The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
5G Enabled Codesign of Energy-Efficient Transmission and Estimation for Industrial IoT Systems
Abstract
In industrial automation, the state of process control could be monitored by spatially distributed sensors and 5G machine-type communication (MTC) enabled industrial Internet of things (IIoT). Thus, ultra-reliable MTC and high-accurate state estimation play important roles for ensuing system stabilization. However, it is challenging due to complex industrial wireless environments and limited communication resources. To address this issue, this paper first presents a transmission-estimation codesign framework to lay down the foundation for guaranteeing the prescribed estimation accuracy with limited communication resources. Under this framework, a hierarchical transmission-estimation approach is proposed to improve the transmission reliability and estimation accuracy according to system dynamics. The proposed approach is then optimized by formulating a constrained minimization problem, which is mixed integer nonlinear programming and solved efficiently with a block-coordinate-descent-based decomposition method. Finally, simulation results demonstrate that the proposed approach has superiorities in improving both the estimation accuracy and the energy efficiency.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“According to the Cisco, up to 500 billion devices are expected to be connected to the IoT by 2030 (Egham, 2017;Lyu et al., 2018;CISCO, 2016).”
From Future Industry Internet of Things with Zero-trust Security (2024) · cites this paper as Lyu et al., 2018
Citations
Cites
(2007) · doi:10.5555/1283383.1283494 · Cited by 7,364
Stability and Stabilizability of Switched Linear Systems: A Survey of Recent Results
Lin, H., & Antsaklis, P. J. (2009) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.2012009 · Cited by 2,698
A survey on clustering algorithms for wireless sensor networks
Abbasi, A. A., & Younis, M. (2007) · Computer Communications · doi:10.1016/j.comcom.2007.05.024 · Cited by 2,398
Multi-sensor optimal information fusion Kalman filter
Sun, S., & Deng, Z. (2004) · Automatica · doi:10.1016/j.automatica.2004.01.014 · Cited by 834
Machine-type communications: current status and future perspectives toward 5G systems
Shariatmadari, H., Ratasuk, R., Iraji, S., Laya, A., Taleb, T., Jäntti, R., & Ghosh, A. (2015) · IEEE Communications Magazine · doi:10.1109/mcom.2015.7263367 · Cited by 431
The industrial indoor channel: large-scale and temporal fading at 900, 2400, and 5200 MHz
Tanghe, E., Joseph, W., Verloock, L., et al. (2008) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2008.070143 · Cited by 340
Qin, J., Fu, W., Gao, H., & Zheng, W. X. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2016.2526683 · Cited by 334
A Reconfigurable Smart Sensor Interface for Industrial WSN in IoT Environment
Chi, Q., Yan, H., Zhang, C., Pang, Z., & Xu, L. D. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2306798 · Cited by 316
A Measurement-Based Statistical Model for Industrial Ultra-Wideband Channels
Kåredal, J., Wyne, S., Almers, P., et al. (2007) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2007.051050 · Cited by 217
Wireless Communication for Factory Automation: an opportunity for LTE and 5G systems
Holfeld, B., Wieruch, D., Wirth, T., et al. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7497764 · Cited by 193
Packet Size Optimization in Wireless Sensor Networks for Smart Grid Applications
Kurt, S., Yıldız, H. U., Yiğit, M., et al. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2619319 · Cited by 185
Distributed Optimal Consensus Filter for Target Tracking in Heterogeneous Sensor Networks
Zhu, S., Chen, C., Li, W., Yang, B., & Guan, X. (2013) · IEEE Transactions on Cybernetics · doi:10.1109/tsmcb.2012.2236647 · Cited by 184
Self-citationComparative Examination on Architecture and Protocol of Industrial Wireless Sensor Network Standards
Wang, Q., & Jiang, J. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2548360 · Cited by 182
He, X. H., Wang, Z., Liu, Y., et al. (2013) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2013.2251891 · Cited by 157
Chen, C., Yan, J. J., Lü, N., et al. (2015) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2014.2386615 · Cited by 145
Self-citationCao, X., Cheng, P., Chen, J., et al. (2012) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2012.2216537 · Cited by 131
On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA Systems
Liu, Y., & Dai, Y. (2014) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2013.2293130 · Cited by 124
Large-Scale Convex Optimization for Dense Wireless Cooperative Networks
Shi, Y., Zhang, J., O'Donoghue, B., & Letaief, K. B. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2443731 · Cited by 118
Multisensor Fusion and Integration: A Review on Approaches and Its Applications in Mechatronics
Luo, R. C., & Chang, C.-C. B. (2011) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2011.2173942 · Cited by 118
Device-to-Device Communications for 5G Internet of Things
Militano, L., Araniti, G., Condoluci, M., Farris, I., & Iera, A. (2015) · EAI Endorsed Transactions on Internet of Things · doi:10.4108/eai.26-10-2015.150598 · Cited by 106
Chen, B., Hu, G., Ho, D. W. C., et al. (2016) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2016.2539221 · Cited by 102
Ma, J., & Sun, S. (2016) · Signal Processing · doi:10.1016/j.sigpro.2016.07.004 · Cited by 93
State Estimation Over a Lossy Network in Spatially Distributed Cyber-Physical Systems
Deshmukh, S., Natarajan, B., & Pahwa, A. (2014) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2014.2330810 · Cited by 75
Hromic, H., Le-Phuoc, D., Serrano, M., Antonić, A., Žarko, I. P., Hayes, C., & Decker, S. (2015) · International Conference on Communications · doi:10.1109/icc.2015.7248401 · Cited by 74
Optimal Periodic Transmission Power Schedules for Remote Estimation of ARMA Processes
Li, Y., Quevedo, D. E., Lau, V. K. N., et al. (2013) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2013.2283838 · Cited by 72
Zhu, R., Zhang, X. J., Liu, X., Shu, W., Mao, T., & Jalaian, B. A. (2015) · IEEE Access · doi:10.1109/access.2015.2501644 · Cited by 72
Caballero‐Águila, R., García-Garrido, I., & Linares‐Pérez, J. (2013) · Applied Mathematics and Computation · doi:10.1016/j.amc.2013.10.068 · Cited by 71
Efficient small data access for machine-type communications in LTE
Andreev, S. D., Larmo, A., Gerasimenko, M., et al. (2013) · International Conference on Communications · doi:10.1109/icc.2013.6655105 · Cited by 67
Hierarchical Fusion Estimation for Clustered Asynchronous Sensor Networks
Zhang, W., Chen, B., & Chen, M. Z. Q. (2015) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2015.2498701 · Cited by 65
Industrial Wireless Networks: The Significance of Timeliness in Communication Systems
Vitturi, S., Tramarin, F., & Seno, L. (2013) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2013.2253837 · Cited by 63
Xu, J., Zhong, Z. D., & Ai, B. (2016) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2016.2558503 · Cited by 39
UWB Channel Measurements and Results for Office and Industrial Environments
Irahhauten, Z., Janssen, G. J. M., Nikookar, H., et al. (2006) · IEEE International Conference on Ultra-Wideband (ICUWB) · doi:10.1109/icu.2006.281554 · Cited by 38
Lyu, L., Chen, C., Yan, J. J., et al. (2016) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2016.2573719 · Cited by 34
Self-citationCo‐design of stabilisation and transmission scheduling for wireless control systems
Lyu, L., Chen, C., Hua, C., et al. (2017) · IET Control Theory and Applications · doi:10.1049/iet-cta.2016.0871 · Cited by 28
Self-citationHierarchical Fusion in Clustered Sensor Networks with Asynchronous Local Estimates
Song, H., Zhang, W., & Yu, L. J. (2014) · IEEE Signal Processing Letters · doi:10.1109/lsp.2014.2341637 · Cited by 27
State-based communication design for wireless control systems
Gatsis, K., Ribeiro, A., & Pappas, G. J. (2016) · Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes · doi:10.1109/cdc.2016.7798258 · Cited by 27
Zhu, S., Soh, Y. C., & Xie, L. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2489606 · Cited by 13
Self-citationFusion of state estimates over long-haul sensor networks under random delay and loss
Liu, Q., Wang, X., & Rao, N. S. V. (2012) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infcom.2012.6195679 · Cited by 6
Research works printed but not linked: 1
- molisch, 2004, IEEE 802.15. 4a channel model—Final report, IEEE
Cited by
Sorted by citations
A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective
Xu, H., Yu, W., Griffith, D., & Golmie, N. (2018) · IEEE Access · doi:10.1109/access.2018.2884906 · Cited by 637
Future Industry Internet of Things with Zero-trust Security
Li, S., Iqbal, M., & Saxena, N. (2024) · Information Systems Frontiers · doi:10.1007/s10796-021-10199-5 · Cited by 128
Metadata
- Authors
- Lyu, L., Chen, C., Zhu, S., & Guan, X.
- Affiliations
- Shanghai Jiao Tong University (CN)
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2018-06
- Volume
- 14
- Issue
- 6
- Pages
- 2690-2704
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2789250945
- Cited by
- 112
- References
- 38
- Citations by year
- 2026: 1 · 2025: 10 · 2024: 6 · 2023: 15 · 2022: 13 · 2021: 10 · 2020: 26 · 2019: 20 · 2018: 11
- FWCI
- 10.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Industrial Informatics (publishedVersion)
- Funders
- NSF of China (61521063, 61622307, 61633017, U1405251, 61371085, 61603251, U1509211)
- National High Technology Research and Development Program of China (863 Program) (2015AA01A702)
- China Scholarship Council
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
- Physical Sciences › Computer Science › Computer Networks and Communications › Age of Information Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT Networks and Protocols
- Keywords
- Industrial Internet of Things, energy efficiency, state estimation, ultra-reliable communication, mixed-integer nonlinear programming, distributed sensors, industrial wireless networks
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
