A Dynamic Spectrum Access Strategy Based on Real-Time Usability in Cognitive Radio Sensor Networks.
ABSTRACT Currently, Wireless Sensor Networks (WSN) mostly operate on the fixed and unlicensed Industrial, Scientific and Medical (ISM) spectrum. With the increasing spectrum shortage in WSN, the Cognitive Radio Sensor Networks (CRSN) is proposed to employ the Cognitive Radio (CR) technology to utilize the spectrum resources dynamically (i.e., Dynamic Spectrum Access, DSA). However, it's a challenge to increase the delivery rate and the throughput in the CRSN because of the power and process restrictions. In this paper, with the consideration of the spectrum idle condition and communication capability, a novel DSA strategy based on the Real-time Usability (DSARU) is presented. And the energy-saving updating algorithm of the spectrum real-time usability is proposed to sense the spectrum changes. Based on the IEEE 802.15.4, DSARU simulation model and experiment system are set up to evaluate the transmission performances. Both simulation and experiment results demonstrate that the DSARU strategy can efficiently increase the delivery rate and throughput, especially under the condition of spectrum interference.
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ABSTRACT: Due to the rapid increase in the usage and demand of wireless sensor networks (WSN), the limited frequency spectrum available for WSN applications will be extremely crowded in the near future. More sensor devices also mean more recharging/replacement of batteries, which will cause significant impact on the global carbon footprint. In this paper, we propose a relay-assisted cognitive radio sensor network (CRSN) that allocates communication resources in an environmentally friendly manner. We use shared band amplify and forward relaying for cooperative communication in the proposed CRSN. We present a multi-objective optimization architecture for resource allocation in a green cooperative cognitive radio sensor network (GC-CRSN). The proposed multi-objective framework jointly performs relay assignment and power allocation in GC-CRSN, while optimizing two conflicting objectives. The first objective is to maximize the total throughput, and the second objective is to minimize the total transmission power of CRSN. The proposed relay assignment and power allocation problem is a non-convex mixed-integer non-linear optimization problem (NC-MINLP), which is generally non-deterministic polynomial-time (NP)-hard. We introduce a hybrid heuristic algorithm for this problem. The hybrid heuristic includes an estimation-of-distribution algorithm (EDA) for performing power allocation and iterative greedy schemes for constraint satisfaction and relay assignment. We analyze the throughput and power consumption tradeoff in GC-CRSN. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results.Sensors 01/2013; 13(4):4884-905. · 2.05 Impact Factor
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ABSTRACT: A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized.Sensors 01/2013; 13(9):11196-228. · 2.05 Impact Factor