Machine Learning based Antenna Selection and Power Allocation in Multi-user MISO Systems

Vu, Thang Xuan; Lei, Lei; Chatzinotas, Symeon; Ottersten, Björn

Paper published in a book (Scientific congresses, symposiums and conference proceedings)

Vu, Thang Xuan; Lei, Lei; Chatzinotas, Symeon et al.

2019 • In 2019 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

Peer reviewed

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https://hdl.handle.net/10993/41131

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Disciplines :

Electrical & electronics engineering

Author, co-author :

Vu, Thang Xuan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Lei, Lei ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Chatzinotas, Symeon ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Ottersten, Björn ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

External co-authors :

Language :

English

Title :

Machine Learning based Antenna Selection and Power Allocation in Multi-user MISO Systems

Publication date :

June 2019

Event name :

2019 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

Event date :

06-19

Main work title :

2019 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

Peer reviewed :

Peer reviewed

European Projects :

H2020 - 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems

FnR Project :

FNR11691338 - Proactive Edge Caching For Content Delivery Networks Powered By Hybrid Satellite/Terrestrial Backhauling, 2017 (01/07/2018-31/12/2021) - Bjorn Ottersten

Funders :

CE - Commission Européenne [BE]

Available on ORBilu :

since 03 December 2019

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Bibliography

E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, "Massive MIMO for next generation wireless systems, " IEEE Commun. Mag., vol. 52, no. 2, pp. 186-195, Feb. 2014.
R. Heath and A. Paulraj, "Antenna selection for spatial multiplexing systems based on minimum error rate, " in IEEE Int. Conf. Commun., Jun. 2001, pp. 2276-2280.
Y. Pei, T.-H. Pham, and Y. Liang, "How many RF chains are optimal for large-scale MIMO systems when circuit power is considered?" in Proc. IEEE Global Commun. Conf., Dec. 2012, pp. 3868-3873.
O. Tervo, L. Tran, H. Pennanen, S. Chatzinotas, M. Juntti, B. Ottersten, "Energy-Efficient Multi-Cell Multigroup Multicasting with Joint Beamforming and Antenna Selection, " IEEE Trans. Signal Process., vol. 66, no. 18, pp. 4904-4919, 2018.
S. Domouchtsidis, C. Tsinos, S. Chatzinotas, and B. Ottersten, "Symbol-Level Precoding for Low Complexity Transmitter Architectures in Large-Scale Antenna Array Systems, " IEEE Trans. Wireless Commun., vol. 18, no. 2, pp. 852-863, Feb. 2019.
O. Mehanna, N. D. Sidiropoulos, and G. B. Giannakis, "Multicast beamforming with antenna selection, " in IEEE Int. Workshop Signal Process. Adv. Wireless Commun., Jun. 2012, pp. 70-74.
J. G. Andrews, S. Buzzi, W. Choi, S. V. Hanly, A. Lozano, A. C. K. Soong, and J. C. Zhang, "What will 5G be?" IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065-1082, Jun. 2014.
L. Lei, L. You, G. Dai, T. X. Vu, D. Yuan, and S. Chatzinotas, "A deep learning approach for optimizing content delivering in cache-enabled HetNet, " in Proc. IEEE Int. Symp. Wireless Commun. Syst., Aug. 2017, pp. 449-453.
T. Oshea and J. Hoydis, "An introduction to deep learning for the physical layer, " IEEE Trans. Cog. Commun. Netw., vol. 3, no. 4, pp. 563-575, Dec. 2017.
H. Sun, X. Chen, Q. Shi, M. Hong, X. Fu, and N. D. Sidiropoulos, "Learning to optimize: Training deep neural networks for wireless resource management, " in IEEE Int. Workshop Signal Process. Adv. Wireless Commun., Jul. 2017, pp. 247-252.
L. Lei, T. X. Vu, L. You, S. Fowler, and D. Yuan, "Efficient minimumenergy scheduling with machine-learning based predictions for multiuser MISO systems, " in Proc. IEEE Int. Conf. Commun., May 2018, pp. 1-6.
J. Joung, "Machine Learning-Based Antenna Selection in Wireless Communications, " in IEEE Commun. Lett., vol. 20, no. 11, pp. 2241-2244, Nov. 2016.
M. S. Ibrahim, A. S. Zamzam, X. Fu, and N. D. Sidiropoulos, "Learningbased antenna selection for multicasting, " in Proc. IEEE Int. Workshop Signal Process. Adv. Wireless Commun., Jun. 2018, pp. 1-5.
D. He, C. Liu, T. Q. S. Quek, and H. Wang, "Transmit antenna selection in MIMO wiretap channels: A machine learning approach, " IEEE Wireless Commun. Lett., vol. 7, no. 4, pp. 634-637, Aug. 2018.
S. Kaviani, O. Simeone, W. A. Krzymien and S. Shamai, "Linear MMSE precoding and equalization for network MIMO with partial cooperation, " in Proc. IEEE Global Commun. Conf., Dec. 2011, pp. 1-6.