In this paper, we consider an optimization of number of secondary users (SUs) in a cooperative spectrum sensing by maximizing the energy efficiency of the cognitive radio network. We obtain the mathematical expressions for number of SUs using OR and AND fusion rules at the fusion center. We consider energy detector as an example for the analysis, based on the analysis we show that performance obtained for OR rule is better than the AND rule.

Energy Efficiency in Cognitive Radio Network Using Cooperative Spectrum Sensing

Optimization of cooperative secondary users in cognitive radio networks

Key management is vital part of security; this issue is even bigger in wireless network compared to wired network The distribution of keys in an authenticated manner is a difficult task in WMANET and when a node leaves or joins it need to generate new session key to maintain forward and backward secrecy This paper reviewed technological solutions for managing keys by divide the network into clusters A clustering architecture increases network lifetime and fault tolerance, and results in more efficient use of network resources Cluster head will maintain the group key; it will also update the group key whenever there is a change in the membership And the CH is responsible for inter-cluster and intra-cluster communication A Secondary Cluster Head (SCH) is also elected to avoid the CH from becoming a bottleneck, and also it acts a monitoring node for cluster head lifetime The combination of Weight based Clustering and RSA algorithm has been proposed for secure multicast key distribution in which source node uses Ad hoc On-Demand Distance Vector (AODV) routing protocol to reach its destination The weight based clustering approach is based on combined weight metric that takes into account of several system parameters like the degree difference, transmission range, battery power and mobility of the node The performance of the system is evaluated based on the few metrics like Packet Delivery Ratio (PDR), and end to end delay As demonstrated, our algorithm reduces frequent head election phenomena by having SCH, thus improving overall performance and reducing energy utilization

Weight based clustered key management scheme using RSA for wireless mobile Ad hoc networks

Cooperative spectrum sensing is used to overcome limited computing power of individual nodes to correctly estimate existence of primary user in presence of multipath fading, shadowing and receiver uncertainty. However, conventional cooperative spectrum sensing is not reliable in case when users suffer different fading environment. Thus, to enhance the detection probability of the system weighted cooperative spectrum sensing has been introduced. In this paper, use of weighted cooperative sensing in cognitive radio has been discussed. Weight initially assigned is a constant real value which updates in each round. The procedure has been completed in various rounds and in each round the weight depends on the detection in the previous round. Two methods for spectrum sensing have been compared to find which gives better result.

Comparison of Different Weight Assignment Strategy in Weighted Cooperative Spectrum Sensing

Forming a clustered network structure has been proposed as a solution to increase network performance, scalability, stability and manageability in an ad hoc network. A good clustering algorithm aims to select cluster heads among available nodes so that a number of specific constraints are satisfied; thus the cluster head selection problem is a multiobjective optimization problem. This paper proposes an algorithm on the basis of ant colony optimization (ACO) to be used to solve this problem. The proposed algorithm is a simple, one hop cluster formation algorithm, to form a clustered structure with the minimum number of clusters. The centralized ACO-based clustering algorithm is evaluated and compared with other clustering algorithms in ad hoc networks in terms of cluster density.

/pdf/a-simple-ant-colony-optimization-algorithm-to-select-cluster-4ovu0ibker.pdf

A Simple Ant Colony Optimization Algorithm to Select Cluster Heads in Ad Hoc Networks

Cognitive radio is a promising technique for efficient utilization of idle authorized spectrum since it is able to sense the spectrum and reuse the frequency when the primary user is absent. In order to overcome the fading, shadowing or hidden terminals in independent detection, cooperative detection is presented. The performance of cooperative sensing is studied in this paper. To enhance the sensing ability, some weighted-cooperative spectrum sensing techniques have been proposed. In this paper, different from the previous studies, we propose a novel weighted-clustering cooperative spectrum sensing algorithm based on distances for cognitive radio network. We firstly classify the secondary users into a few clusters according to several existent methods, and then use cluster-head to collect the observation results come from different secondary users in the same cluster and make a cluster-decision. Considering the different distances between the clusters and the fusion center, different weightings are used to weight the cluster- decisions before combining. The simulation results show that our proposed method improve the probability of detection and reduce the probability of error.

/pdf/cooperative-spectrum-sensing-and-weighted-clustering-157div8f2y.pdf

Cooperative Spectrum Sensing and Weighted- Clustering Algorithm for Cognitive Radio Network

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Cooperative Spectrum Sensing and Weighted- Clustering Algorithm for Cognitive Radio Network