Matching theory for future wireless networks: fundamentals and applications


The emergence of novel wireless networking paradigms like tiny cell and cognitive radio networks has forever transformed the way in that wireless systems are operated. In specific, the necessity for self-organizing solutions to manage the scarce spectral resources has become a prevalent theme in many rising wireless systems. In this article, the first comprehensive tutorial on the employment of matching theory, a Nobel Prize winning framework, for resource management in wireless networks is developed. To cater for the distinctive features of rising wireless networks, a novel, wireless-oriented classification of matching theory is proposed. Then the key solution ideas and algorithmic implementations of this framework are exposed. The developed ideas are applied in 3 important wireless networking areas so as to demonstrate the usefulness of this analytical tool. Results show how matching theory will effectively improve the performance of resource allocation in all three applications discussed.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Subspace Rejection for Matching Pursuit in the Presence of Unresolved Targets - 2018ABSTRACT:Unresolved scatterers (separated by but a three-dB matched filter main lobe width) are known to degrade the matching pursuit
PROJECT TITLE :Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching - 2018ABSTRACT:This two-half paper develops novel methodologies for using fractional programming (FP) techniques to design
PROJECT TITLE :Multi-Attributed Graph Matching With Multi-Layer Graph Structure and Multi-Layer Random Walks - 2018ABSTRACT:This Project addresses the multi-attributed graph matching drawback, which considers multiple attributes
PROJECT TITLE :Co-Saliency Detection for RGBD Images Based on Multi-Constraint Feature Matching and Cross Label Propagation - 2018ABSTRACT:Co-saliency detection aims at extracting the common salient regions from an image cluster
PROJECT TITLE :D-FROST: Distributed Frequency Reuse-Based Opportunistic Spectrum Trading via Matching With Evolving Preferences - 2018ABSTRACT:Spectrum trading creates more accessing opportunities for secondary users (SUs), and

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry