Description
Date depot: 1 janvier 1900
Titre: Opportunistic Data Dissemination in Ad-Hoc Cognitive Radio Networks
Directeur de thèse:
Serge FDIDA (LIP6)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé:
Recent advances in communication technologies and the proliferation of wireless computing
and communication devices make the radio spectrum overcrowded. However, experiments
from the Federal Communication Commission (FCC) reveals that the spectrum utilization
varies from 15% − 85%. Consequently, Cognitive Radio Networks (CRNs) are proposed to
utilize the radio spectrum opportunistically.
In types of cognitive radio networks where channels for transmission are opportunistically
selected – also called Cognitive Radio Ad-Hoc Networks –, reliability in data dissemination
is difficult to achieve. First, in addition to the already known issues of wireless
environments, the diversity in the number of channels that each cognitive node can use adds
another challenge by limiting node’s accessibility to its neighbors. Second, Cognitive Radio
(CR) nodes have to compete with the Primary Radio (PR) nodes for the residual resources
on channels and use them opportunistically. Besides, CR nodes should communicate in a
way that does not disturb the reception quality of PR nodes by limiting CR-to-PR interference.
Therefore, a new channel selection strategy is required which cause less harmful
interference to PR nodes and try to maximize the chances that the message is delivered to
the neighboring cognitive radio receivers, thus increasing the data dissemination reachability.
In this thesis, we propose SURF, a distributed channel selection strategy for reliable
data dissemination in multi-hop cognitive radio ad-hoc networks. SURF classifies the
available channels on the basis of primary radio unoccupancy and the number of cognitive
radio neighbors using the channels. Simulation results in NS-2 confirmed that SURF is
effective in selecting the best channels for data dissemination, when compared to related
approaches. We observe that the channel selection strategies are greatly influenced by the
primary radio nodes activity. Next in this thesis, we study and analyze the impact of
PR nodes activity patterns on different channel selection strategies through NS-2 based
simulations. We observed that intermittent PR activity is the case where clever solutions
need to operate. This is where SURF gives the best results and the target region to avail
communication opportunities.
Finally, in this thesis, we go one step further and check the applicability and feasibility
of SURF. In this perspective, first we propose a cognitive radio based Internet access framework
for disaster response networks. We discuss the architectural details and the working
principle of the proposed framework. We highlight the challenges and issues related with
the deployment and connectivity of the framework. Second, we discuss the applicability
of SURF in the context of channel bonding and in this regard, we discuss an interference
based channel bonding strategy for cognitive radio networks.
Doctorant.e: Rehmani Mubashir Husain