Signal activity detection of phase-shift keying signals

Tadaion, Aliakbar; Derakhtian, Mostafa; Gazor, Saeed; Nayebi, Mohammad Mahdi; Aref, Mohammad Reza

doi:10.1109/tcomm.2006.878830

Cited by 35 publications

(28 citation statements)

References 23 publications

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“…A suboptimal algorithm is also proposed in [35] (involves very small performance loss) with a reduced computational complexity order of |P k | per sub-carrier and hence its overall computational cost is |P|. We provide the data {Y ν } ν∈P k to the procedure in [34] and obtain the ML estimates of the symbols c ν hereafter denoted by c ν .…”

Section: Identification Algorithmmentioning

confidence: 99%

“…The proposed algorithm performs an N-point Fast Fourier Transform (FFT) on M frames, and then detects |P| PSK symbol by the algorithm proposed in [34]. Taking into account the complexity of each term in (20), the overall Computational Complexity (CC) is MN(2 + log 2 N) + k |P k | log 2 |P k | + |P| for M frames using the optimal algorithm in [34] and MN(2 + log 2 N) + 2|P| using the suboptimal algorithm in [35]. For example in [24], authors have considered a case with M = 24, 30 pilots pairs The desired system is active; 8: else if T (Y, P) < η det then 9: The desired system is inactive; 10: end if and N = 2048.…”

Section: Identification Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

GLR test for OFDM system identification using pilot tones pattern

Oularbi

Gazor

Houcke

et al. 2013

J Wireless Com Network

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In the context of cognitive network architecture, an opportunistic cognitive receiver must identify the present active networks. In this article, we propose an efficient algorithm for the identification of OFDM networks exploiting the pilot patterns used in these standards which are prescribed uniquely by their underlying standards. These pilots are inserted for the channel estimation and synchronization between the base stations and their users. The proposed generalized likelihood ratio test (GLRT) not only allows a cognitive observer to detect the active networks by analyzing the observed signals but also performs channel estimation, time-frequency synchronization as well as estimation of the noise variance. These informations are of a great interest for Quality of Service estimation in the purpose of an association with the base station. The proposed solution is applicable to the existing standards (e.g., LTE, WiMAX, WiFi), doesn't require any signaling overhead to be embedded on the pilot tones, is computationally inexpensive and only requires to know the pilot patterns. An other GLRT is proposed as a pre-detector which ignores the pilot information and allows to reduce the computational cost of the system for the cases where a large number of patterns/systems are to be tested.

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Section: Identification Algorithmmentioning

confidence: 99%

Section: Identification Algorithmmentioning

confidence: 99%

GLR test for OFDM system identification using pilot tones pattern

Oularbi

Gazor

Houcke

et al. 2013

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…The signal processing problems represent a significant application of invariant tests in a wide domain of practical detection problems [20,21,[25][26][27][28]. Many properties of invariant tests and their applications have been investigated in statistical literature (see e.g.…”

Section: Introductionmentioning

confidence: 99%

Separating function estimation tests for narrowband signal activity detection using linear array

Ghobadzadeh

Taban

2015

IET Radar, Sonar & Navigation

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This study addresses the narrowband signal detection with unknown frequency, direction of arrival, complex amplitude and noise variance. The authors find a separating function (SF) using the maximal invariant of induced group of transformations. Then three separating function estimation tests (SFETs) are proposed which called SFET 1 , SFET 2 and SFET 3 . It is shown that the SFET 1 using the maximum likelihood estimation (MLE) of SF is equal to the generalised likelihood ratio test. The SFET 2 and SFET 3 are proposed to reduce the computational complexity of SFET 1 , based on a proposed estimation named by averaged MLE. The authors show that the proposed tests are constant false alarm rate. Moreover it is shown that the proposed tests are asymptotically optimal by increasing the number of snapshots and antennas. The simulation results show that the SFET 3 outperforms the SFET 1 and SFET 2 and the decreasing rate of miss detection against the number of snapshots for SFET 3 is higher than that for SFET 1 and SFET 2 .

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“…Signal detection is a critical problem for radar, sonar and wireless communication application [1][2][3][4][5][6][7]. In radar and sonar application, if a target appears, due to environmental uncertainty and Doppler effect, the received data are composed of signal with uncertain amplitude, frequency, phase and direction of angle arrival (DOA) and noise with unknown variance.…”

Section: Introduction and Problem Statementmentioning

confidence: 99%

“…In [2][3][4]6], invariance principle is studied for signal detection with application in communication system. A test is derived that is UMPI if it is given that the signalto-noise-ratio (SNR) is known.…”

Section: Introduction and Problem Statementmentioning

confidence: 99%

Optimal invariant detection of a monochromatic plane wave with five unknown parameters

Cheng

Zhao

et al. 2013

2013 IEEE China Summit and International Conference on Signal and Information Processing

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This paper analyzes the problem of detecting a monochromatic plane wave with unknown amplitude, phase, temporal frequency and direction of arrival (DOA) in complex white Gaussian noise with unknown variance. The uniformly-most-powerful-invariant (UMPI) test is derived by using statistical invariance principle but doesn't exist unless the signal-to-noise ratio (SNR) is known. However, it provides performance bound to evaluate any invariant test's performance when SNR is unknown. Typically, the generalized-likelihood-ratio-test (GLRT) and locally-mostpowerful-invariant (LMPI) test are derived in this paper as realizable suboptimal invariant tests with their performance comparison in different SNR through theoretical analysis. Simulation examples corroborate our analysis and indicate that the GLRT is close to the UMPI bound especially in the low-probability-of-false-alarm region of the receiver operating characteristic (ROC) curve while the performance of LMPI test is close to that of UMPI test in low SNR region.

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Signal activity detection of phase-shift keying signals

Cited by 35 publications

References 23 publications

GLR test for OFDM system identification using pilot tones pattern

GLR test for OFDM system identification using pilot tones pattern

Separating function estimation tests for narrowband signal activity detection using linear array

Optimal invariant detection of a monochromatic plane wave with five unknown parameters

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