Resource Allocation in Multiuser Multicarrier Wireless Systems

Many algorithms have already been proposed in the past to solve the problem of allocating resources in a multi-user multicarrier wireless system. Due to the difficulty of the problem, most of the previous work in this area has focused on developing suboptimal heuristics without performance guarantees.
Resource Allocation in Multiuser Multicarrier Wireless Systems proposes a unified algorithmic framework based on dual optimization techniques that have complexities that are linear in the number of subcarriers and users, and that achieve negligible optimality gaps in standards-based numerical simulations. Adaptive algorithms based on stochastic approximation techniques are also proposed, which are shown to achieve similar performance with even much lower complexity.

List of contents

Next Generation Wireless Communication Systems.- Orthogonal Frequency Division Multiple Access.- A New Approach to OFDMA Resource Allocation.- System Model.- Continuous Rate Maximization with perfect CSI and CDI.- Discrete Rate Maximization with perfect CSI and CDI.- Numerical Results.- Partial Channel State Information Model.- Continuous Rate Maximization with Partial CSI and CDI.- Discrete Rate Maximization with Partial CSI and CDI.- Proportional Rate Maximization with Perfect CSI and CDI.- Adaptive Algorithms for Rate Maximization without CDI.- Summary.- Future Work.- Derivations.

Summary

Many algorithms have already been proposed in the past to solve the problem of allocating resources in a multi-user multicarrier wireless system. Due to the difficulty of the problem, most of the previous work in this area has focused on developing suboptimal heuristics without performance guarantees.

Resource Allocation in Multiuser Multicarrier Wireless Systems proposes a unified algorithmic framework based on dual optimization techniques that have complexities that are linear in the number of subcarriers and users, and that achieve negligible optimality gaps in standards-based numerical simulations. Adaptive algorithms based on stochastic approximation techniques are also proposed, which are shown to achieve similar performance with even much lower complexity.

Product details

• Authors: Brian Evans, Ian Wong, Ian C Wong, Ian C. Wong
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 22.10.2010
• EAN: 9781441945228
• ISBN: 978-1-4419-4522-8
• No. of pages: 122
• Dimensions: 15 mm x 1 mm x 23 mm
• Weight: 223 g
• Illustrations: XVIII, 122 p.
• Subjects: Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering; B, Optimization, engineering, Electrical Engineering, complexity, Signal, Image and Speech Processing, Communications Engineering, Networks, Information Systems and Communication Service, Signal Processing, Computers, Mathematical optimization, Speech processing systems, Digital and Analog Signal Processing, Imaging systems & technology, Image processing, Cybernetics & systems theory, Database Management System, Computer networking & communications, Applied Dynamical Systems, Computational complexity