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In this two-part paper, the problem of channel estimation in Ultra Wide-Band (UWB) systems is investigated. In Part I, a novel Hybrid Sparse/Diffuse (HSD) model is proposed for the UWB channel, and new channel estimation strategies are designed for this model. In this paper (Part II), a Mean-Squared Error (MSE) analysis of the Generalized MMSE and Generalized Thresholding Estimators developed in Part I is performed, for the asymptotic regimes of low and high SNR. The analysis quantifies the achievable MSE performance of these schemes over unstructured estimators. Specifically, we prove that it is beneficial to be conservative in the estimation of the sparse component, i.e., to assume that the sparse component is sparser than it actually is. Moreover, we analyze the scenario with a non-orthogonal pilot sequence, and establish a connection between the Generalized Thresholding estimator and conventional sparse approximation algorithms proposed in the literature. In addition to the theoretical analysis, these channel estimation schemes are evaluated in a more realistic geometry-based channel emulator, for which the HSD model developed in Part I is an approximation. The numerical results are shown to match the expected asymptotic MSE behavior. Moreover, the proposed estimation techniques are shown to outperform conventional unstructured and purely sparse estimators, from both an MSE and a bit error rate perspectives, even for the realistic geometry-based channel model. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]