In recent studies it was found out that previously allocated frequency spectrum is not fully utilized in all the wireless systems. Cognitive radio is the new concept to access this underutilized spectrum and, also a promising technology to cope with the ever increasing bandwidth demand for next generation wireless networks. Cognitive radio network can be classified into three different categories: interweave, underlay and overlay. In an interweave cognitive radio system, the unoccupied spectrum holes can be shared by cognitive users with minimal collision with primary users (spectrum owners) whereas in an underlay system, concurrent transmission is allowed with an interference threshold to the primary users. In an underlay system, cognitive users generally transmit at very low power. In an overlay system, cognitive users, similar to underlay cognitive radio systems, concurrently transmit with primary users but cognitive users may know the codewords of the primary transmitter. Hence, using that knowledge, cognitive transmitter may adopt different coding techniques to cancel/mitigate the interference at the primary receiver and/or it may assist the primary system by relaying primary user’s data. In this thesis, we improve the throughput/bit error rate performance of a cognitive radio system by effectively accessing the channels. Throughout the thesis we assume that cognitive user can sense only one channel at a time and we analyze the performance with perfect and imperfect sensing.
First, we propose a novel opportunistic access scheme for cognitive radios in an interweave cognitive system, that considers the channel gain as well as the predicted idle channel probability (primary user occupancy: busy/idle). In contrast to previous work where a cognitive user vacates a channel only when that channel becomes busy, the proposed scheme requires the cognitive user to switch to the channel with the next highest idle probability if the current channel’s gain is below a certain threshold. We derive the threshold values that maximize the long term throughput for various primary user transition probabilities and cognitive user’s relative movement (Doppler spread). Then, we propose a three state Markov model to analyze the performance of a hybrid interweave-underlay system where the primary user’s occupancy states are hidden, but their activity statistics, ranges of transmission, and interference thresholds are known. The primary user is assumed to be in one of the three transmission modes as seen by the cognitive user: busy, concurrent and idle. We derive the transmission mode selection criteria (interweave/underlay) to improve the long term throughput of a cognitive user based on the primary user traffic characteristics and the achievable throughput ratio between the two modes of operation. Later, we incorporate the sensing error in our analysis where we study the optimal access strategy. Since the optimal policy requires the channel to be sensed in each time-slot, we propose and analyze a forward algorithm based cross-layer frame based sensing policy.
Finally, we focus on the overlay cognitive radio system where cognitive relay nodes assist the primary transmission. As an initial study, we select a two-hop decode-and-forward orthogonal frequency and code division multiplexing based relay network. For this system, we propose adaptive channel allocation and, power allocation strategies and the bit error rate performance is numerically evaluated. This preliminary analysis can be extended to overlay cognitive systems.
Improved Learning Scheme for Cognitive Radio using Artificial Neural Networks
