Abstract—Recently, it has been shown that a simple, distributed CSMA algorithm is throughput-optimal. However, throughput-optimality is established under the perfect or ideal car...
Tae Hyun Kim 0001, Jian Ni, R. Srikant, Nitin H. V...
In many applications decisions must be made about the state of an object based on indirect noisy observation of highdimensional data. An example is the determination of the presen...
Burkay Orten, Prakash Ishwar, W. Clem Karl, Venkat...
Abstract—This paper considers cooperative sensing in cognitive networks under Spectrum Sensing Data Falsification attack (SSDF) in which malicious users can intentionally send f...
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
Compressed sensing is a novel technique where one can recover sparse signals from the undersampled measurements. In this paper, a K × N measurement matrix for compressed sensing ...
In this paper, optimal multi-channel cooperative sensing strategies in cognitive radio networks are investigated. A cognitive radio network with multiple potential channels is cons...
Effective spectrum sensing is a critical prerequisite for multi-channel cognitive radio (CR) networks, where multiple spectrum bands are sensed to identify transmission opportuniti...
Abstract—In cognitive radio networks (CRNs), detecting smallscale primary devices, such as wireless microphones, is a challenging, but very important, problem that has not yet be...
—In this paper, we investigate a selective relay spectrum sensing and best relay data transmission (SRSS-BRDT) scheme for multiple-relay cognitive radio networks. Specifically, ...
— We investigate spectrum sensing by energy detection based on two different objective functions: a Bayesian sensing cost or the network weighted sum capacity. The Bayesian cost ...
Peng Jia, Mai Vu, Tho Le-Ngoc, Seung-Chul Hong, Va...