CROR: Coding-Aware Opportunistic Routing in Multi-Channel Cognitive Radio Networks

Cognitive radio (CR) is a promising technology to improve spectrum utilization. However, spectrum availability is uncertain which mainly depends on primary user's (PU's) behaviors. This makes it more difficult for most existing CR routing protocols to achieve high throughput in multi-channel cognitive radio networks (CRNs). Inter-session network coding and opportunistic routing can leverage the broadcast nature of the wireless channel to improve the performance for CRNs. In this paper we present a coding aware opportunistic routing protocol for multi-channel CRNs, cognitive radio opportunistic routing (CROR) protocol, which jointly considers the probability of successful spectrum utilization, packet loss rate, and coding opportunities. We evaluate and compare the proposed scheme against three other opportunistic routing protocols with multichannel. It is shown that the CROR, by integrating opportunistic routing with network coding, can obtain much better results, with respect to throughput, the probability of PU-SU packet collision and spectrum utilization efficiency.Comment: 6 pages, 8 figures, to appear in Proc. of IEEE GlobeCom 201

Software-defined routing protocol for mobile cognitive radio networks : a cross-layer perspective

The growing demand for wireless applications, combined with inefficient spectrum use, necessitates developing a new wireless communication paradigm that focuses on dynamic spectrum access rather than the fixed spectrum using cognitive radio technology. The unlicensed user, known as secondary user or cognitive user, uses cognitive radio technology to grow opportunistic communication over licensed spectrum bands and improve spectrum management performance. The routing protocol in Cognitive Radio Networks (CRNs) serves as a communication backbone, allowing data packets to transfer between cognitive user nodes through multiple paths and channels. However, the problem of routing in CRNs is to create a robust-stable route over higher channel availability. The previously developed protocols missed opportunities to exploit the time-variant channel estimation technique, which selects the best route using the cross-layer routing decision engine to track the adverse impact of cognitive user mobility and primary user activity. This study aims to construct a robust routing path while limiting interference with primary user activity, delaying routing, and maximizing routing throughput. Here, a new routing framework is created in this study to explore new extended routing functions and features from the lower layers (Physical layer and Data Link layer) feedback to improve routing performance. Then, the link-oriented channel availability and channel quality have been developed based on two reliable metrics, which are channel availability probability and channel quality, to estimate and select a channel that maximizes link-throughput. Furthermore, this study proposes a novel cross layer routing protocol, namely, the Software-Defined Routing Protocol. It is a cross-layer method to combine the lower layer (Physical layer and Data Link layer) sensing derived from the channel estimation model. It periodically updates the routing table for optimal route decision making. The output simulation of the channel estimation method has shown that it has produced a powerful channel selection strategy to maximize the average rate of link throughput and achieved a channel estimate under the time-variant effect. Extensive simulation experiments have been performed to evaluate the proposed protocol in compression with the existing benchmark protocols, namely, dual diversity cognitive Ad-hoc routing protocol and cognitive Ad-hoc on-demand distance vector. The proposed protocol outperforms the benchmarks, resulting in increasing the packet delivery ratio by around (11.89%-12.80%), reducing delay by around (2.74%-4.05%), reducing overhead by around (14.31%-18.36%), and increasing throughput by around (23.94%-28.35%). The software-defined routing protocol, however, lacks the ability to determine the better idle channel at high-speed node mobility. In conclusion, the cross-layer routing protocol successfully achieves high routing performance in finding a robust route, selecting high channel stability, and reducing the probability of interference with primary users for continued communication

QoS based Route Management in Cognitive Radio Networks

Cognitive radio has become a revolutionary technology that enables the functionalities of dynamic spectrum access. These are the radios that can be programmed and configured dynamically and aims at enhancing the efficiency of spectrum usage by allowing unlicensed users to access/share the licensed spectrum. Cognitive radio networks, a network of cognitive radios, are smart networks that automatically sense the channel and adjust the network parameters accordingly. Therefore, cognitive radio networks raise many challenges such as power management, spectrum management, route management, environment awareness, path robustness, and security issues. As Cognitive Radio (CR) enables dynamic spectrum access which causes adverse effects on network performance because routing protocols that exists were designed considering fixed frequency band. Also, effective routing in CRNs needs local and continual knowledge of its environment. If licensed user (primary user) requests for its channel which is currently used by unlicensed user (secondary user) then unlicensed user has to return the channel to licensed user. However, unlicensed user has to search for another channel and accordingly it needs to seek for route discovery. So, all these important factors need to be accounted for while performing route management. In this thesis, QoS based route management technique is proposed. Proposed model makes use of functionalities of profile exchange mechanism and location services. The proposed QoS routing algorithm contains following elements: (a) each licensed user prepares channel property table which lists all the properties of the channel, whereas all the unlicensed users in the network due to cognitive functionality sense the environment and prepare a table which contains identification information of neighbor node and channel present between them. All unlicensed users share their table with central entity. (b) Central entity with the help of received information and location services prepares routing table for all the nodes in the network. (c) Various Quality of Service (QoS) metrics are considered to improve the performance of the network. The metrics include power transmission, probability of channel availability, probability of PU presence, and Expected Transmission Count. Central entity provides a route to destination based on the QoS level requested by unlicensed users. Proposed model provides a route with minimum end-to-end transmission power, high probability of channel availability, low probability of PU presence and low value of expected transmission count, to increase life span of users in the network, to decrease the delay, to stabilize wireless connectivity and to increase the throughput of the communication, respectively, based on the QoS level requested by a secondary user. Performance of the network is examined by simulating the network in NS2 under simulation environment with the help of end to end delay, throughput, packet delivery ratio, and % packet loss. Proposed model performs better than two other reference models mentioned in the thesis and is shown in the simulation results