Computer Science – Networking and Internet Architecture
Scientific paper
2011-07-07
Computer Science
Networking and Internet Architecture
12 pages / 7 figures. Submitted to IEEE Transactions on Communication
Scientific paper
We consider the problem of estimating sparse communication channels in the MIMO context. In small to medium bandwidth communications, as in the current standards for OFDM and CDMA communication systems (with bandwidth up to 20 MHz), such channels are individually sparse and at the same time share a common support set. Since the underlying physical channels are inherently continuous-time, we propose a parametric sparse estimation technique based on finite rate of innovation (FRI) principles. Parametric estimation is especially relevant to MIMO communications as it allows for a robust estimation and concise description of the channels. The core of the algorithm is a generalization of conventional spectral estimation methods to multiple input signals with common support. We show the application of our technique for channel estimation in OFDM (uniformly/contiguous DFT pilots) and CDMA downlink (Walsh-Hadamard coded schemes). In the presence of additive white Gaussian noise, theoretical lower bounds on the estimation of SCS channel parameters in Rayleigh fading conditions are derived. Finally, an analytical spatial channel model is derived, and simulations on this model in the OFDM setting show the symbol error rate (SER) is reduced by a factor 2 (0 dB of SNR) to 5 (high SNR) compared to standard non-parametric methods - e.g. lowpass interpolation.
Barbotin Yann
Hormati Ali
Rangan Sundeep
Vetterli Martin
No associations
LandOfFree
Estimation of Sparse MIMO Channels with Common Support does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Estimation of Sparse MIMO Channels with Common Support, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Estimation of Sparse MIMO Channels with Common Support will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-416650