The DOI matches its Crossref record.
Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization
Open accessAbstract
In the intelligent reflecting surface (IRS)-enhanced wireless communication system, channel state information (CSI) is of paramount importance for achieving the passive beamforming gain of IRS, which, however, is a practically challenging task due to its massive number of passive elements without transmitting/receiving capabilities. In this letter, we propose a practical transmission protocol to execute channel estimation and reflection optimization successively for an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system. Under the unit-modulus constraint, a novel reflection pattern at the IRS is designed to aid the channel estimation at the access point (AP) based on the received pilot signals from the user, for which the channel estimation error is derived in closed-form. With the estimated CSI, the reflection coefficients are then optimized by a low-complexity algorithm based on the resolved strongest signal path in the time domain. Simulation results corroborate the effectiveness of the proposed channel estimation and reflection optimization methods.
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
Cited by
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey
Gong, S., Lu, X., Hoang, D. T., Niyato, D., Shu, L., Kim, D. I., & Liang, Y.-C. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3004197 · Cited by 1,035
Prospective Multiple Antenna Technologies for Beyond 5G
Zhang, J., Bjornson, E., Matthaiou, M., Ng, D. W. K., Yang, H., & Love, D. J. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3000826 · Cited by 877
Zheng, B., You, C., Mei, W., & Zhang, R. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3155305 · Cited by 579
Self-citationPei, X., Yin, H., Tan, L., Cao, L., Li, Z., Wang, K., Zhang, K., & Bjornson, E. (2021) · IEEE Transactions on Communications · doi:10.1109/tcomm.2021.3116151 · Cited by 553
Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computing
Bai, T., Pan, C., Deng, Y., Elkashlan, M., Nallanathan, A., & Hanzo, L. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3007035 · Cited by 528
Metadata
- Authors
- Zheng, B., & Zhang, R.
- Venue
- IEEE Wireless Communications Letters
- Published
- 2020-04
- Volume
- 9
- Issue
- 4
- Pages
- 518-522
- ISSN
- 2162-2337 (ISSN-L)
- 2162-2345
- OpenAlex
- W2971912794
- Cited by
- 876
- References
- 0
- FWCI
- 34.89
- Type
- journal article
- Language
- en
- Open access
- green
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: Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization. https://app.cochat.ai/papers/10.1109/lwc.2019.2961357
- The paper
- Zheng, B., & Zhang, R. (2020). Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization. IEEE Wireless Communications Letters. https://doi.org/10.1109/lwc.2019.2961357
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.