Large Overlaid Cognitive Radio Networks: From Throughput Scaling to Asymptotic Multiplexing Gain
Armin Banaei, C.N. Georghiades, Shuguang Robert Cui · IEEE Transactions on Wireless Communications · 2014
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 employing spectrum sensors cannot improve the network performances.