Scaling Laws for Overlaid Wireless Networks: A Cognitive Radio Network vs. a Primary Network

TL;DR

This paper analyzes the scaling laws of throughput and delay in coexisting primary and secondary wireless networks, demonstrating that both can achieve optimal scaling laws similar to standalone networks under certain conditions.

Contribution

It introduces a model for cognitive radio networks with limited information and shows they can attain optimal throughput and delay scaling laws comparable to standalone networks.

Findings

Both networks can achieve the same throughput scaling as standalone networks.

Secondary users can operate with zero outage probability.

Delay-throughput tradeoff matches the optimal for standalone networks.

Abstract

We study the scaling laws for the throughputs and delays of two coexisting wireless networks that operate in the same geographic region. The primary network consists of Poisson distributed legacy users of density n, and the secondary network consists of Poisson distributed cognitive users of density m, with m>n. The primary users have a higher priority to access the spectrum without particular considerations for the secondary users, while the secondary users have to act conservatively in order to limit the interference to the primary users. With a practical assumption that the secondary users only know the locations of the primary transmitters (not the primary receivers), we first show that both networks can achieve the same throughput scaling law as what Gupta and Kumar [1] established for a stand-alone wireless network if proper transmission schemes are deployed, where a certain throughput is achievable for each individual secondary user (i.e., zero outage) with high probability. By using a fluid model, we also show that both networks can achieve the same delay-throughput tradeoff as the optimal one established by El Gamal et al. [2] for a stand-alone wireless network.