The exploding increase of wireless communications combined with the existing inefficient usage of the licensed spectrum gives a strong impetus to the development and standardization of cognitive radio networking and communications. In this dissertation, a framework for Dynamic Spectrum Access (DSA) is first presented, which is the enabling technology for increasing the spectral efficiency of wireless communications. Based on that, Cognitive Radio (CR) can be developed as an enabling technology for supporting the DSA, which means that the wireless users are provided with enhanced capability for sensing the operating radio environment and for exploiting the network side information obtained from this sensing. The DSA concept means that the users of a wireless system are divided into a multi-tiered hierarchy with the primary users (PUs) entitled to protection and with cognitive radio capable secondary users (SUs). The improved spectrum efficiency is obtained by means of a medium access control protocol with knowledge about the statistical properties or available local information of the channels already occupied by PUs as well as knowledge about the interference tolerance within which the interference to PUs is kept to a given level. Related to this, emphasis is laid on the protocol capability to determine the efficiency of the secondary sharing of spectrum. Based on the type of available local information, the capacity of opportunistic communication is investigated for three models. These are: with dynamic, distributed channels information; with dynamic, parallel channels information; and under a dynamic sub-channels allocation scheme. The results indicate that this capacity is robust with reference to the uncertainty associated with localized sensing of distributed dynamic channels and with timely sensing of parallel dynamic channels. The extension to dynamic parallel sub-channels enables resource allocation to be carried out in sub-channels. The analytical results on the performance of sub-channel allocation indicate a robust traffic capacity in terms of blocking probability, drop-out probability and delay performance as function of PUs traffic loads.

Cognitive Radio networks allow the unlicensed users to share the available spectrum opportunities. However, this demands for solving the problem of contention among multiple unlicensed user packets for transmission. In our paper, we consider the Opportunistic Spectrum Access model for packet transmission between two unlicensed users. We suggest a priority scheme for a unlicensed user to concurrently transmit different types of packets. Our scheme reserves a fixed number of queueing places in the buffer for the prioritized packets. We study the transmission performance under both the priority scheme and imperfect spectrum sensing, with respect to the blocking probabilities, average transmission delay and transmission throughput of unlicensed users packets. The Markov chain based numerical analysis is validated by simulation experiments. Our results show that the suggested priority scheme is able to enhance transmission throughput of unlicensed users packets, together with significant decreased average transmission delay and minor decreased total transmission throughput.

In this paper, we analyze the secondary network transmission given a packet timeout threshold and a target bit error rate (BER) in a downlink multiservice spectrum sharing cognitive radio network (CRN). Under the joint constraint of primary user (PU) outage probability and secondary user (SU) peak transmit power, the adaptive transmit power policy of the SU transmitter (SU-Tx) is obtained. The throughput is maximized by transmitting to the secondary receiver (SU-Rx) having the best channel condition. We maintain fairness with a minimum resource guarantee assigned to each packet of a class of service. Accordingly, the average packet transmission time is determined. In addition, employing an M/G/1/B queueing model, the packet blocking probability is given to develop expressions of the average throughput and packet loss probability for the secondary class of service. Moreover, the quality of experience (QoE) is evaluated based on the relationship between the packet loss probability and mean opinion score (MOS). The results show that the secondary network achieves the stable transmission quality and minimizes packet loss when the number of SU-Rx becomes large.

In dynamic spectrum access networks, the unused licensed spectrum of primary users (PU) is opened to unlicensed secondary user (SU) for improving spectrum efficiency. The problem we study in this paper is to maximize the SU throughput while guaranteeing PU performance. We design a simple time-based threshold strategy to maximize the SU throughput while guaranteeing the PU performance by learning directly from the interaction with PU environment. At a given time, the SU decides if it should transmit and if so to protect the PU performance. It is observed that such strategies perform closely to the strategy optimized based on prior knowledge about PU traffic models. Simulations are used for performance evaluation.

In dynamic spectrum access networks, the unused licensed spectrum used by primary users (PU) is opened to unlicensed secondary users (SU) for improving spectrum efficiency. We design a simple time-based threshold policy for collective protection of PUs, enabled by an out-of-band channel. In particular, multiple SUs may be widely distributed in a geographic location. The interference that collocated SUs cause to each other, termed self-interference, becomes a major source that may degrade the SUs communication performance. We establish an analytical framework for carrier sense multiple access (CSMA) based coexistence mechanisms when integrated into a family of time based threshold policies, and study its performance though theoretical analysis.

In cognitive radio networks, unlicensed users need to learn from environmental changes. This is a process that can be done in a cooperative or non-cooperative manner. Due to the competition for channel utilization among unlicensed users, the non-cooperative approach may lead to overcrowding in the available channels. This paper is about a fuzzy-logic based decision making algorithm for competition-based channel selection. The underlying decision criterion integrates both the statistics of licensed users' channel occupancy and the competition level of unlicensed users. By using such an algorithm, the unlicensed user competitors can achieve an efficient sharing of the available channels. Simulation results are reported to demonstrate the performance and effectiveness of our suggested algorithm.

Opportunistic spectrum access (OSA) is a technology that allows unlicensed users to access spectrum holes and to provide so efficient use of radio resources. Most of the studies done on OSA focus on the situation when the unlicensed user performs the spectrum handoff only within a single cognitive radio network (so-called intra-handoff). In this paper, we consider the users (licensed or unlicensed) to be able to do inter-handoff among different cognitive radio cells as well. The cells provide priority to inter-handoff users. By considering multiple cells being in steady-state, the arrival rates of inter-handoff users are determined. We study the OSA performance of unlicensed users under both intra- and inter-handoff schemes, with respect to the blocking and forced-termination probabilities of unlicensed users as well as the unlicensed user service-completion and inter-handoff throughputs. Our Markov chain based numerical analysis is validated by simulation experiments.