A Cognitive Approach to the Detection of Spectrum Holes in Wireless Networks

The experience of ubiquitous and seamless ac- cess to heterogeneous mobile communication networks is one of the core issues of today's research. This comes along with an increasing demand in bandwidth. However, bandwidth as a natural resource is limited by technical constraints and, as several measurements have shown, is currently used very in- efficiently due to a static allocation. Consequently, we have to consider spectrum allocation techniques and employ use- ful applications for the detection of vacant frequency bands. In this paper, we present a novel, swarm-behavior based ap- proach for the detection of spectrum holes in cognitive wire- less networks. It is based on the fact that several cogni- tive radios form a cognitive network. This network is then split up into several cognitive sub-networks that collaborate among each other and scan the frequency range simultane- ously. Thus, several vacant frequency bands can be found and the overall processing time can be reduced. In addition, fading effects due to multi-path propagation can be met in a more efficient way.

[1]  M.A. El-Sharkawi,et al.  Swarm intelligence for routing in communication networks , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[2]  Jürgen Branke,et al.  Multiswarms, exclusion, and anti-convergence in dynamic environments , 2006, IEEE Transactions on Evolutionary Computation.

[3]  J. I. Mararm,et al.  Energy Detection of Unknown Deterministic Signals , 2022 .

[4]  Friedrich Jondral,et al.  Calculation of detection and false alarm probabilities in spectrum pooling systems , 2005, IEEE Communications Letters.

[5]  R. Berezdivin,et al.  Next-generation wireless communications concepts and technologies , 2002, IEEE Commun. Mag..

[6]  E. Visotsky,et al.  On collaborative detection of TV transmissions in support of dynamic spectrum sharing , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[7]  Anant Sahai,et al.  Cooperative Sensing among Cognitive Radios , 2006, 2006 IEEE International Conference on Communications.

[8]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[9]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[10]  Joseph Mitola,et al.  Cognitive Radio An Integrated Agent Architecture for Software Defined Radio , 2000 .

[11]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

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

[13]  E. Maasland,et al.  Auction Theory , 2021, Springer Texts in Business and Economics.

[14]  T. A. Weiss,et al.  A diversity approach for the detection of idle spectral resources in spectrum pooling systems , 2003 .

[15]  Qi Bi,et al.  Wireless mobile communications at the start of the 21st century , 2001 .