Fundamental limits on detection in low SNR under noise uncertainty

By Rahul Tandra, Anant Sahai. 2005 International Conference on Wireless Networks, Communications and Mobile Computing, 2005

674 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/75fcd4390fe0eb977885e5f461ed522c8a8fb1aa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Signal Processing in Cognitive Radio (2009, background): “In [17], bounds on the SNR wall of general detectors based on the 2kth moments have been presented for a slightly more general noise uncertainty model.”
Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks (2008, background): “One of the main drawbacks of energy detection is that it suffers from an SNR wall when noise power uncertainty is present [3], [11], which we did not take into account in previous sections.”
Multiantenna-Assisted Spectrum Sensing for Cognitive Radio (2010, background): “It has been found that the ED is fairly sensitive to the accuracy of the estimated noise variance [20].”
A Review on Spectrum Sensing for Cognitive Radio: Challenges and Solutions (2010, background): “When there is noise uncertainty, it is known that the energy detection is not e ﬀ ective [9–11 To resolve the noise uncertainty problem, we need to estimate the noise power in real time.”
Multi-antenna based spectrum sensing for cognitive radios: A GLRT approach (2010, background): “, 10 log10 α is uniformly distributed in an interval [−B,B] [2], [3].”
Eigenvalue-based spectrum sensing algorithms for cognitive radio (2008, methodology): “When there is noise uncertainty, the energy detection is not an eﬀective method [9, 6, 10, 17] due to the existence of SNR wall and/or high probability of false alarm.”
COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Spectrum Access in the Time Domain: Modeling and Exploiting White Space (2007, background): “Cooperative sensing among secondary users becomes indispensable in those cases [10].”
Advances in cognitive radio networks: A survey (2011, methodology): “Since the detection performance is very sensitive to the noise power estimate error [18], an adaptive noise level estimation approach is proposed in [19], where multiple signal classification algorithm is used to decouple the noise and signal subspaces and estimate the noise floor.”
SNR Walls for Signal Detection (2008, background): “The context is opportunistically sharing spectrum with primary users that must be detected in order to avoid causing harmful interference on a channel.”
A survey of spectrum sensing algorithms for cognitive radio applications (2009, background): “The main advantage of matched filtering is the short time to achieve a certain probability of false alarm or probability of missdetection [92] as compared to other methods that are discussed in this section.”
Maximum-Minimum Eigenvalue Detection for Cognitive Radio (2007, methodology): “There are two types of noise uncertainty: receiver device noise uncertainty and environment noise uncertainty, which are caused by receiving devices or environment, respectively [3, 4, 5].”
Cooperative Sensing among Cognitive Radios (2006, background): “To understan d this better, consider the problem of detecting a signal in additi ve white Gaussian noise (AWGN) with an noise uncertainty α [9].”
Multiple antenna spectrum sensing in cognitive radios (2010, background): “, αdB, in receiver is normally 1-2 dB which due to the existence of interference can be much higher [10], [15].”