This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Multicast Capacity Scaling Laws for Multihop Cognitive Networks
Nov. 2012 (vol. 11 no. 11)
pp. 1627-1639
Cheng Wang, Tongji University, Shanghai
Shaojie Tang, Illinois Institute of Technology, Chicago
Xiang-Yang Li, Illinois Institute of Technology, Chicago
Changjun Jiang, Tongji University, Shanghai
In this paper, we study multicast capacity for cognitive networks. We consider the cognitive network model consisting of two overlapping ad hoc networks, called the primary ad hoc network (PaN) and secondary ad hoc network (SaN), respectively. PaN and SaN operate on the same space and spectrum. For PaN (or SaN, respectively), we assume that primary (or secondary, respectively) nodes are placed according to a Poisson point process of intensity n (or m, respectively) over a unit square region. We randomly choose n_s (or m_s, respectively) nodes as the sources of multicast sessions in PaN (or SaN, respectively), and for each primary source v^p (or secondary source v^s, respectively), we pick uniformly at random n_d primary nodes (or m_d secondary nodes, respectively) as the destinations of v^p (or v^s, respectively). Above all, we assume that PaN can adopt the optimal protocol in terms of the throughput. Our main work is to design the multicast strategy for SaN by which the optimal throughput can be achieved, without any negative impact on the throughput for PaN in order sense. Depending on n_d and n, we choose the optimal one for PaN from two strategies called percolation strategy and connectivity strategy, respectively. Subsequently, we design the corresponding throughput-optimal strategy for SaN. We derive the regimes in terms of n, n_d, m, and m_d in which the upper bounds on multicast capacities for PaN and SaN can be achieved simultaneously. Unicast and broadcast capacities for the cognitive network can be derived by our results as the special cases by letting n_d=1 (or m_d=1) and n_d=n-1 (or m_d=m-1), respectively, which enhances the generality of this work.
Index Terms:
Throughput,Ad hoc networks,Road transportation,Slabs,Routing,Lattices,Mobile computing,percolation theory,Cognitive networks,wireless ad hoc networks,multicast capacity,random networks
Citation:
Cheng Wang, Shaojie Tang, Xiang-Yang Li, Changjun Jiang, "Multicast Capacity Scaling Laws for Multihop Cognitive Networks," IEEE Transactions on Mobile Computing, vol. 11, no. 11, pp. 1627-1639, Nov. 2012, doi:10.1109/TMC.2011.212
Usage of this product signifies your acceptance of the Terms of Use.