[1]

R. Zhang and C. K. Ho, “MIMO broadcasting for simultaneous wireless information and power transfer,” IEEE Transactions on Wireless Communications, vol. 12, no. 5, pp. 1989–2001, 2013.

doi: 10.1109/twc.2013.031813.120224
[2]

S. Lee, L. Liu, and R. Zhang, “Collaborative wireless energy and information transfer in interference channel,” IEEE Transactions on Wireless Communications, vol. 14, no. 1, pp. 545–557, 2015.

doi: 10.1109/twc.2014.2354335
[3]

Z. Zong, H. Feng, F. R. Yu, N. Zhao, T. Yang, and B. Hu, “Optimal transceiver design for SWIPT in $K$-User MIMO interference channels,” IEEE Transactions on Wireless Communications, vol. 15, no. 1, pp. 430–445, 2016.

doi: 10.1109/twc.2015.2474857
[4]

Y. Xing, Y. Qian, and L. Dong, “Deep learning for optimized wireless transmission to multiple rf energy harvesters,” in Proceedings of the 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), Chicago, IL, USA, August 2018.

[5]

J. Park and B. Clerckx, “Joint wireless information and energy transfer in a two-user MIMO interference channel,” IEEE Transactions on Wireless Communications, vol. 12, no. 8, pp. 4210–4221, 2013.

doi: 10.1109/twc.2013.071913.130084
[6]

W. Wu, X. Zhang, S. Wang, and B. Wang, “Max-min fair wireless energy transfer for multiple-input multiple-output wiretap channels,” IET Communications, vol. 10, no. 7, pp. 739–744, 2016.

doi: 10.1049/iet-com.2015.0753
[7]

A. Thudugalage, S. Atapattu, and J. Evans, “Beamformer design for wireless energy transfer with fairness,” in Proceedings of the 2016 IEEE International Conference on Communications (ICC), pp. 1–6, Kuala Lumpur, Malaysia, May 2016.

[8]

Y. Xing and L. Dong, “Passive radio-frequency energy harvesting through wireless information transmission,” in Proceedings of the 2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS), pp. 73–80, Ottawa, ON, Canada, June 2017.

[9]

P.-V. Mekikis, A. Antonopoulos, E. Kartsakli, A. S. Lalos, L. Alonso, and C. Verikoukis, “Information exchange in randomly deployed dense wsns with wireless energy harvesting capabilities,” IEEE Transactions on Wireless Communications, vol. 15, no. 4, pp. 3008–3018, 2016.

doi: 10.1109/twc.2016.2514419
[10]

J. Xu and R. Zhang, “A general design framework for mimo wireless energy transfer with limited feedback,” IEEE Transactions on Signal Processing, vol. 64, no. 10, pp. 2475–2488, 2016.

doi: 10.1109/tsp.2016.2526965
[11]

K. W. Choi, D. I. Kim, and M. Y. Chung, “Received power-based channel estimation for energy beamforming in multiple-antenna RF energy transfer system,” IEEE Transactions on Signal Processing, vol. 65, no. 6, pp. 1461–1476, 2017.

doi: 10.1109/tsp.2016.2637320
[12]

V. Mnih, K. Kavukcuoglu, D. Silver et al., “Playing atari with deep reinforcement learning,” 2013, https://arxiv.org/abs/1312.5602.

[13]

Y. Xing, Y. Qian, and L. Dong, “A multi-armed bandit approach to wireless information and power transfer,” IEEE Communications Letters, vol. 24, no. 4, pp. 886–889, 2020.

doi: 10.1109/lcomm.2020.2969658
[14]

Y. He, Z. Zhang, F. R. Yu et al., “Deep reinforcement learning-based optimization for cache-enabled opportunistic interference alignment wireless networks,” IEEE Transactions on Vehicular Technology, vol. 66, no. 11, pp. 10 433–510 445, 2017.

doi: 10.1109/tvt.2017.2751641
[15]

J. Foerster, I. A. Assael, N. de Freitas, and S. Whiteson, “Learning to communicate with deep multi-agent reinforcement learning,” 2016, https://arxiv.org/abs/1605.06676.

[16]

Z. Xu, Y. Wang, J. Tang, J. Wang, and M. C. Gursoy, “A deep reinforcement learning based framework for power-efficient resource allocation in cloud rans,” in Proceedings of the 2017 IEEE International Conference on Communications (ICC), pp. 1–6, IEEE, Paris, France, May 2017.

[17]

H. Van Hasselt, A. Guez, and D. Silver, “Deep reinforcement learning with double q-learning,” 2016, https://arxiv.org/abs/1509.06461.

[18]

Z. Wang, T. Schaul, M. Hessel, H. Van Hasselt, M. Lanctot, and N. De Freitas, “Dueling network architectures for deep reinforcement learning,” 2015, https://arxiv.org/abs/1511.06581.

[19]

E. Biglieri, R. Calderbank, A. Constantinides, A. Goldsmith, A. Paulraj, and H. V. Poor, MIMO Wireless Communications, Cambridge University Press, Cambridge, UK, 2007.

[20]

S. Timotheou, I. Krikidis, S. Karachontzitis, and K. Berberidis, “Spatial domain simultaneous information and power transfer for mimo channels,” IEEE Transactions on Wireless Communications, vol. 14, no. 8, pp. 4115–4128, 2015.

doi: 10.1109/twc.2015.2416721
[21]

D. Mishra and G. C. Alexandropoulos, “Jointly optimal spatial channel assignment and power allocation for mimo swipt systems,” IEEE Wireless Communications Letters, vol. 7, no. 2, pp. 214–217, 2018.

doi: 10.1109/lwc.2017.2765320
[22]

A. G. Barto, S. J. Bradtke, and S. P. Singh, “Learning to act using real-time dynamic programming,” Artificial intelligence, vol. 72, no. 1-2, pp. 81–138, 1995.

doi: 10.1016/0004-3702(94)00011-o
[23]

L. Dong and Y. Liu, “Parallel sub-channel transmission for cognitive radios with multiple antennas,” Wireless Personal Communications, vol. 79, no. 3, pp. 2069–2087, 2014.

doi: 10.1007/s11277-014-1974-x
[24]

Y. Xing, H. Pan, B. Xu, T. Zhao, C. Tapparello, and Y. Qian, “Multiuser data dissemination in OFDMA system based on deep q-network,” in Proceedings of the IEEE IEMTRONIC (International IOT, Electronics and Mechatronics Conference), Toronto, Canada, April 2021.

[25]

J. Cavers, Mobile Channel Characteristics, Springer Science & Business Media, Berlin, Germany, 2006.

[26]

T.-Q. Wu and H.-C. Yang, “On the performance of overlaid wireless sensor transmission with rf energy harvesting,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 8, pp. 1693–1705, 2015.

doi: 10.1109/jsac.2015.2391892
[27]

A. Slivkins, “Introduction to multi-armed bandits,” 2019, https://arxiv.org/abs/1904.07272.

[28]

S. Wang, H. Liu, P. H. Gomes, and B. Krishnamachari, “Deep reinforcement learning for dynamic multichannel access in wireless networks,” IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 2, pp. 257–265, 2018.

doi: 10.1109/tccn.2018.2809722