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Cross-Layer Resource Allocation in Wireless Communications : Techniques and Models from PHY and MAC Layer Interaction

By: Ana I. Perez-Neira Marc Realp Campalans (Author)

Ksh 12,780.00
Format :

Format(s): DRM PDF DRM EPUB

ISBN-13: 9780080920887

Publisher: Elsevier Science

Imprint: Academic Press

Publication Date: July 28th, 2010

Country of Publication: GB

Language: English

Pages: 192

Physical Edition EAN: 9780123741417

More ebooks on Communications engineering / telecommunications

  • Description

  • Author Bio

Cross-Layer Resource Allocation in Wireless Communications offers practical techniques and models for the design and optimisation of cross-layer resource allocation - one of the hottest topics in wireless communications. Resource allocation in wireless networks is traditionally approached either through information theory or communications networks. To break down the barriers between these distinct approaches, this book bridges the physical and network layers by providing cross-layer resource allocation techniques, models, and methodologies. Its unique approach allows optimisation of network resources and will enable engineers to improve signal quality, enhance network and spectrum utilization, increase throughput, and solve the problem of shadowing. Topics covered include different views of spectral efficiency, the role of spatial diversity, of delay in resource allocation, and possible extensions to OFDMA systems. This will be an ideal reference on cross-layer resource allocation between the PHY and MAC layers for R&D and network design engineers and researchers in universities dealing with sensor networks and cognitive systems. Gives a full description of the characteristics of the PHY layer that promote efficient resource allocation strategies Gives special emphasis on cross-layer design for spatial diversity schemes Provides a framework for interaction between the PHY and MAC layers, their parameters of performance and their relationship Presents resource allocation as a cross-layer design based on an optimization of MAC layer parameters with an accurate model of the PHY layer

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