Hicham Khalife

Probabilistic Path Selection in Opportunistic Cognitive Radio Networks

We present a novel routing approach for multichannel cognitive radio networks (CRNs). Our approach is based on probabilistically estimating the available capacity of every channel over every CR-to-CR link, while taking into account primary radio (PR). Our routing design consists of two main phases. In the first phase, the source node attempts to compute the most probable path (MPP) to the destination (including the channel assignment along that path) whose bandwidth has the highest probability of satisfying a required demand D. In the second phase, we verify whether the capacity of the MPP is indeed sufficient to meet the demand at confidence level delta. If that is not the case, we judiciously add channels to the links of the MPP such that the augmented MPP satisfies the demand D at the confidence level delta. We show through simulations that our protocol always finds the best path to the destination, achieving in some cases up to 200% improvement in connection acceptance rate compared to the traditional Dijkstra.

Multihop cognitive radio networks: to route or not to route

Routing is a fundamental issue to consider when dealing with multihop cognitive radio networks. We investigate in this work, the potential routing approaches that can be employed in such adaptive wireless networks. We argue that in multihop cognitive radio environments no general routing solution can be proposed, but cognitive environments can be classified into three separate categories, each requiring specific routing solutions. Basically, this classification is imposed by the activity of the users on the licensed bands that cognitive radios try to access. First, over a relatively static primary band, where primary nodes idleness largely exceeds cognitive users communication durations, static mesh routing solutions can be reused, whereas second, over dynamically available spectrum bands new specific routing solutions have to be proposed, we give some guidelines and insights about designing such solutions. Third, if cognitive radios try to access over highly active and rarely available primary bands, opportunistic forwarding without preestablished routing is to be explored.

SURF: A Distributed Channel Selection Strategy for Data Dissemination in Multi-Hop Cognitive Radio Networks

In this paper, we propose an intelligent and distributed channel selection strategy for efficient data dissemination in multi-hop cognitive radio network. Our strategy, SURF, classifies the available channels and uses them efficiently to increase data dissemination reliability in multi-hop cognitive radio networks. The classification is done on the basis of primary radio unoccupancy and of the number of cognitive radio neighbors using the channels. Through extensive NS-2 simulations, we study the performance of SURF compared to four related approaches. Simulation results confirm that our approach is effective in selecting the best channels for efficient communication (in terms of less primary radio interference) and for highest dissemination reachability in multi-hop cognitive radio networks.

Activity pattern impact of primary radio nodes on channel selection strategies

The performance of cognitive radio network is highly dependent upon the primary radio nodes activity pattern. In this paper, we study and analyze the impact of different PR nodes activity pattern with the help of three performance metrics. In this perspective, we use our channel selection strategy SURF and three other channel selection strategies i.e., Random (RD), Highest Degree (HD), and Selective Broadcasting (SB). We analyze the performance of these channel selection strategies through extensive NS-2 simulations. Moreover, we also analyze how these strategies respond to different PR nodes activity. Simulation results confirm that SURF outperforms RD, HD, and SB in terms of delivery ratio and causes less harmful interference to PR nodes, in all primary radio nodes activity pattern.

A cognitive radio based Internet access framework for disaster response network deployment

In this paper, we propose a cognitive radio based Internet access framework for disaster response network deployment in challenged environments. The proposed architectural framework is designed to help the existent but partially damaged networks to restore their connectivity and to connect them to the global Internet. This architectural framework provides the basis to develop algorithms and protocols for the future cognitive radio network deployments in challenged environments.

Improving Data Dissemination in Multi-hop Cognitive Radio Ad-Hoc Networks

In this paper, we present SURF, a distributed channel selection strategy for efficient data dissemination in multi-hop cognitive radio ad-hoc networks (CRNs). SURF classifies the available channels on the basis of primary radio unoccupancy and the number of cognitive radio neighbors using the channels. Through extensive NS-2 simulations, we compare the performance of SURF with three related approaches. Simulation results confirm that SURF is effective in selecting the best channels for efficient communication and for highest dissemination reachability in multi-hop CRNs.

Mitigating the hospital area communication's interference using Cognitive Radio Networks

The communication infrastructures and devices in hospitals are becoming increasingly wireless because of doctors and nurses are mobile in their work. On the other hand, the hospital patients communications or their monitoring devices generate lot of electromagnetic waves. In this context, deployment of wireless networks should not only meet some performance requirements but should also be aware and able to control interferences. Cognitive Radio Networks (CRNs) seem to be suitable for delivering high-quality communication services and mitigating radio interferences in hospital environment. In this paper, we discuss the design of hospital networks above CRNs to overcome current constraints.

Point to multipoint transport in multichannel wireless environments

We propose a transport protocol capable of dynamically adapting to network and receiver properties in multi-destination, multi-channel wireless networks. The key feature of our solution resides in its ability to convey common traffic to a group of users, while at the same time distributing information to each user as quickly as possible. This is achieved by clustering receivers in groups, each group being served at a suitable throughput. We emphasize in this study on the two groups of receivers case. We show analytically and through OMNet++ simulations that groups formation is decided by the wireless link performance and the proportion of receivers constituting each group. Our solution captures dynamically these effects. Indeed, our transport is capable to cope transparently with wireless links changes (i.e specturm handoff) by adapting dynamically its transmission rate and groups composition. It is therefore adapted for point-to-multipoint cognitive radio networks.

A cooperative MAC protocol for lossy forwarding networks

We present in this paper a MAC layer protocol capable to cope with lossy links in interference-prone wireless environments. Our approach exploits the recent advances in information theory and physical layer coding by relaying at intermediate nodes corrupted messages. To do so, we rely on collaboration between nodes and on a complete rethinking of the header structures and wireless access techniques. Our ns-3 simulations show considerable gains in terms of throughput when compared to classical protocols in low SNR (high interference) situations. Our protocol also includes advanced features in order to mitigate interference and control the level of required reliability.

Bringing SDN to the edge of tactical networks

New services put a lot of pressure on the tactical networks, always requiring more bandwidth, service differentiation and agility. In this paper we propose a framework for managing traffic in future tactical networks. Our solution is based on the Mobile Edge Cloud (MEC) architecture and its close interaction with Software Defined Networking (SDN). The whole facilitated by the spread of Software-Defined Radios (SDR) in tactical radios. We have implemented our architecture in a proof of concept and tested it with 2 tactical scenarios. Our experiments show that centralizing the intelligence in the MEC allows to guarantee the requirements of the tactical applications either by adapting the waveform parameters, or through changing the radio interface or even by reconfiguring the applications. More generally, the best decision can be seen as the optimal reaction to the wireless links variations.