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Achieving Congestion Mitigation Using Distributed Power Control for Spectrum Sensor Nodes in Sensor Network-Aided Cognitive Radio Ad Hoc Networks

School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
China Telecommunication Technology Labs-Terminals, China Academy of Information and Communications Technology, Beijing 100191, China
Author to whom correspondence should be addressed.
Academic Editor: Francisco Javier Falcone Lanas
Sensors 2017, 17(9), 2132;
Received: 13 August 2017 / Revised: 9 September 2017 / Accepted: 13 September 2017 / Published: 15 September 2017
(This article belongs to the Special Issue Cognitive Radio Sensing and Sensor Networks)
The data sequence of spectrum sensing results injected from dedicated spectrum sensor nodes (SSNs) and the data traffic from upstream secondary users (SUs) lead to unpredictable data loads in a sensor network-aided cognitive radio ad hoc network (SN-CRN). As a result, network congestion may occur at a SU acting as fusion center when the offered data load exceeds its available capacity, which degrades network performance. In this paper, we present an effective approach to mitigate congestion of bottlenecked SUs via a proposed distributed power control framework for SSNs over a rectangular grid based SN-CRN, aiming to balance resource load and avoid excessive congestion. To achieve this goal, a distributed power control framework for SSNs from interior tier (IT) and middle tier (MT) is proposed to achieve the tradeoff between channel capacity and energy consumption. In particular, we firstly devise two pricing factors by considering stability of local spectrum sensing and spectrum sensing quality for SSNs. By the aid of pricing factors, the utility function of this power control problem is formulated by jointly taking into account the revenue of power reduction and the cost of energy consumption for IT or MT SSN. By bearing in mind the utility function maximization and linear differential equation constraint of energy consumption, we further formulate the power control problem as a differential game model under a cooperation or noncooperation scenario, and rigorously obtain the optimal solutions to this game model by employing dynamic programming. Then the congestion mitigation for bottlenecked SUs is derived by alleviating the buffer load over their internal buffers. Simulation results are presented to show the effectiveness of the proposed approach under the rectangular grid based SN-CRN scenario. View Full-Text
Keywords: cognitive radio; sensor network; congestion mitigation; power control cognitive radio; sensor network; congestion mitigation; power control
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Zhang, L.; Xu, H.; Zhuo, F.; Duan, H. Achieving Congestion Mitigation Using Distributed Power Control for Spectrum Sensor Nodes in Sensor Network-Aided Cognitive Radio Ad Hoc Networks. Sensors 2017, 17, 2132.

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