The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Content-Centric Sparse Multicast Beamforming for Cache-Enabled Cloud RAN
Open accessAbstract
This paper presents a content-centric transmission design in a cloud radio access network by incorporating multicasting and caching. Users requesting the same content form a multicast group and are served by a same cluster of base stations (BSs) cooperatively. Each BS has a local cache, and it acquires the requested contents either from its local cache or from the central processor via backhaul links. We investigate the dynamic content-centric BS clustering and multicast beamforming with respect to both channel condition and caching status. We first formulate a mixed-integer nonlinear programming problem of minimizing the weighted sum of backhaul cost and transmit power under the quality-of-service constraint for each multicast group. Theoretical analysis reveals that all the BSs caching a requested content can be included in the BS cluster of this content, regardless of the channel conditions. Then, we reformulate an equivalent sparse multicast beamforming (SBF) problem. By adopting smoothed ℓ0-norm approximation and other techniques, the SBF problem is transformed into the difference of convex programs and effectively solved using the convex-concave procedure algorithms. Simulation results demonstrate significant advantage of the proposed content-centric transmission. The effects of heuristic caching strategies are also evaluated.
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
Enhancing Sparsity by Reweighted ℓ 1 Minimization
Candès, E. J., Wakin, M. B., & Boyd, S. P. (2008) · Journal of Fourier Analysis and Applications · doi:10.1007/s00041-008-9045-x · Cited by 4,863
Web caching and Zipf-like distributions: evidence and implications
Breslau, L., Cao, P., Fan, L., Phillips, G., & Shenker, S. (1999) · IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320) · doi:10.1109/infcom.1999.749260 · Cited by 3,467
Multi-Cell MIMO Cooperative Networks: A New Look at Interference
Gesbert, D., Hanly, S., Huang, H., Shamai Shitz, S., Simeone, O., & Yu, W. (2010) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2010.101202 · Cited by 1,760
Self-citationTransmit beamforming for physical-layer multicasting
Sidiropoulos, N. D., Davidson, T. N., & Luo, Z.-Q. (2006) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2006.872578 · Cited by 1,335
FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers
Shanmugam, K., Golrezaei, N., Dimakis, A. G., Molisch, A. F., & Caire, G. (2013) · IEEE Transactions on Information Theory · doi:10.1109/tit.2013.2281606 · Cited by 1,246
Yuille, A. L., & Rangarajan, A. (2003) · Neural Computation · doi:10.1162/08997660360581958 · Cited by 1,151
Living on the edge: The role of proactive caching in 5G wireless networks
Bastug, E., Bennis, M., & Debbah, M. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6871674 · Cited by 1,146
Cache in the air: exploiting content caching and delivery techniques for 5G systems
Wang, X., Chen, M., Taleb, T., Ksentini, A., & Leung, V. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736753 · Cited by 1,063 · cited 1×
“Caching, on the other hand, brings contents closer to users by pre-fetching the contents during the off-peak time and hence can greatly reduce the network congestion and improve the user-perceived experience [5], [8], [9].”
BackgroundVariations and extension of the convex–concave procedure
Lipp, T., & Boyd, S. (2016) · Optimization and Engineering · doi:10.1007/s11081-015-9294-x · Cited by 744
Femtocaching and device-to-device collaboration: A new architecture for wireless video distribution
Golrezaei, N., Molisch, A. F., Dimakis, A. G., & Caire, G. (2013) · IEEE Communications Magazine · doi:10.1109/mcom.2013.6495773 · Cited by 686
Cited by
Big data caching for networking: moving from cloud to edge
Zeydan, E., Bastug, E., Bennis, M., Kader, M. A., Karatepe, I. A., Er, A. S., & Debbah, M. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7565185 · Cited by 310
Li, L., Zhao, G., & Blum, R. S. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2820021 · Cited by 282
Echo State Networks for Proactive Caching in Cloud-Based Radio Access Networks With Mobile Users
Chen, M., Saad, W., Yin, C., & Debbah, M. (2017) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2017.2683482 · Cited by 176
Li, X., Wang, X., Wan, P.-J., Han, Z., & Leung, V. C. M. (2018) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2018.2844658 · Cited by 140
Cooperative Multigroup Multicast Transmission in Integrated Terrestrial-Satellite Networks
Zhu, X., Jiang, C., Yin, L., Kuang, L., Ge, N., & Lu, J. (2018) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2018.2832780 · Cited by 108
Metadata
- Authors
- Tao, M., Chen, E., Zhou, H., & Yu, W.
- Venue
- IEEE Transactions on Wireless Communications
- Published
- 2016-09
- Volume
- 15
- Issue
- 9
- Pages
- 6118-6131
- ISSN
- 1536-1276 (ISSN-L)
- 1558-2248
- OpenAlex
- W2213621529
- Cited by
- 423
- References
- 28
- FWCI
- 76.43
- 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: Content-Centric Sparse Multicast Beamforming for Cache-Enabled Cloud RAN. https://app.cochat.ai/papers/10.1109/twc.2016.2578922
- The paper
- Tao, M., Chen, E., Zhou, H., & Yu, W. (2016). Content-Centric Sparse Multicast Beamforming for Cache-Enabled Cloud RAN. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/twc.2016.2578922
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.
