The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Coding Techniques for Repairability in Networked Distributed Storage Systems
Open accessAbstract
This survey comprises a tutorial on traditional erasure codes and their applications to networked distributed storage systems (NDSS), followed by a survey of novel code families tailor made for better repairability in NDSS.
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Cites
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Fundamentals of Wireless Communication
Tse, D., & Viswanath, P. (2005) · doi:10.1017/cbo9780511807213 · Cited by 13,162
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
Zhang, Q., & Li, H. (2007) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2007.892759 · Cited by 10,069
Communication Theory of Secrecy Systems
Shannon, C. E. (1949) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1949.tb00928.x · Cited by 9,440
Shi, Q., Razaviyayn, M., Luo, Z.-Q., & He, C. (2011) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2011.2147784 · Cited by 2,129
A tutorial on decomposition methods for network utility maximization
Palomar, D. P., & Chiang, M. (2006) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2006.879350 · Cited by 1,647
An introduction to convex optimization for communications and signal processing
Luo, Z.-Q., & Yu, W. (2006) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2006.879347 · Cited by 562
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Xiao, M., Mumtaz, S., Huang, Y., Dai, L., Li, Y., Matthaiou, M., Karagiannidis, G. K., Bjornson, E., Yang, K., I, C.-L., et al. (2017) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2017.2719924 · Cited by 1,122
Learning to Optimize: Training Deep Neural Networks for Interference Management
Sun, H., Chen, X., Shi, Q., Hong, M., Fu, X., & Sidiropoulos, N. D. (2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2018.2866382 · Cited by 874
Quantized Precoding for Massive MU-MIMO
Jacobsson, S., Durisi, G., Coldrey, M., Goldstein, T., & Studer, C. (2017) · IEEE Transactions on Communications · doi:10.1109/tcomm.2017.2723000 · Cited by 367
A Deep Learning Framework for Optimization of MISO Downlink Beamforming
Xia, W., Zheng, G., Zhu, Y., Zhang, J., Wang, J., & Petropulu, A. P. (2020) · IEEE Transactions on Communications · doi:10.1109/tcomm.2019.2960361 · Cited by 345
Learning to optimize: Training deep neural networks for wireless resource management
Sun, H., Chen, X., Shi, Q., Hong, M., Fu, X., & Sidiropoulos, N. D. (2017) · 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) · doi:10.1109/spawc.2017.8227766 · Cited by 308
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
Robust Group Sparse Beamforming for Multicast Green Cloud-RAN With Imperfect CSI
Shi, Y., Zhang, J., & Letaief, K. B. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2442957 · Cited by 63
Metadata
- Authors
- Oggier, F., & Datta, A.
- Venue
- Foundations and Trends in Communications and Information Theory
- Publisher
- Emerald
- Published
- 2013-06-06
- Volume
- 9
- Issue
- 4
- Pages
- 383-466
- ISSN
- 1567-2190 (ISSN-L)
- 1567-2328
- OpenAlex
- W2022800466
- Cited by
- 305
- References
- 7
- FWCI
- 58.15
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
