Multiuser Diversity Gain in Cognitive Networks
Ali Tajer, Xiaodong Wang

TL;DR
This paper analyzes the multiuser diversity gain in cognitive networks, demonstrating how spectrum sharing and distributed allocation schemes can achieve optimal throughput scaling with multiple secondary users and spectrum bands.
Contribution
It introduces a distributed spectrum allocation scheme that attains the optimal double-logarithmic throughput scaling without centralized control.
Findings
Throughput scales as M log log N with secondary users and spectrum bands.
Distributed scheme requires exchange of approximately M log M bits.
Scheme guarantees fairness among secondary users.
Abstract
Dynamic allocation of resources to the \emph{best} link in large multiuser networks offers considerable improvement in spectral efficiency. This gain, often referred to as \emph{multiuser diversity gain}, can be cast as double-logarithmic growth of the network throughput with the number of users. In this paper we consider large cognitive networks granted concurrent spectrum access with license-holding users. The primary network affords to share its under-utilized spectrum bands with the secondary users. We assess the optimal multiuser diversity gain in the cognitive networks by quantifying how the sum-rate throughput of the network scales with the number of secondary users. For this purpose we look at the optimal pairing of spectrum bands and secondary users, which is supervised by a central entity fully aware of the instantaneous channel conditions, and show that the throughput of the…
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Taxonomy
TopicsCognitive Radio Networks and Spectrum Sensing · Cooperative Communication and Network Coding · Advanced MIMO Systems Optimization
