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We study the high-power asymptotic behavior of the sum-rate capacity of multi-user interference networks with an equal number of transmitters and receivers. We assume that each transmitter is cognizant of the message it wishes to convey to its corresponding receiver and also of the messages that a subset of the other transmitters wish to send. The receivers are assumed not to be able to cooperate in any way so that they must base their decision on the signal they receive only. We focus on the networks pre-log, which is defined as the limiting ratio of the sum-rate capacity to half the logarithm of the transmitted power. We present both upper and lower bounds on the networks pre-log. The lower bounds are based on a linear partial-cancellation scheme which entails linearly transforming Gaussian codebooks so as to eliminate the interference in a subset of the receivers. Inter alias, the bounds give a complete characterization of the networks and side-information settings that result in a full pre-log, i.e., in a pre-log that is equal to the number of transmitters (and receivers) as well as a complete characterization of networks whose pre-log is equal to the full pre-log minus one. They also fully characterize networks where the full pre-log can only be achieved if each transmitter knows the messages of all users, i.e., when the side-information is full.
We employ Permutation Trellis Code (PTC) based multi-level Frequency Shift Keying signaling to mitigate the impact of Primary Users (PUs) on the performance of Secondary Users (SUs) in Cognitive Radio Networks (CRNs). The PUs are assumed to be dynami
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 sca
A new form of multiuser diversity, named emph{multiuser interference diversity}, is investigated for opportunistic communications in cognitive radio (CR) networks by exploiting the mutual interference between the CR and the existing primary radio (PR
An interference alignment example is constructed for the deterministic channel model of the $K$ user interference channel. The deterministic channel example is then translated into the Gaussian setting, creating the first known example of a fully con
Spectrum sensing is an essential enabling functionality for cognitive radio networks to detect spectrum holes and opportunistically use the under-utilized frequency bands without causing harmful interference to legacy networks. This paper introduces