimation are considered based on the number of SUs performing the estimation. For the single estimation scenario, three novel algorithms are proposed to enhance the estimation of primary user activity statistics under imperfect spectrum sensing given the knowledge of minimum transmission time. Simulation results show that the proposed methods enable an accurate estimation for the primary user statistics. For the cooperative estimation scenario, a new reporting mechanism is proposed in order to increase the spectrum and energy efficiency of the cooperative network and improve resilience under Byzantine attacks. The proposed method is compared in terms of efficiency with methods proposed in the literature and the default periodic reporting method. Simulation results show that the proposed scheme not only reduces significantly the signalling overhead, but with a minor modification it can estimate the primary user distribution under Byzantine attacks with high accuracy. In summary, this thesis contributes a holistic set of mathematical models and novel methods for an accurate estimation of the primary traffic statistics in CR networks based solely on spectrum sensing

Throughput Analysis of Primary and Secondary Networks in a Shared IEEE 802.11 System

In this paper, we analyze the coexistence of a primary and a secondary (cognitive) network when both networks use the IEEE 802.11 based distributed coordination function for medium access control. Specifically, we consider the problem of channel capture by a secondary network that uses spectrum sensing to determine the availability of the channel, and its impact on the primary throughput. We integrate the notion of transmission slots in Bianchi's Markov model with the physical time slots, to derive the transmission probability of the secondary network as a function of its scan duration. This is used to obtain analytical expressions for the throughput achievable by the primary and secondary networks. Our analysis considers both saturated and unsaturated networks. By performing a numerical search, the secondary network parameters are selected to maximize its throughput for a given level of protection of the primary network throughput. The theoretical expressions are validated using extensive simulations carried out in the Network Simulator 2. Our results provide critical insights into the performance and robustness of different schemes for medium access by the secondary network. In particular, we find that the channel captures by the secondary network does not significantly impact the primary throughput, and that simply increasing the secondary contention window size is only marginally inferior to silent-period based methods in terms of its throughput performance.Comment: To appear in IEEE Transactions on Wireless Communication