Probabilistic Analysis of Wireless Systems Using Theorem Proving
Electronic Notes in Theoretical Computer Science (ENTCS)
Achievable throughput in two-scale wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
The capacity of wireless networks: information-theoretic and physical limits
IEEE Transactions on Information Theory
Opportunistic scheduling in large-scale wireless networks
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Opportunistic relaying in wireless networks
IEEE Transactions on Information Theory
Increased connectivity at lower cost: The case for multi-radio nodes in multi-hop wireless networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Throughput scaling of wireless networks with random connections
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Optimal throughput of two-hop relay networks with different relay cooperation
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Throughput scaling of wireless networks with random connections
IEEE Transactions on Information Theory
Virtual cooperation for throughput maximization in distributed large-scale wireless networks
EURASIP Journal on Advances in Signal Processing - Special issue on cooperative MIMO multicell networks
Probabilistic flooding in stochastic networks: Analysis of global information outreach
Computer Networks: The International Journal of Computer and Telecommunications Networking
Network topology models for multihop wireless networks
ISRN Communications and Networking
| Hi-index | 755.02 |
A network of nodes in which pairs communicate over a shared wireless medium is analyzed. We consider the maximum total aggregate traffic flow possible as given by the number of users multiplied by their data rate. The model in this paper differs substantially from the many existing approaches in that the channel connections in this network are entirely random: rather than being governed by geometry and a decay-versus-distance law, the strengths of the connections between nodes are drawn independently from a common distribution. Such a model is appropriate for environments where the first-order effect that governs the signal strength at a receiving node is a random event (such as the existence of an obstacle), rather than the distance from the transmitter. It is shown that the aggregate traffic flow as a function of the number of nodes n is a strong function of the channel distribution. In particular, for certain distributions the aggregate traffic flow is at least n/(logn)d for some d0, which is significantly larger than the O(√n) results obtained for many geometric models. The results provide guidelines for the connectivity that is needed for large aggregate traffic. The relation between the proposed model and existing distance-based models is shown in some cases.