In many wireless networks, each node has direct radio link to only a small number of other nodes, called its neighbors. Before efficient routing or other network-level activities are possible, nodes have to discover and identify their neighbors. This is called neighbor discovery. By neighbor discovery, every node tries to determine the set of nodes it can communicate within one wireless hop Fast and efficient discovery of all neighboring nodes by a node new to a neighborhood is Essential and critical to the deployment of wireless networks. The recently emerged technology Cognitive radio (CR) has a promising approach to improve the available spectrum utilization efficiency so as to meet the increased demand for wireless communication, which attempts to search for unused or underutilized channels in the spectrum by scanning the part of wireless spectrum.

Cognitive Radios, Neighbor Discovery, Heterogeneous Network

[1]. Neeraj Mittal, Yanyan Zeng, S.Venkatesan, R. Chandrasekaran, �Randomized Distributed Algorithms for Neighbor Discovery in Multi-Hop Multi-Channel Heterogeneous Wireless Networks� in IEEE 2011 31st International Conference on Distributed Computing Systems.
[2]. Yanyan Zeng, Neeraj Mittal, S. Venkatesan, R. Chandrasekaran �Fast Neighbor Discovery with Lightweight Termination Detection in Heterogeneous Cognitive Radio Networks� @2010 Ninth International Symposium on Parallel and Distributed Computing
[3]. S. Vasudevan, D. Towsley, D. Goeckel, and R. Khalili, �Neighbor Discovery in Wireless Networks and the Coupon Collector�s Problem,� in Proc. 15th ACM Annual International Conference on Mobile Computing and Networking (MobiCom), 2009, pp. 181
[4]. Mr. Pravin Khawse, Prof. S. P. Chhaware �Improved Distributed Heterogeneous Neighbor Discovery In Wireless Networks� in IJRSAT ISSN 2319-2690
[5]. D. Cabric, S. M. Mishra, D. Willkommen, R. W. Brodersen, and A. Wolisz, �A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum,� in Proc. 14th IST Mobile Wireless Communications Summit, Jun. 2005.
[6]. R. W. Broderson, A. Wolisz, D. Cabric, S. M. Mishra, and D. Willkomm, �CORVUS: A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum,� available at http://bwrc.eecs.berkeley.edu/Research/MCMA/.
[7]. M. J. McGlynn and S. A. Borbash, �Birthday Protocols for Low Energy Deployment and Flexible Neighbor Discovery in Ad Hoc Wireless Networks,� in Proceedings of the ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2001.
[8]. S. Vasudevan, D. Towsley, D. Goeckel, and R. Khalili, �Neighbor Discovery in Wireless Networks and the Coupon Collector�s Problem,� in Proceedings of the 14th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), 2009.
[9]. Z. Zhang, �Performance of neighbor discovery algorithms in mobile ad hoc self-configuring networks with directional antennas,� in Proc. IEEE Military Communications Conference, vol. 5, pp. 3162�3168, Oct. 2005. D. D.
[10]. Lin and T. J. Lim, �Subspace-based active user identification for a collision-free slotted ad hoc network,� IEEE Trans. Commun., vol. 52, pp. 612�621, Apr. 2004.
[11]. D. Angelosante, E. Biglieri, and M. Lops, �A simple algorithm for neighbor discovery in wireless networks,� in Proc. IEEE Int�l Conf. Acoustics, Speech and Signal Processing, vol. 3, pp. 169�172, April 2007.
[12]. D. Angelosante, E. Biglieri, and M. Lops, �Neighbor discovery in wireless networks: A multiuser-detection.
[13]. Nasipuri A, Castaneda R, Das SR. Performance of multipath routing for on-demand protocols in mobile ad hoc networks. ACM/Kluwer Mobile Networks and Applications.