Connectivity of Clustered and Multi-type User CR Network: A Percolation Based Approach

For the clustered, large scale ad hoc cognitive radio network with multi-type users, we address the percolation-based connectivity problem, in which the existence of a communication link between two secondary users depends on not only the distance between them, the transmitting and receiving activities of nearby primary users, but also the neighboring user’s type. From the mean-field approximation perspective, we firstly give the sufficient condition for the single type (here “type” means transmission radius) clustered secondary users on how the marginal nodes in the clusters are correlated to provide the critical percolation radius. Then the connectivity of the secondary users with inhomogeneous node distribution is studied, where two types of sub-critical secondary users are migrated into a super-critical cognitive user network through a multi-type branching process in random environment, which essentially is a percolation parameter optimization problem. Various simulations are performed to show the percolation is effective both in theory and practice in guidance of the deployment of the wireless network.

[1]  Kwang-Cheng Chen,et al.  Cognitive Radio-Enabled Network-Based Cooperation: From a Connectivity Perspective , 2012, IEEE Journal on Selected Areas in Communications.

[2]  Sisi Liu,et al.  Cluster-Based Control Channel Allocation in Opportunistic Cognitive Radio Networks , 2012, IEEE Transactions on Mobile Computing.

[3]  Rahul Vaze Percolation and connectivity on the signal to interference ratio graph , 2012, 2012 Proceedings IEEE INFOCOM.

[4]  Dianjie Lu,et al.  Connectivity of large-scale Cognitive Radio Ad Hoc Networks , 2012, 2012 Proceedings IEEE INFOCOM.

[5]  Thomas G. Robertazzi,et al.  Critical connectivity phenomena in multihop radio models , 1989, IEEE Trans. Commun..

[6]  Edmund M. Yeh,et al.  Information dissemination in large-scale wireless networks with unreliable links , 2008, WICON 2008.

[7]  Ian F. Akyildiz,et al.  Percolation theory based connectivity and latency analysis of cognitive radio ad hoc networks , 2011, Wirel. Networks.

[8]  Edmund M. Yeh,et al.  Connectivity, Percolation, and Information Dissemination in Large-Scale Wireless Networks with Dynamic Links , 2009, ArXiv.

[9]  P. Thiran,et al.  Percolation in the signal to interference ratio graph , 2006, Journal of Applied Probability.

[10]  Ananthram Swami,et al.  Connectivity of Heterogeneous Wireless Networks , 2009, IEEE Transactions on Information Theory.

[11]  T. E. Harris,et al.  The Theory of Branching Processes. , 1963 .

[12]  François Baccelli,et al.  Impact of interferences on connectivity in ad hoc networks , 2005, IEEE/ACM Transactions on Networking.

[13]  James Gross,et al.  Robust Clustering of Ad-Hoc Cognitive Radio Networks under Opportunistic Spectrum Access , 2011, 2011 IEEE International Conference on Communications (ICC).