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Faris Mismar

Plano, TX, USA
Senior Principal Consultant

Biography

Dr. Faris B. Mismar is a Bell Labs senior principal consultant. He brings over 18 years of professional experience in telecommunications and seven years in machine learning.  He worked for Motorola, Ericsson, Samsung, and Nokia.  He has been working on improving radio resource management algorithms through machine learning since 2015.  Dr. Mismar is a Marcus Wallenberg Scholar.  He has published over 10 conference and journal papers in various IEEE venues.  He continues to serve as a reviewer for several IEEE conferences and journals.  Faris is an adjunct professor of electrical and computer engineering at The University of Texas at Dallas.  He is a Senior Member of the IEEE.

Competencies

Future Wireless Communications Technologies
Machine Learning and Automation
Cloud and Virtualization
Enterprise and Private Networks
Heterogeneous Networks Roll-out Strategy Development

Education

Ph.D. in Electrical and Computer Engineering, The University of Texas at Austin.

MBA, The University of Texas at Dallas.

MS in Electrical Engineering, The University of Texas at Dallas.

BSc. in Computer Engineering, The University of Jordan.

Professional activities

Senior Member, IEEE, 2017-present.

Selected articles and publications

Journal Publications

[J1] F. B. Mismar and J. Hoydis, “Unsupervised Learning in Next-Generation Networks: Real-Time Performance Self-Diagnosis,” in IEEE Communications Letters, vol. 25, no. 10, pp. 3330-3334, Oct. 2021.
[J2] F. B. Mismar, A. AlAmmouri, A. Alkhateeb, B. L. Evans, and J. G. Andrews, “Deep Learning Predictive Band Switching in Wireless Networks,” in IEEE Transactions on Wireless Communications, vol. 20, no. 1, pp. 96-109, Jan 2021.
[J3] F. B. Mismar, B. L. Evans, and A. Alkhateeb, “Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination,” in IEEE Transactions on Communications, vol. 68, no. 3, pp. 1581-1592, Mar. 2020.
[J4] F. B. Mismar, J. Choi, and B. L. Evans, “A Framework for Automated Cellular Network Tuning with Reinforcement Learning,” in IEEE Transactions on Communications, vol. 67, no. 10, pp. 7152-7167, Oct. 2019.
[J5] F. B. Mismar and B. L. Evans, “Deep Learning in Downlink Coordinated Multipoint in New Radio Heterogeneous Networks,” in IEEE Wireless Communications Letters, vol. 8, no. 4, pp. 1040-1043, Aug. 2019.

Conferences

[C1] F. B. Mismar, “Intermodulation Interference Detection in 6G Networks: A Machine Learning Approach,” Proc. IEEE Vehicular 95th Technology Conference (invited paper), Helsinki, Finland, Aug. 2022, pp. 1-6.
[C2] A. Taha, Y. Zhang, F. B. Mismar, and A. Alkhateeb “Deep Reinforcement Learning for Intelligent Reflecting Surfaces: Towards Standalone Operation,” Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications, Atlanta, GA, USA, May 2020, pp. 1-5.
[C3] F. B. Mismar and B. L. Evans, “Deep Q-Learning for Self-Organizing Networks Fault Management and Radio Performance Improvement,” Proc. IEEE Asilomar, Pacific Grove, CA, USA, Oct. 2018, pp. 1457-1461.
[C4] F. B. Mismar and B. L. Evans, “Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells,” Proc. IEEE Asilomar, Pacific Grove, CA, USA, Oct. 2018, pp. 1485-1489.
[C5] F. B. Mismar and B. L. Evans, “Partially Blind Handovers for mmWave New Radio Aided by Sub-6 GHz LTE Signaling,” Proc. IEEE Intl. Conf. on Communications Workshops, Kansas City, MO, May 2018, pp. 1-5.
[C6] I. da Silva, Y. Wang, F. B. Mismar and W. Su, “Event-based Performance Monitoring for Inter-System Cell Reselection:
A SON Enabler,” International Symposium on Wireless Communication Systems, Paris, France, Oct. 2012, pp. 6-10.

Patents

[P1] F. B. Mismar and S. Nammi, “METHODS FOR ADAPTING A REPORTING PERIOD FOR A USER EQUIPMENT,” U.S. Patent: 9,883,528, issued September 2016.
[P2] S. Nammi and F. B. Mismar, “A METHOD TO TRANSMIT SIGNALING RADIO BEARER MESSAGES IN MULTI ANTENNA WIRELESS SYSTEMS,” U.S. Patent: US 9,762,456, issued September 2016.