| 41. |
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| 42. |
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| 43. |
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| 44. |
- Li, J., et al.
(författare)
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Sensor Array and Multichannel Signal Processing
- 2011
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Ingår i: IEEE Signal Processing Magazine. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-0792 .- 1053-5888. ; 28:5, s. 157-158
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Tidskriftsartikel (refereegranskat)abstract
- This article follows the ICASSP 2011 Trends in Sensor Array and Multichannel Signal Processing (SAM SP) expert session and represents our views on continuing and emergingresearch areas in this field.
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| 45. |
- Lioliou, Panagiota, 1982, et al.
(författare)
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Bayesian Approach to Channel Estimation for AF MIMO Relaying Systems
- 2012
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Ingår i: IEEE Journal on Selected Areas in Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0733-8716 .- 1558-0008. ; 30:8, s. 1440-1451
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we investigate the problem of channel estimation in amplify-and-forward multiple-input multiple-output relaying systems operating over random wireless channels. Using the Bayesian framework, novel linear minimum mean square error and expectation-maximization based maximum a posteriori channel estimation algorithms are developed, that provide the destination with full knowledge of all channel parameters involved in the transmission. Moreover, new, explicit expressions for the Bayesian Cramer-Rao bound are deduced for predicting and evaluating the channel estimation accuracy. Our simulation results demo nstrate that the incorporation of prior knowledge into the channel estimation algorithm offers significantly improved performance, especially in the low signal-to-noise ratio regime.
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| 46. |
- Lioliou, Panagiota, 1982, et al.
(författare)
-
Bayesian Channel Estimation Techniques for AF MIMO Relaying Systems
- 2011
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Ingår i: IEEE Vehicular Technology Conference. - 1550-2252. - 9781424483273 ; , s. Art. no. 6093283-
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we consider the fundamental problem of channel estimation in multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems operating over random channels. Using the Bayesian framework, linear minimum mean square error (LMMSE) and expectation-maximization (EM) based maximum a posteriori (MAP) channel estimation algorithms are developed, that provide the destination with full knowledge of all channel parameters involved in the transmission. The performance of the proposed algorithms is evaluated in terms of the mean square error (MSE) as a function of the signal-to-noise ratio (SNR) during the training interval. Our simulation results show that the incorporation of prior knowledge into the channel estimation algorithm offers improved performance, especially in the low SNR regime.
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| 47. |
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| 48. |
- Lioliou, Panagiota, 1982, et al.
(författare)
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Channel Tracking for AF MIMO Relaying Systems
- 2012
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Ingår i: IEEE Vehicular Technology Conference. - 1550-2252. - 9781467322171 ; , s. 1-5
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we consider the problem of channelestimation in multiple-input multiple-output (MIMO) amplifyand-forward (AF) relaying systems operating over time varyingchannels. Only data at the receiving end are assumed availablefor the estimation. By employing a first-order autoregressive(AR) model for characterizing the time-varying nature of thechannels to be estimated, we derive an expectation-maximization(EM) Kalman filter (KF) that utilizes the received signal at thedestination to track the individual channel links. The extendedKF algorithm is also derived and compared to the proposedEM-based KF. Our simulation results show that the proposedEM-based KF offers better estimation performance with lesscomplexity when compared to the EKF algorithm.
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| 49. |
- Lioliou, Panagiota, 1982, et al.
(författare)
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Efficient Channel Estimation Techniques for Amplify and Forward Relaying Systems
- 2012
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Ingår i: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; 60:11, s. 3150-3155
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present a channel estimation scheme for Amplify-and-Forward (AF) relaying systems, using measurements at the destination only. A Least-Squares (LS) based channel estimation algorithm is developed, that provides the destination with full knowledge of all channel responses involved in the transmission. To investigate the algorithm performance, the Cramer-Rao lower bound (CRB) is analytically computed and compared with the asymptotic covariance of the proposed estimator. Since the existing estimator does not reach the CRB, we also propose and analyze an improved algorithm by taking into account the noise characteristics via weighted LS (WLS). The improved algorithm is asymptotically efficient, since it attains the CRB as the SNR tends to infinity.
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| 50. |
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