Low-Rank Channel and Interference Estimation in mm- Wave Massive Antenna Arrays. Soatti, G., Murtada, A., Nicoli, M., Gambini, J., & Spagnolini, U. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 922-926, Sep., 2018. doi abstract bibtex Millimeter wave (mm-Wave) communications are characterized by wideband channels with few directional paths, mostly in line-of-sight. Antenna arrays are mandatory to cope with severe path-loss, and the resulting channel response is sparse in the space-time (ST) domain. This paper addresses the sparsity by proposing a channel estimation method that exploits the algebraic structure of channel and interference, without requiring complex antenna-array calibration procedures. The method relies on the recognition that the ST channel is low-rank and exhibits slowly and fast-varying features (angles/delays of arrival and fading amplitudes, respectively) and, accordingly, that the interference has a slowly-varying spatial covariance with fast-varying amplitudes. The accuracy of the estimation of quasi-stationary components is increased by introducing averaging mechanisms over multiple sequences. Numerical results show that: i) rank-1 is an effective channel-interference representation in mm- Wave setting with severe interference; ii) fundamental limits (derived in closed form) prove the remarkable performance gains in terms of signal-to interference ratio; iii) circular array arrangement with directive elements is preferable compared to square or triangular configurations.
@InProceedings{8553218,
author = {G. Soatti and A. Murtada and M. Nicoli and J. Gambini and U. Spagnolini},
booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
title = {Low-Rank Channel and Interference Estimation in mm- Wave Massive Antenna Arrays},
year = {2018},
pages = {922-926},
abstract = {Millimeter wave (mm-Wave) communications are characterized by wideband channels with few directional paths, mostly in line-of-sight. Antenna arrays are mandatory to cope with severe path-loss, and the resulting channel response is sparse in the space-time (ST) domain. This paper addresses the sparsity by proposing a channel estimation method that exploits the algebraic structure of channel and interference, without requiring complex antenna-array calibration procedures. The method relies on the recognition that the ST channel is low-rank and exhibits slowly and fast-varying features (angles/delays of arrival and fading amplitudes, respectively) and, accordingly, that the interference has a slowly-varying spatial covariance with fast-varying amplitudes. The accuracy of the estimation of quasi-stationary components is increased by introducing averaging mechanisms over multiple sequences. Numerical results show that: i) rank-1 is an effective channel-interference representation in mm- Wave setting with severe interference; ii) fundamental limits (derived in closed form) prove the remarkable performance gains in terms of signal-to interference ratio; iii) circular array arrangement with directive elements is preferable compared to square or triangular configurations.},
keywords = {calibration;channel estimation;millimetre wave antenna arrays;millimetre wave communication;channel response;channel-interference representation;quasistationary components;fading amplitudes;ST channel;complex antenna-array calibration procedures;algebraic structure;channel estimation method;space-time domain;antenna arrays;directional paths;wideband channels;millimeter wave communications;interference estimation;low-rank channel;Channel estimation;Antenna arrays;Interference;Maximum likelihood estimation;Array signal processing;mm-Wave;space-time channel estimation;subspace methods;antenna array},
doi = {10.23919/EUSIPCO.2018.8553218},
issn = {2076-1465},
month = {Sep.},
}
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Antenna arrays are mandatory to cope with severe path-loss, and the resulting channel response is sparse in the space-time (ST) domain. This paper addresses the sparsity by proposing a channel estimation method that exploits the algebraic structure of channel and interference, without requiring complex antenna-array calibration procedures. The method relies on the recognition that the ST channel is low-rank and exhibits slowly and fast-varying features (angles/delays of arrival and fading amplitudes, respectively) and, accordingly, that the interference has a slowly-varying spatial covariance with fast-varying amplitudes. The accuracy of the estimation of quasi-stationary components is increased by introducing averaging mechanisms over multiple sequences. Numerical results show that: i) rank-1 is an effective channel-interference representation in mm- Wave setting with severe interference; ii) fundamental limits (derived in closed form) prove the remarkable performance gains in terms of signal-to interference ratio; iii) circular array arrangement with directive elements is preferable compared to square or triangular configurations.","keywords":"calibration;channel estimation;millimetre wave antenna arrays;millimetre wave communication;channel response;channel-interference representation;quasistationary components;fading amplitudes;ST channel;complex antenna-array calibration procedures;algebraic structure;channel estimation method;space-time domain;antenna arrays;directional paths;wideband channels;millimeter wave communications;interference estimation;low-rank channel;Channel estimation;Antenna arrays;Interference;Maximum likelihood estimation;Array signal processing;mm-Wave;space-time channel estimation;subspace methods;antenna array","doi":"10.23919/EUSIPCO.2018.8553218","issn":"2076-1465","month":"Sep.","bibtex":"@InProceedings{8553218,\n author = {G. 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The method relies on the recognition that the ST channel is low-rank and exhibits slowly and fast-varying features (angles/delays of arrival and fading amplitudes, respectively) and, accordingly, that the interference has a slowly-varying spatial covariance with fast-varying amplitudes. The accuracy of the estimation of quasi-stationary components is increased by introducing averaging mechanisms over multiple sequences. 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