Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
On outer bounds to the capacity region of wireless networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Antenna Theory: Analysis and Design
Antenna Theory: Analysis and Design
The capacity of wireless networks
IEEE Transactions on Information Theory
A network information theory for wireless communication: scaling laws and optimal operation
IEEE Transactions on Information Theory
Upper bounds to transport capacity of wireless networks
IEEE Transactions on Information Theory
The transport capacity of wireless networks over fading channels
IEEE Transactions on Information Theory
Information-theoretic upper bounds on the capacity of large extended ad hoc wireless networks
IEEE Transactions on Information Theory
Closing the Gap in the Capacity of Wireless Networks Via Percolation Theory
IEEE Transactions on Information Theory
Wireless Ad Hoc Networks: Strategies and Scaling Laws for the Fixed SNR Regime
IEEE Transactions on Information Theory
Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks
IEEE Transactions on Information Theory
Hi-index | 754.84 |
For a wireless network with n nodes distributed in an area A, and with n source-destination pairs communicating with each other at some common rate, the hierarchical cooperation scheme proposed in (Ozgur, Leveque, and Tse, 2007) is analyzed and optimized by choosing the number of hierarchical stages and the corresponding cluster sizes that maximize the total throughput. It turns out that increasing the number of stages does not necessarily improve the throughput, and the closed-form solutions for the optimization problem can be explicitly obtained. Based on the expression of the maximum achievable throughput, it is found that the hierarchical scheme achieves a scaling with the exponent depending on n. In addition, to apply the hierarchical cooperation scheme to random networks, a clustering algorithm is developed, which divides the whole network into quadrilateral clusters, each with exactly the number of nodes required.