Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network

We study two distinct, but overlapping, networks that operate at the same time, space, and frequency. The first network consists of $n$ randomly distributed \emph{primary users}, which form either an ad hoc network, or an infrastructure-supported ad hoc network with $l$ additional base stations. The second network consists of $m$ 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 cognitive users. Base on percolation theory, we show that when the secondary network is denser than the primary network, both networks can simultaneously achieve the same throughput scaling law as a stand-alone network. Furthermore, the primary network throughput is subject to only a vanishingly fractional loss. Specifically, for the ad hoc and the infrastructure-supported primary models, the primary network achieves sum throughputs of order $n^{1/2}$ and $\max\{n^{1/2},l\}$, respectively. For both primary network models, for any $\delta>0$, the secondary network can achieve sum throughput of order $m^{1/2-\delta}$ with an arbitrarily small fraction of outage. Thus, almost all secondary source-destination pairs can communicate at a rate of order $m^{-1/2-\delta}$.Comment: 28 pages, 12 figures, submitted to IEEE Trans. on Information Theor

Scaling Laws of Cognitive Networks

We consider a cognitive network consisting of n random pairs of cognitive transmitters and receivers communicating simultaneously in the presence of multiple primary users. Of interest is how the maximum throughput achieved by the cognitive users scales with n. Furthermore, how far these users must be from a primary user to guarantee a given primary outage. Two scenarios are considered for the network scaling law: (i) when each cognitive transmitter uses constant power to communicate with a cognitive receiver at a bounded distance away, and (ii) when each cognitive transmitter scales its power according to the distance to a considered primary user, allowing the cognitive transmitter-receiver distances to grow. Using single-hop transmission, suitable for cognitive devices of opportunistic nature, we show that, in both scenarios, with path loss larger than 2, the cognitive network throughput scales linearly with the number of cognitive users. We then explore the radius of a primary exclusive region void of cognitive transmitters. We obtain bounds on this radius for a given primary outage constraint. These bounds can help in the design of a primary network with exclusive regions, outside of which cognitive users may transmit freely. Our results show that opportunistic secondary spectrum access using single-hop transmission is promising.Comment: significantly revised and extended, 30 pages, 13 figures, submitted to IEEE Journal of Special Topics in Signal Processin

Multiuser Diversity Gain in Cognitive Networks

Dynamic allocation of resources to the \emph{best} link in large multiuser networks offers considerable improvement in spectral efficiency. This gain, often referred to as \emph{multiuser diversity gain}, can be cast as double-logarithmic growth of the network throughput with the number of users. In this paper we consider large cognitive networks granted concurrent spectrum access with license-holding users. The primary network affords to share its under-utilized spectrum bands with the secondary users. We assess the optimal multiuser diversity gain in the cognitive networks by quantifying how the sum-rate throughput of the network scales with the number of secondary users. For this purpose we look at the optimal pairing of spectrum bands and secondary users, which is supervised by a central entity fully aware of the instantaneous channel conditions, and show that the throughput of the cognitive network scales double-logarithmically with the number of secondary users ($N$) and linearly with the number of available spectrum bands ($M$), i.e., $M\log\log N$. We then propose a \emph{distributed} spectrum allocation scheme, which does not necessitate a central controller or any information exchange between different secondary users and still obeys the optimal throughput scaling law. This scheme requires that \emph{some} secondary transmitter-receiver pairs exchange $\log M$ information bits among themselves. We also show that the aggregate amount of information exchange between secondary transmitter-receiver pairs is {\em asymptotically} equal to $M\log M$. Finally, we show that our distributed scheme guarantees fairness among the secondary users, meaning that they are equally likely to get access to an available spectrum band.Comment: 32 pages, 3 figures, to appear in the IEEE/ACM Transactions on Networkin

Cognitive Radio Networks: Highlights of Information Theoretic Limits, Models and Design

In recent years, the development of intelligent, adaptive wireless devices called cognitive radios, together with the introduction of secondary spectrum licensing, has led to a new paradigm in communications: cognitive networks. Cognitive networks are wireless networks that consist of several types of users: often a primary user (the primary license-holder of a spectrum band) and secondary users (cognitive radios). These cognitive users employ their cognitive abilities to communicate without harming the primary users. The study of cognitive networks is relatively new and many questions are yet to be answered. In this article we highlight some of the recent information theoretic limits, models, and design of these promising networks.Engineering and Applied Science