Large Overlaid Cognitive Radio Networks: From Throughput Scaling to Asymptotic Multiplexing Gain

2011/03/04 by Banaei, Armin, Georghiades, Costas N., Cui, Shuguang
#FOS: Computer and information sciences #Networking and Internet Architecture (cs.NI)

paper · doi:10.48550/arxiv.1103.0843

Abstract

We study the asymptotic performance of two multi-hop overlaid ad-hoc networks that utilize the same temporal, spectral, and spatial resources based on random access schemes. The primary network consists of Poisson distributed legacy users with density λ^(p) and the secondary network consists of Poisson distributed cognitive radio users with density λ^(s) = (λ^(p))^β (β>0, β≠ 1) that utilize the spectrum opportunistically. Both networks are decentralized and employ ALOHA medium access protocols where the secondary nodes are additionally equipped with range-limited perfect spectrum sensors to monitor and protect primary transmissions. We study the problem in two distinct regimes, namely β>1 and 01. On the contrary, spectrum sensing turns out to be unnecessary when β<1 and setting the secondary network's ALOHA parameter appropriately can substantially improve primary network performance.

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