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We study the problem of optimal power allocation in a single-hop ad hoc wireless network.
C. E. Shannon, “A mathematical theory of communication,” The Bell system technical journal , vol. 27, no. 3, pp. 379–423, 1948
1948
Earlier work this paper cites.
W. Yu and R. Lui, “Dual methods for nonconvex spectrum optimization of multicarrier systems,” IEEE Trans. Commun. , vol. 54, no. 7, pp. 1310–1322, 2006
2006
Earlier work this paper cites.
J. Huang, R. A. Berry, and M. L. Honig, “Distributed interference compensation for wireless networks,” IEEE J. Sel. Areas Commun. , vol. 24, no. 5, pp. 1074–1084, 2006
2006
Earlier work this paper cites.
M. Cave, C. Doyle, and W. Webb, Essentials of Modern Spectrum Management . Cambridge University Press Cambridge, 2007
2007
Earlier work this paper cites.
Z. Luo and S. Zhang, “Dynamic spectrum management: Complexity and duality,” IEEE J. Sel. Topics Signal Process. , vol. 2, no. 1, pp. 57–73, 2008
2008
Earlier work this paper cites.
F. Wang, M. Krunz, and S. Cui, “Price-based spectrum management in cognitive radio networks,” IEEE J. Sel. Topics Signal Process. , vol. 2, no. 1, pp. 74–87, 2008
2008
Earlier work this paper cites.
S. Hayashi and Z.-Q. Luo, “Spectrum management for interference-limited multiuser communication systems,” IEEE Trans. Inf. Theory , vol. 55, no. 3, pp. 1153–1175, 2009
2009
Earlier work this paper cites.
J. Papandriopoulos and J. S. Evans, “SCALE: A low-complexity distributed protocol for spectrum balancing in multiuser DSL networks,” IEEE Trans. Inf. Theory , vol. 55, no. 8, pp. 3711–3724, 2009
2009
Earlier work this paper cites.
K. Gregor and Y. LeCun, “Learning fast approximations of sparse coding,” in Intl. Conf. Mach. Learn. (ICML) , 2010, pp. 399–406
2010
Earlier work this paper cites.
H. Boche, S. Naik, and T. Alpcan, “Characterization of convex and concave resource allocation problems in interference coupled wireless systems,” IEEE Trans. Signal Process. , vol. 59, no. 5, pp. 2382–2394, 2011
2011
Earlier work this paper cites.
Y.-F. Liu, Y.-H. Dai, and Z.-Q. Luo, “Coordinated beamforming for MISO interference channel: Complexity analysis and efficient algorithms,” IEEE Trans. Signal Process. , vol. 59, no. 3, pp. 1142–1157, 2011
2011
Earlier work this paper cites.
Q. Shi, M. Razaviyayn, Z.-Q. Luo, and C. He, “An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel,” IEEE Trans. Signal Process. , vol. 59, no. 9, pp. 4331–4340, 2011
2011
Earlier work this paper cites.
M. Razaviyayn, M. Hong, and Z.-Q. Luo, “Linear transceiver design for a MIMO interfering broadcast channel achieving max–min fairness,” Signal Processing , vol. 93, no. 12, pp. 3327–3340, 2013
2013
Earlier work this paper cites.
2013
Earlier work this paper cites.
2014
Earlier work this paper cites.
M. Hong and Z.-Q. Luo, “Chapter 8 - Signal Processing and Optimal Resource Allocation for the Interference Channel,” in Academic Press Library in Signal Processing: Volume 2 , ser. Academic Press Library in Signal Processing, N. D. Sidiropoulos, F. Gini, R. Chellappa, and S. Theodoridis, Eds. Elsevier, 2014, vol. 2, pp. 409 – 469
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
Q. Yu, Y. Zhao, L. Zhang, K. Yang, and S. Leng, “A fair resource allocation algorithm for data and energy integrated communication networks,” Energy , vol. 1, p. U2, 2016
2016
Earlier work this paper cites.
M. Defferrard, X. Bresson, and P. Vandergheynst, “Convolutional neural networks on graphs with fast localized spectral filtering,” in Adv. Neural Info. Process. Syst. (NeurIPS) , 2016, pp. 3844–3852
2016
Cited alongside, same era.
A. G. Marques, S. Segarra, G. Leus, and A. Ribeiro, “Sampling of graph signals with successive local aggregations,” IEEE Trans. Signal Process. , vol. 64, no. 7, pp. 1832–1843, 2016
2016
Cited alongside, same era.
2017
Cited alongside, same era.
Z. Liu, X. Li, P. Luo, C. C. Loy, and X. Tang, “Deep learning markov random field for semantic segmentation,” IEEE Trans. Pattern Analy. and Machine Intel. , vol. 40, no. 8, pp. 1814–1828, 2017
2017
Cited alongside, same era.
Z. Qin, H. Ye, G. Y. Li, and B.-H. F. Juang, “Deep learning in physical layer communications,” IEEE Wirel. Commun. , vol. 26, no. 2, pp. 93–99, 2019
2019
Later among the works it cites.
T. Zhang and S. Mao, “Energy-efficient power control in wireless networks with spatial deep neural networks,” IEEE Trans. Cognitive Comm. and Netw. , vol. 6, no. 1, pp. 111–124, 2019
2019
Later among the works it cites.
M. Eisen, C. Zhang, L. F. Chamon, D. D. Lee, and A. Ribeiro, “Learning optimal resource allocations in wireless systems,” IEEE Trans. Signal Process. , vol. 67, no. 10, pp. 2775–2790, 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
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T. N. Kipf and M. Welling, “Semi-supervised classification with graph convolutional networks,” in Intl. Conf. Learn. Repres. (ICLR) , 2017
2017
Cited alongside, same era.
2017
Cited alongside, same era.
S. Segarra, A. G. Marques, and A. Ribeiro, “Optimal graph-filter design and applications to distributed linear network operators,” IEEE Trans. Signal Process. , vol. 65, no. 15, pp. 4117–4131, 2017
2017
Cited alongside, same era.
W. Lee, M. Kim, and D.-H. Cho, “Deep power control: Transmit power control scheme based on convolutional neural network,” IEEE Commun. Lett. , vol. 22, no. 6, pp. 1276–1279, 2018
2018
Cited alongside, same era.
S. Wang, H. Liu, P. H. Gomes, and B. Krishnamachari, “Deep reinforcement learning for dynamic multichannel access in wireless networks,” IEEE Trans. Cognitive Comm. and Netw. , vol. 4, no. 2, pp. 257–265, 2018
2018
Cited alongside, same era.
Z. Chang, L. Lei, Z. Zhou, S. Mao, and T. Ristaniemi, “Learn to cache: Machine learning for network edge caching in the big data era,” IEEE Wirel. Commun. , vol. 25, no. 3, pp. 28–35, 2018
2018
Cited alongside, same era.
H. Sun, X. Chen, Q. Shi, M. Hong, X. Fu, and N. D. Sidiropoulos, “Learning to optimize: Training deep neural networks for interference management,” IEEE Trans. Signal Process. , vol. 66, no. 20, pp. 5438–5453, 2018
2018
Cited alongside, same era.
Y. Ding, X. Xue, Z. Wang, Z. Jiang, X. Fan, and Z. Luo, “Domain knowledge driven deep unrolling for rain removal from single image,” in Intl. Conf. on Digital Home (ICDH) . IEEE, 2018, pp. 14–19
2018
Cited alongside, same era.
2019
Later among the works it cites.
Y. Li, M. Tofighi, V. Monga, and Y. C. Eldar, “An algorithm unrolling approach to deep image deblurring,” in IEEE Intl. Conf. Acoust., Speech and Signal Process. (ICASSP) . IEEE, 2019, pp. 7675–7679
2019
Later among the works it cites.
O. Solomon, R. Cohen, Y. Zhang, Y. Yang, Q. He, J. Luo, R. J. van Sloun, and Y. C. Eldar, “Deep unfolded robust PCA with application to clutter suppression in ultrasound,” IEEE Trans. Medical Imag. , vol. 39, no. 4, pp. 1051–1063, 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
D. Xu, X. Chen, C. Wu, S. Zhang, S. Xu, and S. Cao, “Energy-efficient subchannel and power allocation for hetnets based on convolutional neural network,” in IEEE Veh. Technol. Conf. (VTC) . IEEE, 2019, pp. 1–5
2019
Later among the works it cites.
T. Van Chien, E. Bjornson, and E. G. Larsson, “Sum spectral efficiency maximization in massive MIMO systems: Benefits from deep learning,” in IEEE Intl. Conf. on Commun. (ICC) . IEEE, 2019, pp. 1–6
2019
Later among the works it cites.
W. Cui, K. Shen, and W. Yu, “Spatial deep learning for wireless scheduling,” IEEE J. Sel. Areas Commun. , vol. 37, no. 6, pp. 1248–1261, 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
T. M. Roddenberry and S. Segarra, “HodgeNet: Graph neural networks for edge data,” in Asilomar Conf. Signals, Systems, and Computers , 2019, pp. 220–224
2019
Later among the works it cites.
A. Balatsoukas-Stimming and C. Studer, “Deep unfolding for communications systems: A survey and some new directions,” in IEEE Intl. Wrksp. Signal Process. Sys. (SiPS) . IEEE, 2019, pp. 266–271
2019
Later among the works it cites.
R. Liu, S. Cheng, L. Ma, X. Fan, and Z. Luo, “Deep proximal unrolling: Algorithmic framework, convergence analysis and applications,” IEEE Trans. Image Process. , vol. 28, no. 10, pp. 5013–5026, 2019
2019
Later among the works it cites.
M. Eisen and A. R. Ribeiro, “Optimal wireless resource allocation with random edge graph neural networks,” IEEE Trans. Signal Process. , 2020
2020
Closest in time.
F. Meng, P. Chen, L. Wu, and J. Cheng, “Power allocation in multi-user cellular networks: Deep reinforcement learning approaches,” IEEE Trans. Wireless Commun. , 2020
2020
Closest in time.