The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Universal Decentralized Estimation in a Bandwidth Constrained Sensor Network
Abstract
Consider a situation where a set of distributed sensors and a fusion center wish to cooperate to estimate an unknown parameter over a bounded interval [-U,U]. Each sensor collects one noise-corrupted sample, performs a local estimation, and transmits a message to the fusion center, while the latter combines the received messages to produce a final estimate. This correspondence investigates optimal local estimation and final fusion schemes under the constraint that the communication from each sensor to the fusion center must be a one-bit message. Such a binary message constraint is well motivated by the bandwidth limitation of the communication links, fusion center, and by the limited power budget of local sensors. In the absence of bandwidth constraint and assuming the noises are bounded to the interval [-U,U], additive, independent, but otherwise unknown, the classical estimation theory suggests that a total of O(U2/epsi2) sensors are necessary and sufficient in order for the sensors and the fusion center to jointly estimate the unknown parameter within epsi root mean squared error (MSE). It is shown in this correspondence that the same remains true even with the binary message constraint. Furthermore, the optimal decentralized estimation scheme suggests allocating 1/2 of the sensors to estimate the first bit of the unknown parameter, 1/4 of the sensors to estimate the second bit, and so on
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
Noiseless coding of correlated information sources
Slepian, D., & Wolf, J. (1973) · IEEE Transactions on Information Theory · doi:10.1109/tit.1973.1055037 · Cited by 3,952
Detection with Distributed Sensors
Tenney, R., & Sandell, N. (1981) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.1981.309178 · Cited by 846
On the complexity of decentralized decision making and detection problems
Tsitsiklis, J., & Athans, M. (1985) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1985.1103988 · Cited by 427
Speyer, J. (1979) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1979.1101973 · Cited by 386
Combining and updating of local estimates and regional maps along sets of one-dimensional tracks
Willsky, A., Bello, M., Castanon, D., Levy, B., & Verghese, G. (1982) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1982.1103019 · Cited by 243
Distributed estimation and quantization
Gubner, J. A. (1993) · IEEE Transactions on Information Theory · doi:10.1109/18.243470 · Cited by 194
Quantization for decentralized hypothesis testing under communication constraints
Longo, M., Lookabaugh, T. D., & Gray, R. M. (1990) · IEEE Transactions on Information Theory · doi:10.1109/18.52470 · Cited by 179
Design of quantizers for decentralized estimation systems
Lam, W.-M., & Reibman, A. R. (1993) · IEEE Transactions on Communications · doi:10.1109/26.241739 · Cited by 172
Distributed estimation algorithms for nonlinear systems
Castañón, D. A., & Teneketzis, D. (1985) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1985.1103972 · Cited by 123
Joint estimation in sensor networks under energy constraints
Xiao, J., Cui, S. R., Luo, Z.-Q. T., & Goldsmith, A. J. (2005) · IEEE International Conference on Sensing, Communication, and Networking (SECON) · doi:10.1109/sahcn.2004.1381925 · Cited by 68
Self-citation
Cited by
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
Neural Networks Meet Physical Networks: Distributed Inference Between Edge Devices and the Cloud
Chinchali, S. P., Cidon, E., Pergament, E., Chu, T., & Katti, S. (2018) · Proceedings of the 17th ACM Workshop on Hot Topics in Networks · doi:10.1145/3286062.3286070 · Cited by 46
Metadata
- Authors
- Luo, Z.-Q.
- Venue
- IEEE Transactions on Information Theory
- Published
- 2005-06
- Volume
- 51
- Issue
- 6
- Pages
- 2210-2219
- ISSN
- 0018-9448 (ISSN-L)
- OpenAlex
- W2154546286
- Cited by
- 368
- References
- 11
- FWCI
- 44.52
- 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: Universal Decentralized Estimation in a Bandwidth Constrained Sensor Network. https://app.cochat.ai/papers/10.1109/tit.2005.847692
- The paper
- Luo, Z.-Q. (2005). Universal Decentralized Estimation in a Bandwidth Constrained Sensor Network. IEEE Transactions on Information Theory. https://doi.org/10.1109/tit.2005.847692
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.
