Journal Papers

These are submitted, accepted, and published journal papers by people in the Embedded Signal Processing Laboratory related to machine learning for communication systems.
  1. Y. Cho, J. Choi, and B. L. Evans, “Learning-Based One-Bit Maximum Likelihood Detection for Massive MIMO Systems: Dithering-Aided Adaptive Approach”, IEEE Transactions on Vehicular Technology, accepted for publication.

  2. E. Balti and B. L. Evans, "A Unified Framework for Full-Duplex Massive MIMO Cellular Networks with Low-Reso lution Data Converters", IEEE Open Journal of the Communications Society, vol. 4, Jan. 2023, pp. 1-28. 10.1109/OJCOMS.2022.3230327.

  3. F. B. Mismar, A. AlAmmouri, A. Alkhateeb, J. G. Andrews, and B. L. Evans, "Deep Learning Predictive Band Switching in Wireless Networks", IEEE Transactions on Wireless Communications, vol. 20, no. 1, Jan. 2021, pp. 96-109, DOI 10.1109/TWC.2020.3023397.

  4. F. B. Mismar, B. L. Evans, and A. Alkhateeb, "Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination", IEEE Transactions on Communications, vol. 68, no. 3, Mar. 2020, pp. 1581-1592, DOI 10.1109/TCOMM.2019.2961332. One of the top 50 most accessed articles in January, February, March, April, May, June, July, August, September, October, and November of 2020 among all articles in the IEEE Transactions on Communications.

  5. F. B. Mismar, J. Choi, and B. L. Evans, ``A Framework for Automated Cellular Network Tuning with Reinforcement Learning'', IEEE Transactions on Communications, vol. 67, no. 10, Oct. 2019, pp. 7152-7167, DOI 10.1109/TCOMM.2019.2926715.

  6. F. B. Mismar and B. L. Evans, ``Deep Learning in Downlink Coordinated Multipoint in New Radio Heterogeneous Networks'' IEEE Wireless Communication Letters, vol. 8, no. 4, Aug. 2019, pp. 1040-1043, DOI 10.1109/LWC.2019.2904686.

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