Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network
Sang-Woon Jeon, Natasha Devroye, Mai Vu, Sae-Young Chung, Vahid Tarokh

TL;DR
This paper demonstrates that cognitive networks can achieve the same throughput scaling as primary networks with minimal loss, using modified routing protocols and percolation theory, even when secondary users are denser.
Contribution
It introduces new multihop routing protocols for cognitive users that preserve primary network throughput and proves simultaneous throughput scaling using percolation theory.
Findings
Both networks achieve the same throughput scaling as standalone networks.
Primary network throughput is only slightly reduced by secondary users.
Secondary users can communicate at nearly optimal rates with minimal outage.
Abstract
We study two distinct, but overlapping, networks that operate at the same time, space, and frequency. The first network consists of randomly distributed \emph{primary users}, which form either an ad hoc network, or an infrastructure-supported ad hoc network with additional base stations. The second network consists of randomly distributed, ad hoc secondary users or cognitive users. The primary users have priority access to the spectrum and do not need to change their communication protocol in the presence of secondary users. The secondary users, however, need to adjust their protocol based on knowledge about the locations of the primary nodes to bring little loss to the primary network's throughput. By introducing preservation regions around primary receivers and avoidance regions around primary base stations, we propose two modified multihop routing protocols for the…
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