Weighted Sum Rate Maximization In Wireless Networks

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Weighted Sum-Rate Maximization in Wireless Networks

Author: Pradeep Chathuranga Weeraddana
language: en
Publisher: Now Pub
Release Date: 2012-09-04
In Weighted Sum-Rate Maximization in Wireless Networks: A Review, a cohesive discussion of the existing solution methods associated with the WSRMax problem, including global, fast local, as well as decentralized methods, is presented.
Managing Resources for Futuristic Wireless Networks

The key parameter that needs to be considered when planning the management of resources in futuristic wireless networks is a balanced approach to resource distribution. A balanced approach is necessary to provide an unbiased working environment for the distribution, sharing, allocation, and supply of resources among the devices of the wireless network. Equal resource distribution also maintains balance and stability between the operations of communication systems and thus improves the performance of wireless networks. Managing Resources for Futuristic Wireless Networks is a pivotal reference source that presents research related to the control and management of key parameters of bandwidth, spectrum sensing, channel selection, resource sharing, and task scheduling, which is necessary to ensure the efficient operation of wireless networks. Featuring topics that include vehicular ad-hoc networks, resource management, and the internet of things, this publication is ideal for professionals and researchers working in the field of networking, information and knowledge management, and communication sciences. Moreover, the book will provide insights and support executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.
Submodular Rate Region Models for Multicast Communication in Wireless Networks

This book proposes representations of multicast rate regions in wireless networks based on the mathematical concept of submodular functions, e.g., the submodular cut model and the polymatroid broadcast model. These models subsume and generalize the graph and hypergraph models. The submodular structure facilitates a dual decomposition approach to network utility maximization problems, which exploits the greedy algorithm for linear programming on submodular polyhedra. This approach yields computationally efficient characterizations of inner and outer bounds on the multicast capacity regions for various classes of wireless networks.