Using Higher Order Cyclostationarity to Identify Space-Time Block Codes

DeYoung, M.R.; Heath, Robert W.; Evans, Brian L.

doi:10.1109/glocom.2008.ecp.647

Cited by 25 publications

(15 citation statements)

References 16 publications

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“…The problem of signal classification for multi-antenna (MA) systems remains relatively unexplored. Previously reported investigations [3], [4], [5], [6], [7], [8] all relied on the assumption that the data rate, carrier phase, and frequency offsets, phase noise and Doppler shift were precisely known. Since these conditions are unrealistic in practice, further work is needed to address the important practical problem of signal classification for MA systems affected by transmission impairments.…”

Section: Introductionmentioning

confidence: 99%

Cyclostationarity-based blind classification of STBCs for cognitive radio systems

Marey

Dobre

Inkol

2012

2012 IEEE International Conference on Communications (ICC)

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Signal classification is a major task of a cognitive radio. This paper proposes a novel cyclostationarity-based algorithm for the blind classification of space time block codes (STBCs) and derives analytical expressions for the second-order cyclic statistics used as the basis of the algorithm. Monte Carlo simulation results demonstrate a good classification performance with low sensitivity to phase noise and the channel Doppler shift. The proposed approach avoids the need for a priori knowledge of the channel coefficients, carrier phase, and timing offsets. Moreover, it does not need accurate information about the transmission data rate and carrier frequency offset.Index Terms-Signal intelligence and cognitive radio, signal cyclostationarity, signal classification, multiple antenna systems. I. INTRODUCTIONCognitive radio (CR), as a promising technology for improving the effective utilization of the radio spectrum, has recently attracted much attention [1], [2]. Spectrum awareness is currently one of the most challenging problems in CR design; it is a prerequisite for adaptively responding to changes in the signal environment. Consequently, the detection and classification of signals with relaxed a priori information about the signal parameters is critical for proper CR functionality. The problem of signal classification for multi-antenna (MA) systems remains relatively unexplored. Previously reported investigations [3], [4], [5], [6], [7], [8] all relied on the assumption that the data rate, carrier phase, and frequency offsets, phase noise and Doppler shift were precisely known. Since these conditions are unrealistic in practice, further work is needed to address the important practical problem of signal classification for MA systems affected by transmission impairments. In this paper, we develop and analyze an STBC classification algorithm based on the second-order cyclostationarity observed with two receive antennas, in the presence of transmission impairments. This algorithm does not require information about channel, carrier phase and timing offsets. Moreover, it does not need accurate information about the transmission data rate and carrier frequency offset, and is robust with respect to channel Doppler shift and phase noise.The rest of the paper is organized as follows. Section II presents the signal model and problem formulation. Second-order cyclostationarity of STBCs and the proposed algorithm are introduced in Section III. Simulation results are provided in Section IV. Finally, conclusions are drawn

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Section: Introductionmentioning

confidence: 99%

Cyclostationarity-based blind classification of STBCs for cognitive radio systems

Marey

Dobre

Inkol

2012

2012 IEEE International Conference on Communications (ICC)

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“…Space-time block code (STBC) as a MIMO-based system, its blind identification [1,2,3] becomes an essential part of transmission parameter estimation. STBC identification algorithms can be divided into two categories: the maximum likelihood (ML) [4,5] and the feature based (FB) [6,7]. The former provides the correct recognition probability of the optimal solution, Vincent Choqueuse and MlanieMarazin proposed an algorithm based on second-order statistics (SOS).However, the algorithm needs to know the channel information in advance, such as the noise power and carrier frequency offset.…”

Section: Introductionmentioning

confidence: 99%

Blind Identification of Space-time Block Coding (STBC) Using Single Receive Antenna over Frequency-selective Fading Channels

Lin¹,

Yu²,

Liu³

2017

Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

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Abstract-Blind recognition of STBC is an important issue in the non-cooperative context. However, the research on blind recognition over frequency-selective fading channels has been rarely reported. This paper introduces a novel and efficient algorithm for the frequency-selective fading channels to classify STBC via Kolmogorov-Smirnov (K-S) test when a single antenna is employed at the receiver. The proposed algorithm exploits the discrimination features provided by the empirical cumulative distributions (CDFs) of the received signal. The distance between CDFs is employed relies on the two-sample Kolmogorov-Smirnov test. The algorithm's performance is compared under the condition in different modulation mode, sampling factors and confidence interval. Monte Carlo simulations are conducted to demonstrate the well performance of the proposed algorithms, and the proposed algorithm does not need the estimation of channel, noise statistics and modulation type, and, consequently, is well-suited for non-cooperative communication context.

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“…Second-order statistics are exploited in [12], [13], while fourth-order statistics are considered in [14]. In [15]- [17], signal cyclostationarity-based features are used. Most of these investigations assume perfect timing and frequency synchronization [11]- [16].…”

Section: Introductionmentioning

confidence: 99%

An efficient algorithm for space-time block code classification

Eldemerdash

Dobre

Marey

et al. 2013

2013 IEEE Global Communications Conference (GLOBECOM)

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This paper proposes a novel and efficient algorithm for space-time block code (STBC) classification, when a single antenna is employed at the receiver. The algorithm exploits the discriminating features provided by the discrete Fourier transform (DFT) of the fourth-order lag products (FOLPs) of the received signal. It does not require estimation of the channel, signal-to-noise ratio (SNR), and modulation of the transmitted signal. Computer simulations are conducted to evaluate the performance of the proposed algorithm. The results show the validity of the algorithm, its robustness to carrier frequency offset, and low sensitivity to timing offset.

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Using Higher Order Cyclostationarity to Identify Space-Time Block Codes

Cited by 25 publications

References 16 publications

Cyclostationarity-based blind classification of STBCs for cognitive radio systems

Cyclostationarity-based blind classification of STBCs for cognitive radio systems

Blind Identification of Space-time Block Coding (STBC) Using Single Receive Antenna over Frequency-selective Fading Channels

An efficient algorithm for space-time block code classification

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