Asymptotic Performance of ALOHA-Based Cognitive Overlaid Networks
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abstract
We study the asymptotic performance of two over-laid wireless 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 n and the secondary network consists of Poisson distributed cognitive radio users with density m = n (> 1) that utilize the spectrum opportunistically. Both networks are decentralized and deploy ALOHA protocols where the secondary users are equipped with range-limited perfect spectrum sensors to monitor and protect primary transmissions. First, we show that both networks can achieve their corresponding stand-alone throughput scaling even without secondary spectrum sensing (i.e., sensing range set to zero), which implies the need for a more comprehensive performance metric than just throughput scaling to evaluate the influence of the overlaid interactions. We thus introduce a new criterion, termed as the asymptotic multiplexing gain, which captures the effect of spectrum sensing and internetwork interferences. 2010 IEEE.
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2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)