Spectrum and transmission range aware clustering for cognitive radio ad hoc networks

Cognitive radio network (CRN) is a promising technology to overcome the problem of spectrum shortage by enabling the unlicensed users to access the underutilization spectrum bands in an opportunistic manner. On the other hand, the hardness of establishing a fixed infrastructure in specific situations such as disaster recovery, and battlefield communication imposes the network to have an ad hoc structure. Thus, the emerging of Cognitive Radio Ad Hoc Network (CRAHN) has accordingly become imperative. However, the practical implementation of CRAHN faced many challenges such as control channel establishment and the scalability problems. Clustering that divides the network into virtual groups is a reliable solution to handle these issues. However, previous clustering methods for CRAHNs seem to be impractical due to issues regarding the high number of constructed clusters and unfair load distribution among the clusters. Additionally, the homogeneous channel model was considered in the previous work despite channel heterogeneity is the CRN features. This thesis addressed these issues by proposing two clustering schemes, where the heterogeneous channel is considered in the clustering process. First, a distributed clustering algorithm called Spectrum and Transmission Range Aware Clustering (STRAC) which exploits the heterogeneous channel concept is proposed. Here, a novel cluster head selection function is formulated. An analytical model is derived to validate the STRAC outcomes. Second, in order to improve the bandwidth utilization, a Load Balanced Spectrum and Transmission Range Aware Clustering (LB-STRAC) is proposed. This algorithm jointly considers the channel heterogeneity and load balancing concepts. Simulation results show that on average, STRAC reduces the number of constructed clusters up to 51% compared to conventional clustering technique, Spectrum Opportunity based Clustering (SOC). In addition, STRAC significantly reduces the one-member cluster ratio and re-affiliation ratio in comparison to non-heterogeneity channel consideration schemes. LB-STRAC further improved the clustering performance by outperforming STRAC in terms of uniformity and equality of the traffic load distribution among all clusters with fair spectrum allocation. Moreover, LB-STRAC has been shown to be very effective in improving the bandwidth utilization. For equal traffic load scenario, LB-STRAC on average improves the bandwidth utilization by 24.3% compared to STRAC. Additionally, for varied traffic load scenario, LB-STRAC improves the bandwidth utilization by 31.9% and 25.4% on average compared with STRAC for non-uniform slot allocation and for uniform slot allocation respectively. Thus, LB-STRAC is highly recommended for multi-source scenarios such as continuous monitoring applications or situation awareness applications

Multipath Routing over Wireless Mesh Networks

Master'sMASTER OF SCIENC

Transparent Spectrum Co-Access in Cognitive Radio Networks

The licensed wireless spectrum is currently under-utilized by as much as 85%. Cognitive radio networks have been proposed to employ dynamic spectrum access to share this under-utilized spectrum between licensed primary user transmissions and unlicensed secondary user transmissions. Current secondary user opportunistic spectrum access methods, however, remain limited in their ability to provide enough incentive to convince primary users to share the licensed spectrum, and they rely on primary user absence to guarantee secondary user performance. These challenges are addressed by developing a Dynamic Spectrum Co-Access Architecture (DSCA) that allows secondary user transmissions to co-access transparently and concurrently with primary user transmissions. This work exploits dirty paper coding to precode the cognitive radio channel utilizing the redundant information found in primary user relay networks. Subsequently, the secondary user is able to provide incentive to the primary user through increased SINR to encourage licensed spectrum sharing. Then a region of co-accessis formulated within which any secondary user can co-access the licensed channel transparently to the primary user. In addition, a Spectrum Co-Access Protocol (SCAP) is developed to provide secondary users with guaranteed channel capacity and while minimizing channel access times. The numerical results show that the SCAP protocol build on the DSCA architecture is able to reduce secondary user channel access times compared with opportunistic spectrum access and increased secondary user network throughput. Finally, we present a novel method for increasing the secondary user channel capacity through sequential dirty paper coding. By exploiting similar redundancy in secondary user multi-hop networks as in primary user relay networks, the secondary user channel capacity can be increased. As a result of our work in overlay spectrum sharing through secondary user channel precoding, we provide a compelling argument that the current trend towards opportunistic spectrum sharing needs to be reconsidered. This work asserts that limitations of opportunistic spectrum access to transparently provide primary users incentive and its detrimental effect on secondary user performance due to primary user activity are enough to motivate further study into utilizing channel precoding schemes. The success of cognitive radios and its adoption into federal regulator policy will rely on providing just this type of incentive