| 51. |
- Lioliou, Panagiota, 1982, et al.
(author)
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Performance Analysis of Relay Channel Estimation
- 2009
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In: 43rd Asilomar Conference on Signals, Systems and Computers; Pacific Grove, CA; United States; 1 November 2009 through 4 November 2009. - 1058-6393. - 9781424458271 ; , s. 1533-1537
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Conference paper (peer-reviewed)abstract
- Amplify-and-Forward (AF) relays can be used to enhance the channel in Multiple-Input-Multiple-Output (MIMO) wireless communication systems. However, optimizing the channel requires Channel State Information (CSI). This paper is concerned with the performance of relay channel estimation. A Least Squares (LS) based algorithm for the estimation of all relevant channel parameters was recently proposed by the authors. It is based on creating different compound channels by varying the gain factors at the relays. From this, the individual links from source to relay and from relay to destination, are revealed using LS. To investigate the algorithm performance, the Cramér-Rao lower Bound (CRB) is computed and compared with the asymptotic covariance of the proposed estimator. Furthermore, we propose and analyze an improved algorithm that is efficient for high Signal-to-Noise Ratio (SNR). Computer simulations demonstrate the performance of the algorithm. The results indicate that the asymptotic expressions are in good agreement with the simulations.
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| 52. |
- Lioliou, Panagiota, 1982, et al.
(author)
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Self-Interference Suppression in Full-Duplex MIMO Relays
- 2010
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In: 44th Asilomar Conference on Signals, Systems and Computers. - 1058-6393. - 9781424497218 ; , s. 658-662
-
Conference paper (peer-reviewed)abstract
- Full-duplex relays can provide cost-effective cover-age extension and throughput enhancement. However, the main limiting factor is the resulting self-interference signal which deteriorates the relay performance. In this paper, we propose a novel technique for self-interference suppression in full-duplex Multiple-Input Multiple-Output (MIMO) relays. The relay employs transmit and receive weight filters for suppressing the self-interference signal. Unlike existing techniques that are based on zero forcing of self-interference, we aim at maximizing the ratio between the power of the useful signal to the self-interference power at the relay reception and transmission. Our simulation results show that the proposed algorithm outperforms the existing schemes since it can suppress interference substantially with less impact on the useful signal.
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| 53. |
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| 54. |
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| 55. |
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| 56. |
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| 57. |
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| 58. |
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| 59. |
- Mecklenbräuker, Christoph F., et al.
(author)
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Eigenbeam transmission over line-of-sight MIMO channels for fixed microwave links
- 2011
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In: Proceedings - ITG/IEEE Workshop on Smart Antennas (WSA). - 9781612840741
-
Conference paper (peer-reviewed)abstract
- We propose and analyze eigenbeam transmission over line-of-sight (LOS) multiple-input multiple-output (MIMO) channels with linear reception. In particular, we consider fixed point-to-point microwave links for which the singular value decomposition of the LOS MIMO channel matrix is analytically derived. We demonstrate that the Tx eigenbeams can be defined without channel state information at the transmitter and that the beams admit an insightful physical interpretation. We also evaluate the performance of a lattice-reduction aided linear receiver through numerical simulations.
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| 60. |
- Mecklenbräuker, Christoph F., et al.
(author)
-
Sequential Bayesian Sparse Signal Reconstruction Using Array Data
- 2013
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In: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1941-0476 .- 1053-587X. ; 61:24, s. 6344-6354
-
Journal article (peer-reviewed)abstract
- In this paper, the sequential reconstruction of source waveforms under a sparsity constraint is considered from a Bayesian perspective. Let the wave field, which is observed by a sensor array, be caused by a spatially-sparse set of sources. A spatially weighted Laplace-like prior is assumed for the source field and the corresponding weighted Least Absolute Shrinkage and Selection Operator (LASSO) cost function is derived. After the weighted LASSO solution has been calculated as the maximum a posteriori estimate at time step, the posterior distribution of the source amplitudes is analytically approximated. The weighting of the Laplace-like prior for time step is then fitted to the approximated posterior distribution. This results in a sequential update for the LASSO weights. Thus, a sequence of weighted LASSO problems is solved for estimating the temporal evolution of a sparse source field. The method is evaluated numerically using a uniform linear array in simulations and applied to data which were acquired from a towed horizontal array during the long range acoustic communications experiment.
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