Name
Title | ||
|---|---|---|
Compressed sensing maximum likelihood channel estimation for ultra-wideband impulse radio |
Abstract | ||
|---|---|---|
One of the most attractive features of ultra-wideband impulse radio is the collection of rich multipath with the transmission of ultra-short pulses. Exploiting the rich multi-path diversity with channel estimating Rake receivers enables significant energy capture, higher performance and flexibility than suboptimal receivers. Although data-aided (DA) maximum likelihood (ML) channel estimator shows a promising performance, its implementation is restricted by the Nyquist sampling criterion. The emerging theory of compressed sensing (CS) describes a novel framework to jointly compress and detect a sparse signal with fewer samples than the traditional Nyquist criterion. In this paper, we propose a CS-ML channel estimator which combines the compression framework of CS for sampling rate reduction while retaining the noise statistics formulation of ML to achieve a reliable performance. Simulation assessment indicates that, with far fewer measurements, the performance of our proposed scheme supersedes that of the l1-norm minimization estimator of CS and can be as close as the ML, but with a reduction in complexity. |
Year | Venue | Keywords |
|---|---|---|
2009 | ICC | cs-ml channel estimator,maximum likelihood channel estimation,channel estimator,nyquist sampling criterion,promising performance,ultra-wideband impulse radio,higher performance,fewer measurement,fewer sample,reliable performance,compression framework,l1-norm minimization estimator,compressed sensing,signal to noise ratio,fading,bit error rate,complexity reduction,rake receiver,ultra wideband,maximum likelihood estimation,radio receivers,sampling methods,nyquist criterion,maximum likelihood |
Field | DocType | ISSN |
Multipath propagation,Rake,Computer science,Signal-to-noise ratio,Sampling (signal processing),Communication channel,Algorithm,Real-time computing,Nyquist stability criterion,Statistics,Compressed sensing,Estimator | Conference | 1550-3607 |
Citations | PageRank | References |
5 | 0.48 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ted C.-K. Liu | 1 | 82 | 4.42 |
| Xiaodai Dong | 2 | 958 | 85.45 |
| Wu-Sheng Lu | 3 | 296 | 24.90 |