Characterization of End-to-end Path Selection for Cognitive Radio Wireless Mesh Networks

Abstract: The Cognitive Radio (CR) can delivers the environment to Secondary Users (SUs) of Wireless Mesh Network (WMN) to utilize unused spectrum of Primary Users (PUs) opportunistically. The CR can improve the spectrum usage of the WMN. However, this rises the some additional complexities for the SUs such as spectrum heterogeneity, unpredictable PU activity and interference constraints. In this paper an analytical model has been developed to analyse these complexities for each SU node and link characteristics for end-to-end optimal Path and channel assignment. Numerical results show that the analytical model is an effective tool to investigate the effects of the PU activities and channel heterogeneity on the network performance

Energy Aware Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks

Cognitive radio networks (CRNs) emerged as a paradigm to solve the problem of limited spectrum availability and the spectrum underutilization in wireless networks by opportunistically exploiting portions of the spectrum temporarily vacated by licensed primary users (PUs). Routing in CRNs is a challenging problem due to the PU activities and mobility. On the other hand, energy aware routing is very important in energy-constraint CRNs. In addition, it is crucial that CR users efficiently exchange data with each other before the appearance of PUs. To design a robust routing scheme for mobile CR ad hoc networks (CRANs), the constraints on residual energy of each CR user, reliability, and the protection of PUs must additionally be taken into account. Moreover, multipath routing has great potential for improving the end-to-end performance of ad hoc networks. Considering all these evidences, in this paper, we propose an energy aware on-demand multipath routing (EOMR) protocol for mobile CRANs to ensure the robustness and to improve the throughput. The proposed routing scheme involves energy efficient multipath route selection and spectrum allocation jointly. The simulation results show that our approach improves the overall performance of the network

Resource Allocation and Path Selection Strategies for Cognitive Radio Multihop Networks

The next-generation cellular wireless networks will support high data rates and provide quality of service (QoS) for multimedia applications with increased network capacity. Under limited frequency resources, the conventional approach to increase network capacity is to install more base stations (BSs) to exploit spatial reuse. This solution is not very efficient because the cost of the BS transceiver is quite high. An alterna- tive approach is to employ relay stations (RSs) as intermediate nodes to establish multihop communication paths between mobile hosts and their corresponding BSs. Multihop cellular networks (MCN) can potentially enhance coverage, data rates, QoS performance in terms of call block- ing probability, bit error rate, as well as QoS fairness for different users. A number of different architectures, protocols, and analytical models for MCNs have been proposed in the literature where different system aspects were investigated. This thesis aims to present strategies of re- source allocation (RA) and path selection (PS) for cognitive radio (CR) multi-hop communications over a packet-oriented and bit-interleaved- coded OFDM transmission, employing practical modulation and coding schemes. As a promising technology, cognitive radio can be leveraged by the cellular network to increase the overall spectral efciency by allowing additional users in an already crowded spectrum. Here, we assume that a secondary transmitter (ST) adapt his parameters for transmitting to a secondary receiver (SR) or to a relay, over sections of spectrum owned by licensed or primary users (PUs), without harming the quality of service of the latter. This approach is known as underlay. The performance of the system are evaluated in terms of goodput (GP), which is defined as the number of information bits delivered in error free packets per unit of time. It is able to quantify the trade-off between data rate and link reliability, and it is a more suitable metric to quantify the actual perfor- mance of packet-oriented systems, employing practical modulation and coding schemes, respect to the capacity for example. A generic trans- mitter of the network is able to optimize the GP by a proper selection of the transmission parameters, if the channel state information (CSI) are perfect. In most wireless networks, because of channel estimation errors and channel feedback delay, this CSI will not be perfect there- fore any transmitting node only has outdated and imperfect CSI and the channel prediction and as a consequence, a predicted GP (PGP), will be optimized. GP depends on PER that is not easy to calculate for a multi-carrier system and so will be use kESM technique. From here a Local-RA (L-RA) technique and a Sub-Optimal PS (Sub-PS) strategies are formulated for non-cooperative CR multi-hop communications, ex- ploiting xed decode-and-forward (DF) relay nodes (RNs). With these strategies we are able to reduce the signaling over the feedback channel and the computational complexity, compared to the Optimal-RA with Optimal-PS method, paying a very little reduction of GP. Finally we will evaluate whether the increase of the number of relays corresponds to a performance increase

QoS based Route Management in Cognitive Radio Networks

Cognitive radio networks are smart networks that automatically sense the channel and adjust the network parameters accordingly. Cognitive radio is an emerging technology that enables the dynamic deployment of highly adaptive radios that are built upon software defined radio technology. The radio technology allows the unlicensed operation to be in the licensed band. The cognitive radio network paradigm therefore raises many technical challenges such as the power efficiency, spectrum management, spectrum detection, environment awareness, the path selection as well as the path robustness, and security issues. Traditionally, in the routing approaches in the wired network, each node allows a maximum load through the selected route while traditionally in the routing approaches in wireless network, each node broadcasts its request with the identification of the required destination. However, the existing routing approaches in cognitive radio networks (CRN) follow the traditional approaches in wireless network especially those applied for ad hoc networks. In addition, these traditional approaches do not take into account spectrum trading as well as spectrum competition among licensed users (PUs). In this thesis, a novel QoS based route management approach is proposed by introducing two different models; the first model is without game theory and the second model is with game theory. The proposed QoS routing algorithm contains the following elements: (i) a profile for each user, which contains different parameters such as the unlicensed user (secondary user, SU) identification, number of neighbors, channel identification, neighbor identification, probabilities of idle slots and the licensed user (primary user, PU) presence. In addition, the radio functionality feature for CRN nodes gives the capability to sense the channels and therefore each node shares its profile with the sensed PU, which then exchanges its profile with other PUs, (ii) spectrum trading, a PU calculates its price based on the SU requirements, (iii) spectrum competition, a new coefficient α is defined that controls the price because of competition among PUs and depends on many factors such as the number of primary users, available channels, and duration of the usage, (iv) a new function called QoS function is defined to provide different levels of quality of service to SUs, and (v) the game theory concept adds many features such as the flexibility, the dynamicity in finding solutions to the model and the dynamic behaviors of users. Based on the previous elements, all possible paths are managed and categorized based on the level of QoS requested by SUs and the price offered by the PU. The simulation results show that the aggregate throughput and the average delay of the routes determined by the proposed QoS routing algorithm are superior to existing wireless routing algorithms. Moreover, network dynamics is examined under different levels of QoS