The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Bandwidth-constrained distributed estimation for wireless sensor Networks-part I: Gaussian case
Abstract
We study deterministic mean-location parameter estimation when only quantized versions of the original observations are available, due to bandwidth constraints. When the dynamic range of the parameter is small or comparable with the noise variance, we introduce a class of maximum-likelihood estimators that require transmitting just one bit per sensor to achieve an estimation variance close to that of the (clairvoyant) sample mean estimator. When the dynamic range is comparable or larger than the noise standard deviation, we show that an optimum quantization step exists to achieve the best possible variance for a given bandwidth constraint. We will also establish that in certain cases the sample mean estimator formed by quantized observations is preferable for complexity reasons. We finally touch upon algorithm implementation issues and guarantee that all the numerical maximizations required by the proposed estimators are concave.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Cited by
Diffusion recursive least-squares for distributed estimation over adaptive networks
Cattivelli, F. S., Lopes, C. G., & Sayed, A. H. (2008) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2007.913164 · Cited by 623
Distributed Kalman filtering based on consensus strategies
Carli, R., Chiuso, A., Schenato, L., & Zampieri, S. (2008) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2008.080505 · Cited by 511
Stochastic Event-Triggered Sensor Schedule for Remote State Estimation
Han, D., Mo, Y., Wu, J., Weerakkody, S., Sinopoli, B., & Shi, L. (2015) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2015.2406975 · Cited by 393
Distributed compression-estimation using wireless sensor networks
Xiao, J.-J., Ribeiro, A., Luo, Z.-Q., & Giannakis, G. B. (2006) · IEEE Signal Processing Magazine · doi:10.1109/msp.2006.1657815 · Cited by 347
Self-citationDistributed Learning in Wireless Sensor Networks
Predd, J. B., Kulkarni, S. R., & Poor, H. V. (2007) · Wireless Sensor Networks · doi:10.1002/9780470061794.ch8 · Cited by 264
Metadata
- Authors
- Ribeiro, A., & Giannakis, G. B.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2006-03
- Volume
- 54
- Issue
- 3
- Pages
- 1131-1143
- ISSN
- 1053-587X (ISSN-L)
- OpenAlex
- W2154828437
- Cited by
- 557
- References
- 1
- FWCI
- 53.84
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Bandwidth-constrained distributed estimation for wireless sensor Networks-part I: Gaussian case. https://app.cochat.ai/papers/10.1109/tsp.2005.863009
- The paper
- Ribeiro, A., & Giannakis, G. B. (2006). Bandwidth-constrained distributed estimation for wireless sensor Networks-part I: Gaussian case. IEEE Transactions on Signal Processing. https://doi.org/10.1109/tsp.2005.863009
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
