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

摘要

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)})^beta (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 0 < β 1. On the contrary, spectrum sensing turns out to be unnecessary when β < 1 and employing spectrum sensors cannot improve the network performances.