TY - JOUR
T1 - UWB sparse/diffuse channels, Part I
T2 - Channel models and Bayesian estimators
AU - Michelusi, Nicolò
AU - Mitra, Urbashi
AU - Molisch, Andreas F.
AU - Zorzi, Michele
N1 - Funding Information:
Manuscript received September 12, 2011; revised March 12, 2012; accepted June 07, 2012. Date of publication June 22, 2012; date of current version September 11, 2012. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Xavier Mestre. This work was supported in part by the following grants and organizations: ONR N00014-09-1-0700, NSF CNS-0832186, NSF CNS-0821750 (MRI), Aldo Gini Foundation (Padova, Italy).
PY - 2012
Y1 - 2012
N2 - In this two-part paper, the problem of channel estimation in Ultra Wide-Band (UWB) systems is investigated. Due to the large transmission bandwidth, the channel has been traditionally modeled as sparse. However, some propagation phenomena, e.g., scattering from rough surfaces and frequency distortion, are better modeled by a diffuse channel. Herein, a novel Hybrid Sparse/Diffuse (HSD) channel model is proposed. Tailored to the HSD model, channel estimators are designed for different scenarios that vary in the amount of side information available at the receiver. An Expectation-Maximization algorithm to estimate the power delay profile of the diffuse component is also designed. The proposed methods are compared to unstructured and purely sparse estimators. The numerical results show that the HSD estimation schemes considerably improve the estimation accuracy and the bit error rate performance over conventional channel estimators. In Part II, the new channel estimators are evaluated with more realistic geometry-based channel emulators. The numerical results show that, even when the channel is generated in this manner, the new estimation strategies achieve high performance. Moreover, a Mean-Squared Error analysis of the proposed estimators is performed, in the high and low Signal to Noise Ratio regimes, thus quantifying, in closed form, the achievable performance gains.
AB - In this two-part paper, the problem of channel estimation in Ultra Wide-Band (UWB) systems is investigated. Due to the large transmission bandwidth, the channel has been traditionally modeled as sparse. However, some propagation phenomena, e.g., scattering from rough surfaces and frequency distortion, are better modeled by a diffuse channel. Herein, a novel Hybrid Sparse/Diffuse (HSD) channel model is proposed. Tailored to the HSD model, channel estimators are designed for different scenarios that vary in the amount of side information available at the receiver. An Expectation-Maximization algorithm to estimate the power delay profile of the diffuse component is also designed. The proposed methods are compared to unstructured and purely sparse estimators. The numerical results show that the HSD estimation schemes considerably improve the estimation accuracy and the bit error rate performance over conventional channel estimators. In Part II, the new channel estimators are evaluated with more realistic geometry-based channel emulators. The numerical results show that, even when the channel is generated in this manner, the new estimation strategies achieve high performance. Moreover, a Mean-Squared Error analysis of the proposed estimators is performed, in the high and low Signal to Noise Ratio regimes, thus quantifying, in closed form, the achievable performance gains.
KW - Bayesian estimation
KW - channel estimation
KW - channel modeling
KW - sparse approximations
KW - ultra wideband
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U2 - 10.1109/TSP.2012.2205681
DO - 10.1109/TSP.2012.2205681
M3 - Article
AN - SCOPUS:84866515579
SN - 1053-587X
VL - 60
SP - 5307
EP - 5319
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 10
M1 - 6224193
ER -