Dynamic Spectrum Allocation in Wireless Cognitive Sensor Networks: Improving Fairness and Energy Efficiency

This paper considers the centralized spectrum allocations in resource-constrained wireless sensor networks with the following goals: (1) allocate spectrum as fairly as possible, (2) utilize spectrum resource maximally, (3) reflect the priority among sensor data, and (4) reduce spectrum handoff. The problem is formulated into a multi-objective problem, where we propose a new approach to solve it using modified game theory (MGT). In addition, cooperative game theory is adopted to obtain approximated solutions for MGT in reasonable time. The results obtained from numerical experiments show that the proposed algorithm allocates spectrum bands fairly with well observing each sensor's priority and nearly minimal spectrum handoffs.

[1]  Brian M. Sadler,et al.  Dynamic spectrum access in WLAN channels: empirical model and its stochastic analysis , 2006, TAPAS '06.

[2]  M. Sunar,et al.  A Comparative Study of Multiobjective Optimization Methods in Structural Design , 2001 .

[3]  Mahmoud Naghshineh,et al.  Channel assignment schemes for cellular mobile telecommunication systems: A comprehensive survey , 2000, IEEE Communications Surveys & Tutorials.

[4]  K. J. Liu,et al.  Collusion-Resistant Dynamic Spectrum Allocation for Wireless Networks via Pricing , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[5]  Deep Medhi,et al.  Routing, flow, and capacity design in communication and computer networks , 2004 .

[6]  Abhay Parekh,et al.  Spectrum sharing for unlicensed bands , 2005, IEEE Journal on Selected Areas in Communications.

[7]  Haitao Zheng,et al.  Distributed spectrum allocation via local bargaining , 2005, 2005 Second Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2005. IEEE SECON 2005..

[8]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[9]  U. Berthold,et al.  Guidelines for designing OFDM overlay systems , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[10]  Friedrich Jondral,et al.  Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency , 2004, IEEE Communications Magazine.

[11]  Q. Zhao,et al.  Decentralized cognitive mac for dynamic spectrum access , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[12]  Zhu Han,et al.  Fair multiuser channel allocation for OFDMA networks using Nash bargaining solutions and coalitions , 2005, IEEE Transactions on Communications.

[13]  Lijun Qian,et al.  Energy Efficient Adaptive Modulation in Wireless Cognitive Radio Sensor Networks , 2007, 2007 IEEE International Conference on Communications.

[14]  H. Tang,et al.  Some physical layer issues of wide-band cognitive radio systems , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[15]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[16]  Lang Tong,et al.  A Measurement-Based Model for Dynamic Spectrum Access in WLAN Channels , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.

[17]  Michael L. Honig,et al.  Auction-Based Spectrum Sharing , 2006, Mob. Networks Appl..