Is blind channel estimation feasible in mobile communication systems? A study based on GSM

Boss, D.; Kammeyer, Karl‐Dirk; Petermann, T.

doi:10.1109/49.730455

Cited by 50 publications

(17 citation statements)

References 18 publications

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“…In feasibility studies based on the global system for mobile communications (GSM), we have shown that the blind EVI algorithm can even compete with conventional second order methods based on training sequences [2]. It is well-known that cumulants of order three or higher vanish for Gaussian random processes.…”

Section: Introductionmentioning

confidence: 99%

Blind turbo channel estimation in OFDM receivers

Petermann

Vogeler

Kammeyer

et al. 2001

Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256)

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Finite-Alphabet-based blind channel estimation in OFDM systems is known to be extremely complex due to an exhaustive search to be performed over a tremendous number of channel coefficient combinations. In this paper, we present a novel blind channel estimator which dramatically reduces this number of coefficient combinations to be checked without a significant deterioration in estimation quality. Hence, the new low complexity approach enables the application of blind channel estimators based on the finite alphabet set even if the transmitted data are high-rate modulated. Furthermore, we show that the performance of blind channel estimation can be improved by an iterative process based upon the capabilities of channel coding. Using bit error rates, the algorithm is tested with simulations and compared to other blind and nonblind channel estimators.

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Section: Introductionmentioning

confidence: 99%

Blind turbo channel estimation in OFDM receivers

Petermann

Vogeler

Kammeyer

et al. 2001

Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256)

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“…Besides the non-blind LS scheme, we have selected the HOS-based EIGENVECTOR APPROACH TO BLIND IDEN-TIFICATION (EVI) by Boss et al [1] which is a non-linear method maximizing a fourth order cross-cumulant on a second order boundary condition. An investigation of further algorithms based on HOS and SOS can be found in [2,6,7]. A common drawback of all existing blind approaches whether they are based on HOS or SOS is the interference of the estimated channel impulse response by an unknown complex factor.…”

Section: Blind and Non-blind Channel Estimationmentioning

confidence: 99%

“…2 [2]. However, their repeated transmission leaves a GSM system with an overhead capacity of ¾ ½½ ¾¾ ± which can be used for other purposes if the channel is estimated blindly.…”

Section: Blind and Non-blind Channel Estimationmentioning

confidence: 99%

“…The fundamental idea of blind system identification is to derive the complete channel characteristics (including phase information) from the received signal only, i.e. without training 2 While in ´ µ, the index Ø Ì refers to the symbol period Ì ¿ ×, the index used in ´ µ changes from burst to burst only sequences. Fig.…”

Section: Blind and Non-blind Channel Estimationmentioning

confidence: 99%

“…However, their repeated transmission leaves the communication system with a considerable overhead which could be used for the transmission of additional data sequences, if the channel estimation was solved blindly. In recent publications [2,6], we have shown that some blind approaches yield promising results in estimating GSM channels although there is still a significant AE ¼ loss compared to non-blind channel estimation schemes. In order to reduce this loss, we have utilized an iterative channel estimation which employs the bits after channel decoding as a new "training" sequence.…”

Section: Introductionmentioning

confidence: 99%

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Iterative blind and non-blind channel estimation in GSM receivers

Petermann

Kühn²,

Kammeyer

11th IEEE International Symposium on Personal Indoor and Mobile Radio Communications. PIMRC 2000. Proceedings (Cat. No.00TH8525

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Channel estimation plays a leading role in wireless communication systems such as GSM (Global System for Mobile communications). Putting the main emphasis on investigating the application of non-blind and blind channel estimation approaches to the identification of a full I INTRODUCTIONOptimum receivers in digital communication systems require the knowledge of the transmission channel. In general, this knowledge is not available so that the channel's equivalent baseband impulse response has to be estimated. Hence, state-of-the-art mobile communication systems transmit training sequences to assist the receiver in estimating the channel impulse response. However, their repeated transmission leaves the communication system with a considerable overhead which could be used for the transmission of additional data sequences, if the channel estimation was solved blindly. In recent publications [2, 6], we have shown that some blind approaches yield promising results in estimating GSM channels although there is still a significant AE ¼ loss compared to non-blind channel estimation schemes. In order to reduce this loss, we have utilized an iterative channel estimation which employs the bits after channel decoding as a new "training" sequence. Furthermore, the separation of this sequence into different sections enables the use of GSM 1 £ This research is supported by the German NSF (DFG contr. #Ka 841/5-1) 1 By GSM, we understand GSM-900 as well as its derivatives DCS-1800or PCS-1900 for data or speech transmission at very high mobile unit speeds.Since high rate data transmission over mobile radio channels is playing a growing role, we have carried out our simulations for the TCH/F9.6 transmission mode for full rate data at ½¾ kbit/s.The paper is organized as follows: Section II gives an overview of the GSM communication system. Based on the so-called burst structure, we outline in section III the approaches of non-blind and blind channel estimation. In section IV, we describe the concept of iterative channel estimation in a GSM receiver. Finally, simulation results are presented in section V and the paper is concluded in section VI.

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Blind Equalization Techniques

Tugnait¹

2003

Wiley Encyclopedia of Telecommunications

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A tutorial review of various approaches to single‐user blind channel equalization and estimation is presented. Multipath propagation and limited bandwidth are the two main causes of signal distortion in digital communications leading to intersymbol interference at the receiver which, in turn, may lead to high error rates in symbol detection. Traditionally, a training sequence is transmitted during the acquisition mode to enable the receiver to design an equalizer or estimate the channel. In blind channel equalization and estimation no training sequences are available or used. In this article emphasis is on linear time‐invariant channels. The relevant channel models and equalizer structures are reviewed first followed by a discussion of joint channel and symbol estimation methods, direct equalization and symbol estimation approaches without channel estimation, and channel estimation using second‐order and higher‐order statistical methods as well as non‐statistical approaches. Commercial applications of blind equalization are also briefly discussed.

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Is blind channel estimation feasible in mobile communication systems? A study based on GSM

Cited by 50 publications

References 18 publications

Blind turbo channel estimation in OFDM receivers

Blind turbo channel estimation in OFDM receivers

Iterative blind and non-blind channel estimation in GSM receivers

Blind Equalization Techniques

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