The Experts below are selected from a list of 1965 Experts worldwide ranked by ideXlab platform
Mohamed Siala - One of the best experts on this subject based on the ideXlab platform.
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Maximuma posteriori Fast Fading Channel estimation for alamouti’s space-time transmit diversity
Annales Des Télécommunications, 2003Co-Authors: Inès Kammoun, Mohamed SialaAbstract:Cet article considère le schéma de diversité spatio-temporelle à deux antennes à l’émission proposé par Alamouti. Ce schéma effectue une détection au maximum de vraisemblance basée sur un traitement linéaire au niveau du récepteur. Quand le canal n’est pas connu — à l’émetteur et au récepteur — ce schéma suppose une estimation des deux canaux de propagation vus par les deux antennes d’émission. Notre objectif est d’évaluer cette technique de diversité avec une estimation réaliste considérant un canal variant très rapidement dans le temps. Pour une estimation robuste du canal, nous proposons un algorithme, bloc par bloc, d’estimation au maximum a posteriori . Ce dernier effectue une estimation itérative semi-aveugle du canal basée sur l’algorithme EM de maximisation d’espérance. Il nécessite une représentation convenable du canal variable dans le temps en se servant du théorème de développement orthogonal de Karhunen-Loeve. Le récepteur itératif, utilise de manière optimale les symboles pilotes et les symboles inconnus de données pour améliorer la qualité de l’estimation du canal. L’intérêt de l’algorithme utilisé est illustré par des résultats de simulations. De plus, une évaluation de la complexité de cet algorithme avec comparaison est fournie pour différents scénarios. This paper considers the Alamouti’s two-branch transmit diversity scheme. This scheme supports a maximum likelihood detection based on linear processing at the receiver. When no knowledge of the Channel is available — at the transmitter and the receiver- the above scheme requires in general the estimation of the two discrete propagation Channels seen from the two transmit antennas. Our objective is to evaluate the Alamouti’s technique of diversity with a realistic estimation algorithm considering a very Fast time-varying Channel. For a robust Channel estimation, we propose an EM-based maximum a posteriori semi-blind algorithm. This algorithm requires a convenient representation of the time-varying Fading Channel using a discrete version of the Karhunen-Loève expansion theorem. The iterative receiver optimally uses pilot as well as unknown data symbols for improving Channel estimation quality. The validity of the proposed algorithm is highlighted by simulation results. Moreover, a complexity evaluation of this algorithm and a comparison is provided for different scenarii.
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maximum a posteriori Fast Fading Channel estimation for alamouti s space time transmit diversity
Annales Des Télécommunications, 2003Co-Authors: Inbs Kammoun, Mohamed SialaAbstract:This paper considers the Alamouti’s two-branch transmit diversity scheme. This scheme supports a maximum likelihood detection based on linear processing at the receiver. When no knowledge of the Channel is available — at the transmitter and the receiver- the above scheme requires in general the estimation of the two discrete propagation Channels seen from the two transmit antennas. Our objective is to evaluate the Alamouti’s technique of diversity with a realistic estimation algorithm considering a very Fast time-varying Channel. For a robust Channel estimation, we propose an EM-based maximuma posteriori semi-blind algorithm. This algorithm requires a convenient representation of the time-varying Fading Channel using a discrete version of the Karhunen-Loeve expansion theorem. The iterative receiver optimally uses pilot as well as unknown data symbols for improving Channel estimation quality. The validity of the proposed algorithm is highlighted by simulation results. Moreover, a complexity evaluation of this algorithm and a comparison is provided for different scenarii.
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Maximum a posteriori Fast Fading Channel estimation based exclusively on pilot symbols
Annales Des Télécommunications, 2001Co-Authors: Mohamed SialaAbstract:An innovations-based block-by-block maximum a posteriori Fast Fading Channel estimation algorithm, based exclusively on the received samples of pilot symbols, is proposed. This algorithm enables the theoretical determination of the optimum positions of pilot symbols using the raw bit error rate criterion. Moreover, it can be reformulated simply using appropriate weighting of the projections of received pilot symbols samples on an extended orthonormal base. This base can be determined simply as a function of the statistical properties of the Channel.
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Maximum a posteriori Fast Fading Channel estimation based exclusively on pilot symbols
Annales Des Télécommunications, 2001Co-Authors: Mohamed SialaAbstract:On propose un algorithme ďestimation, bloc par bloc, ďun canal avec évanouissements rapides, basé sur ľinnovation et utilisant uniquement les échantillons reçus associés aux symboles pilotes. Cet algorithme permet de déterminer théoriquement les positions optimales des symboles pilotes dans le bloc en s’appuyant sur le critére du taux ďerreur binaire brut. De plus, il peut être reformulé simplement en utilisant une pondération appropriée des projections des échantillons reçus associés aux symboles pilotes sur une base orthonormale etendue. Cette base peut être déterminée simplement à partir des propriétés statistiques du canal. An innovations-based block-by-block maximum a posteriori Fast Fading Channel estimation algorithm, based exclusively on the received samples of pilot symbols, is proposed. This algorithm enables the theoretical determination of the optimum positions of pilot symbols using the raw bit error rate criterion. Moreover, it can be reformulated simply using appropriate weighting of the projections of received pilot symbols samples on an extended orthonormal base. This base can be determined simply as a function of the statistical properties of the Channel.
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semi blind maximum a posteriori Fast Fading Channel estimation for multicarrier systems
17° Colloque sur le traitement du signal et des images 1999 ; p. 215-218, 1999Co-Authors: Mohamed Siala, Emmanuel JaffrotAbstract:We propose in this paper an optimum semi-blind Fast Fading Channel estimation algorithm for multicarrier systems. This algorithm performs an iterative estimation of the multiplicative Channel according to the maximum a posteriori criterion, using the Expectation-Maximization algorithm. It requires a convenient representation of the two-dimensional frequency-time discrete multiplicative Channel seen by all multicarrier transmitted symbols. This representation is guaranteed by the KarhunenLoeve expansion theorem based on the spaced-frequency spaced-time correlation function of the Channel.
Borsen Chen - One of the best experts on this subject based on the ideXlab platform.
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robust Fast time varying multipath Fading Channel estimation and equalization for mimo ofdm systems via a fuzzy method
IEEE Transactions on Vehicular Technology, 2012Co-Authors: Borsen Chen, Changyi Yang, Weiji LiaoAbstract:Channel estimation is an important issue for wireless communication systems. A Channel estimation scheme using a Takagi-Sugeno (T-S) fuzzy-based Kalman filter under the time-varying velocity of the mobile station in a multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system is proposed in this paper. The fuzzy technique is used to interpolate several linear models to approximate the nonlinear estimation system. A MIMO system with the orthogonal space-time block coding (OSTBC) scheme is considered, where the radio Channel is modeled as an autoregressive (AR) random process. The parameters of the AR process and the Channel gain are simultaneously estimated by the proposed method. One-step-ahead prediction can be obtained during this estimation procedure. This is useful for the decision-directed Channel-tracking design, particularly in the Fast-Fading Channel. Furthermore, the robust minimum mean-square error (MMSE) equalization design can be achieved by considering the Channel prediction error to improve the performance of symbol detection. To validate the performance of our proposed method, several simulation results are given and compared with those of other methods. When considering the time-varying velocity of the mobile station communication in the MIMO-OFDM system, the enhanced equalizer based on the T-S fuzzy-based Kalman filter performs better than those based on the conventional Channel estimators in terms of symbol error rate.
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robust mc cdma Channel tracking for Fast time varying multipath Fading Channel
IEEE Transactions on Vehicular Technology, 2010Co-Authors: Changyi Yang, Borsen ChenAbstract:An unscented Kalman filter (UKF)-based Channel-tracking method is proposed for a Fast time-varying multipath Fading Channel in a multicarrier code-division multiple-access (MC-CDMA) system. The mobile radio Channel is modeled as an autoregressive (AR) random process. The parameters of the AR process and the Channel gain are simultaneously estimated by the proposed method. One-step-ahead prediction can also be obtained during Channel estimation. It is useful for the decision-directed Channel-tracking design, particularly in the Fast-Fading Channel. Meanwhile, the estimated parameters can enhance the minimum mean-square error (MMSE) equalizer for symbol detection. The simulation results show that the enhanced equalizer based on the proposed estimation algorithm performs much better than that based on the conventional Channel estimators in symbol error rate.
Chang Wen Chen - One of the best experts on this subject based on the ideXlab platform.
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robust uncoded video transmission over wireless Fast Fading Channel
International Conference on Computer Communications, 2014Co-Authors: Hao Cui, Chong Luo, Chang Wen ChenAbstract:This research studies robust uncoded video transmission over wireless Fast Fading Channel, where only statistical Channel state information (CSI) is available at the sender. We observe that increasing Channel diversity for high priority (HP) data is essential to improving the robustness of video transmission in Fading Channels. By utilizing the noise and loss resilient nature of video, we find it possible to design a more robust system by re-allocating the power and Channel uses among HP and LP (low priority) data. With total power and Channel use constraints, we derive an optimal resource allocation scheme under the squared error distortion criterion. In particular, we first propose a new power allocation algorithm at given Channel allocation. Second, based on the proposed power allocation algorithm, we design a Channel allocation algorithm to strike the tradeoff between the diversity increase of HP data and the information loss of LP data. Third, under known noise power distribution, we derive the optimal resource allocation for uncoded video multicast. Simulations show that the proposed system achieves 2dB and 5dB gain in average and outage PSNR over Softcast in video Unicast, and around 1.4dB and 4dB gain in multicast.
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INFOCOM - Robust uncoded video transmission over wireless Fast Fading Channel
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, 2014Co-Authors: Hao Cui, Chong Luo, Chang Wen ChenAbstract:This research studies robust uncoded video transmission over wireless Fast Fading Channel, where only statistical Channel state information (CSI) is available at the sender. We observe that increasing Channel diversity for high priority (HP) data is essential to improving the robustness of video transmission in Fading Channels. By utilizing the noise and loss resilient nature of video, we find it possible to design a more robust system by re-allocating the power and Channel uses among HP and LP (low priority) data. With total power and Channel use constraints, we derive an optimal resource allocation scheme under the squared error distortion criterion. In particular, we first propose a new power allocation algorithm at given Channel allocation. Second, based on the proposed power allocation algorithm, we design a Channel allocation algorithm to strike the tradeoff between the diversity increase of HP data and the information loss of LP data. Third, under known noise power distribution, we derive the optimal resource allocation for uncoded video multicast. Simulations show that the proposed system achieves 2dB and 5dB gain in average and outage PSNR over Softcast in video Unicast, and around 1.4dB and 4dB gain in multicast.
Changyi Yang - One of the best experts on this subject based on the ideXlab platform.
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robust Fast time varying multipath Fading Channel estimation and equalization for mimo ofdm systems via a fuzzy method
IEEE Transactions on Vehicular Technology, 2012Co-Authors: Borsen Chen, Changyi Yang, Weiji LiaoAbstract:Channel estimation is an important issue for wireless communication systems. A Channel estimation scheme using a Takagi-Sugeno (T-S) fuzzy-based Kalman filter under the time-varying velocity of the mobile station in a multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system is proposed in this paper. The fuzzy technique is used to interpolate several linear models to approximate the nonlinear estimation system. A MIMO system with the orthogonal space-time block coding (OSTBC) scheme is considered, where the radio Channel is modeled as an autoregressive (AR) random process. The parameters of the AR process and the Channel gain are simultaneously estimated by the proposed method. One-step-ahead prediction can be obtained during this estimation procedure. This is useful for the decision-directed Channel-tracking design, particularly in the Fast-Fading Channel. Furthermore, the robust minimum mean-square error (MMSE) equalization design can be achieved by considering the Channel prediction error to improve the performance of symbol detection. To validate the performance of our proposed method, several simulation results are given and compared with those of other methods. When considering the time-varying velocity of the mobile station communication in the MIMO-OFDM system, the enhanced equalizer based on the T-S fuzzy-based Kalman filter performs better than those based on the conventional Channel estimators in terms of symbol error rate.
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robust mc cdma Channel tracking for Fast time varying multipath Fading Channel
IEEE Transactions on Vehicular Technology, 2010Co-Authors: Changyi Yang, Borsen ChenAbstract:An unscented Kalman filter (UKF)-based Channel-tracking method is proposed for a Fast time-varying multipath Fading Channel in a multicarrier code-division multiple-access (MC-CDMA) system. The mobile radio Channel is modeled as an autoregressive (AR) random process. The parameters of the AR process and the Channel gain are simultaneously estimated by the proposed method. One-step-ahead prediction can also be obtained during Channel estimation. It is useful for the decision-directed Channel-tracking design, particularly in the Fast-Fading Channel. Meanwhile, the estimated parameters can enhance the minimum mean-square error (MMSE) equalizer for symbol detection. The simulation results show that the enhanced equalizer based on the proposed estimation algorithm performs much better than that based on the conventional Channel estimators in symbol error rate.
Hao Cui - One of the best experts on this subject based on the ideXlab platform.
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robust uncoded video transmission over wireless Fast Fading Channel
International Conference on Computer Communications, 2014Co-Authors: Hao Cui, Chong Luo, Chang Wen ChenAbstract:This research studies robust uncoded video transmission over wireless Fast Fading Channel, where only statistical Channel state information (CSI) is available at the sender. We observe that increasing Channel diversity for high priority (HP) data is essential to improving the robustness of video transmission in Fading Channels. By utilizing the noise and loss resilient nature of video, we find it possible to design a more robust system by re-allocating the power and Channel uses among HP and LP (low priority) data. With total power and Channel use constraints, we derive an optimal resource allocation scheme under the squared error distortion criterion. In particular, we first propose a new power allocation algorithm at given Channel allocation. Second, based on the proposed power allocation algorithm, we design a Channel allocation algorithm to strike the tradeoff between the diversity increase of HP data and the information loss of LP data. Third, under known noise power distribution, we derive the optimal resource allocation for uncoded video multicast. Simulations show that the proposed system achieves 2dB and 5dB gain in average and outage PSNR over Softcast in video Unicast, and around 1.4dB and 4dB gain in multicast.
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INFOCOM - Robust uncoded video transmission over wireless Fast Fading Channel
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, 2014Co-Authors: Hao Cui, Chong Luo, Chang Wen ChenAbstract:This research studies robust uncoded video transmission over wireless Fast Fading Channel, where only statistical Channel state information (CSI) is available at the sender. We observe that increasing Channel diversity for high priority (HP) data is essential to improving the robustness of video transmission in Fading Channels. By utilizing the noise and loss resilient nature of video, we find it possible to design a more robust system by re-allocating the power and Channel uses among HP and LP (low priority) data. With total power and Channel use constraints, we derive an optimal resource allocation scheme under the squared error distortion criterion. In particular, we first propose a new power allocation algorithm at given Channel allocation. Second, based on the proposed power allocation algorithm, we design a Channel allocation algorithm to strike the tradeoff between the diversity increase of HP data and the information loss of LP data. Third, under known noise power distribution, we derive the optimal resource allocation for uncoded video multicast. Simulations show that the proposed system achieves 2dB and 5dB gain in average and outage PSNR over Softcast in video Unicast, and around 1.4dB and 4dB gain in multicast.