We consider the problem of distributed detection over a multiaccess channel. Assuming a random number of sensors transmitting their observations using Type Based Multiple Access, we derive the detection performance using Large Deviations Principle as the mean number of sensors goes to infinity. We characterize the performance in terms of error exponents. We provide comparison with the case when the number of sensors is deterministic. We generalize this scheme to multiple collections, propose a Minimum Sum-Rate detector and characterize its error exponents. 1
In this paper, we explore the impact of wireless channel capacity on asymptotic detection performanc...
abstract: Distributed inference has applications in fields as varied as source localization, evaluat...
107 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.Distributed sensor systems wi...
We consider the problem of distributed detection over a multi-access channel. Assuming a random numb...
We study the large deviations performance, i.e., the exponential decay rate of the error probability...
Abstract—The problem of distributed detection in a sensor network over multiaccess fading channels i...
We study, by large deviations analysis, the asymptotic performance of Gaussian running consensus dis...
We study the large deviations performance of consensus+innovations distributed detection over noisy ...
This dissertation studies the performance of the distributed detection systems by means of the large...
Abstract—We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN) for...
We analyze multiuser detection under the assumption that the number of users accessing the channel i...
We consider the problem of distributed detection of a common random signal. After evaluating the det...
This thesis considers the massive random access problem in which a large number of sporadically acti...
We consider a decentralized detection problem in which two sensors collect data from a discrete-time...
Distributed inference has applications in fields as varied as source localization, evaluation of net...
In this paper, we explore the impact of wireless channel capacity on asymptotic detection performanc...
abstract: Distributed inference has applications in fields as varied as source localization, evaluat...
107 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.Distributed sensor systems wi...
We consider the problem of distributed detection over a multi-access channel. Assuming a random numb...
We study the large deviations performance, i.e., the exponential decay rate of the error probability...
Abstract—The problem of distributed detection in a sensor network over multiaccess fading channels i...
We study, by large deviations analysis, the asymptotic performance of Gaussian running consensus dis...
We study the large deviations performance of consensus+innovations distributed detection over noisy ...
This dissertation studies the performance of the distributed detection systems by means of the large...
Abstract—We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN) for...
We analyze multiuser detection under the assumption that the number of users accessing the channel i...
We consider the problem of distributed detection of a common random signal. After evaluating the det...
This thesis considers the massive random access problem in which a large number of sporadically acti...
We consider a decentralized detection problem in which two sensors collect data from a discrete-time...
Distributed inference has applications in fields as varied as source localization, evaluation of net...
In this paper, we explore the impact of wireless channel capacity on asymptotic detection performanc...
abstract: Distributed inference has applications in fields as varied as source localization, evaluat...
107 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.Distributed sensor systems wi...