4 edition of Blind equalization with differential detection for channels with ISI and fading found in the catalog.
Blind equalization with differential detection for channels with ISI and fading
by National Library of Canada = Bibliothèque nationale du Canada in Ottawa
Written in English
|Series||Canadian theses = Thèses canadiennes|
|The Physical Object|
In this project, we analyze the performance of channel estimation and adaptive equalization in slow fading channel. The first simulation is AWGN channel. Following the prompt from command line, you will see the three outputs which are the original image, received image, and BER curve. The second simulation is flat fading channel. A Fast and Robust Adaptive Blind Equalization A Fast and Robust Adaptive Blind Equalization Algorithm in High Speed Satellite Channel. PROAKIS J, (SHITZ) S S. Fading Channels: Information-Theoretic and Communications Aspects [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, , Author: Xiao Tian Zheng, Ji Lin Li, Yun Jie Zhang, Mo Lin, Xing Rong Wang, Jian Wang, Xiu Mao, Xin Hua Li.
Equalization of linearly frequency-selective fading channels Article (PDF Available) in IEEE Transactions on Communications 45(12) - January . However, the earlier work,, concerning the proposal for blind equalization based on linear programming was incomplete in several ways. These include the lack of any analysis of the performance of the technique in channels with ISI and additive white Gaussian noise (AWGN), no analysis of performance compared to the CMA algorithm, and the Cited by: 1.
Blind Equalization for Broadband Access using the Constant Modulus Algorithm: /ch The cost of laying optical fiber to the home means that digital transmission using copper twisted pairs is still widely used to provide broadband InternetAuthor: Mark S. Leeson, Eugene Iwu. Blind equalization is a digital signal processing technique in which the transmitted signal is inferred from the received signal, while making use only of the transmitted signal statistics. Hence, the use of the word blind in the name.. Blind equalization is essentially blind deconvolution applied to digital eless, the emphasis in blind equalization is on online estimation.
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Detection. In this thesis, new structures which combine blind equalization with dif- ferential detection are presented. Also, to equalize null and fading channels, decision feedback is added to these new structures. Among the already known noncoherent receiver structures, sever al adapt ive solu- tions are proposed for DQPSK.
Schemes which combine differential detection and blind equalization, to eliminate the need for phase recovery and training sequence, are studied. Decision feedback is also added in an attempt to equalize null and fading : Eloise Tse, Subbarayan Pasupathy. In order to simplify the blind equalization process, researchers have proposed blind sequential detection approaches that avoid explicit estimation of the channel [10, 11].
In [ 10 ], for example, a framework is developed for applying a blind Bayesian maximum likelihood (ML) sequence detector for ISI by: 1. Abstract: A novel equalization/detection algorithm for orthogonal frequency division multiplexing (OFDM) signals transmitted over frequency-selective channels is introduced and investigated.
The algorithm stems from the recognition that the Fourier transform processing inherent in OFDM turns a single wideband frequency-selective channel into a set of correlated narrowband frequency-flat fading by: Abstract: The problem of blind demodulation of multiuser information symbols in a high-rate code-division multiple-access (CDMA) network in the presence of both multiple-access interference (MAI) and intersymbol interference (ISI) is considered.
The dispersive CDMA channel is first cast into a multiple-input multiple-output (MIMO) signal model by: The proposed algorithm is recursive and blind for it requires no training symbols for channel estimation.
However, it assumes knowledge of the variance of the additive noise and the coefficients of the AR process used to model the variation of the fading channel tap by: Equalization methods for ISI channels using neural networks have been dealt with extensively in the literature .
In this paper we consider the case where the input sequence is also unknown, and blind channel equalization is required. Following the blind equalization step, one can apply decisionFile Size: KB. 1 A Comparison of Blind Channel Estimation schemes for OFDM in Fading Channels Chin Keong Ho1, B.
Farhang-Boroujeny1 and Francois Chin2 1Department of Electrical Engineering, National University of Singapore,Singapore Tel: (++65)Fax: (++65)e-mail:fengp, [email protected] Size: KB. A Technique for Combining Equalization with Differential Detection Kenneth Mark Aleong, Department of Electrical Engineering McGill University, Montreal June, A Thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Engineering.
l Equalization compensates for intersymbolinterference (ISI) created by multipathwithin time dispersive channels. An equalizer within a receiver compensates for the average range of expected channel amplitude and delay characteristics. l Equalizers must be adaptive since the channel is generally unknown and time Size: KB.
Blind equalization/detection for OFDM signals over frequency-selective channels Article (PDF Available) in IEEE Journal on Selected Areas in Communications 16(8). Blind equalization and estimation of channel using artificial neural networks Abstract: In this work a new technique is presented for blind channel equalization.
Most of the existing techniques perform channel estimation in first phase and equalization in second phase. The algorithm presented here provides not only the direct blind equalization. This paper introduces a novel blind equalization algorithm for frequency-selective channels based on a Bayesian formulation of the problem and the sequential importance sampling (SIS) technique.
6 Equalization of Channels with ISI Many practical channels are bandlimited and linearly distort the transmit signal. For all equalization schemes derived in the following, it is assumed ISI channel with ES/N0 ratio ES N0 = E2 hFile Size: KB.
A high data rate leads to frequency-selective fading and high mobility gives rise to time-selective fading in communication channels This related works for channel estimation and equalization can be categorized as data-aided schemes [XI and non-data-aided (blind) schemes [ [31, [ Data-aidedCited by: 1.
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract — We consider semi-blind data detectors for OFDM systems over fast fading channels. Three maximum-likelihood (ML) data detectors (MLD) are derived assuming exact channel correlation.
The first two exploit the correlation among pre-DFT and post-DFT received signals and the third one average the ML metric. (CMA) for blind equalization of the channels are shown , .
Finally, a comparison of the simulation results of LMS and CMA for the test channels is provided. Index Terms— Blind Channel Equalization, LMS algorithm, Constant Modulus Algorithm Many algorithms have been proposed during the past few I.
INTRODUCTIONAuthor: Sanaz Moshirian, Soheil Ghadami, Mohammad Havaei. Blind Equalization Christoph Krall Graz University of Technology Christian Doppler Laboratory for Nonlinear Signal Processing Inffeldga A Graz, Austria @ Abstract—Equalization is a very essential topic in data communication.
Due to the communication channel. Abstract: A novel blind channel identification and equalization method is proposed by exploiting the cyclostationarity of communication signals. Identification and equalization of possibly nonminimum phase multipath channels are achieved without using training signals.
Unlike most of the adaptive blind equalization methods for which the convergence properties are often problematic, the. The suboptimal approaches in Section 5 may be employed to reduce the complexity of the EKF-based blind MAPSD algorithm. Thus, for the fading channel model with timing uncertainity in Eq.
(92), lower complexity dualmode algorithms can be addition to metric pruning (as discussed in Section ), pseudo-Kalman matrix updating and memory truncation using decision feedback may be used to. We consider semi-blind data detectors for OFDM systems over fast fading channels.
Three maximum-likelihood (ML) data detectors (MLD) are derived assuming exact channel correlation.A high speed data communication over a bandlimited chan- l is subject to ISI, whereby adjacent symbols on the output of e channel smear and overlap each other causing degradationnt where full bandwidth utilization of the channel is required.
nventional equalization techniques are very well known which ch wcessing 22 () â€“ Cited by: 9.Blind Equalization and Identification (Signal Processing and Communications) 1st Edition by Zhi Ding (Author), Ye Li (Author) out of 5 stars 1 rating. ISBN ISBN Why is ISBN important? ISBN. This bar-code number lets you verify that you're getting exactly the right version or edition of a book.