UWB sparse/diffuse channels, Part I: Channel models and Bayesian estimators

Nicolò Michelusi, Urbashi Mitra, Andreas F. Molisch, Michele Zorzi

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


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.

Original languageEnglish (US)
Article number6224193
Pages (from-to)5307-5319
Number of pages13
JournalIEEE Transactions on Signal Processing
Issue number10
StatePublished - 2012
Externally publishedYes


  • Bayesian estimation
  • channel estimation
  • channel modeling
  • sparse approximations
  • ultra wideband

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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