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I received my PhD and MASc in Electrical and Computer Engineering from Ryerson University in 2019 and 2015, respectively. Prior to joining Laurier, I was a postdoctoral fellow at DABNEL lab, Computer Science department at Ryerson. I also worked as a research assistant in Computer Science department at Thompson River University in 2020.
In the last few years, I have been working on communication networking aspects of resource management in 5G cloud radio access networks with emphasis on algorithm design, network architecture development, and system-level performance analysis. I, along with my students, colleagues, and supervisors, have designed novel algorithms and communication protocols for Cloud RAN supported IoT networks, that have both (i) enhanced network performance, in terms of spectrum efficiency, coverage, and energy efficiency, and (ii) satisfied a wide range of cellular IoT devices' requirements and constraints.
My research interests include:
- wireless technologies, standards, and protocols for the next generation communication networks (i.e., 5G/6G , Industrial IoT networks (IIoT))
- resource management in 5G/6G and beyond networks
- industrial IoT networks
- software-defined wireless sensor networks
- machine learning application in next generation communication networks
- Nomination for the Governor General Gold Medal (GGGM) Award, Ryerson University, 2019
- Doctoral Completion Award, Ryerson University, 2019
- Graduate Research Development Award, Ryerson University, 2018
- Ontario Graduate Scholarship (OGS), 2016/17/18
- Graduate Research Excellence Award (GREA), Ryerson University, 2014/15/16/17
L. Ferdouse, I. Woungang, A. Anpalagan and K. Yamamoto, "A Resource Allocation Policy for Downlink Communication in Distributed IRS Aided Multiple-Input Single-Output Systems," in IEEE Transactions on Communications, Feb. 2023
S. Taimoor, L. Ferdouse, W. Ejaz, "Holistic resource management in UAV-assisted wireless networks: An optimization perspective," in Journal of Network and Computer Applications, Aug. 2022
L. Ferdouse, I.Woungang, A. Anpalagan and S. Erkucuk, ”Energy Efficient Downlink Resource Allocation in Cellular IoT Supported H-CRANs”, in IEEE Transactions on Vehicular Technology, Jun. 2020.
L. Ferdouse, S. Erkucuk, A. Anpalagan, and I. Woungang, ”Energy efficient SCMA supported downlink Cloud-RANs for 5G networks”, in IEEE Access, vol. 8, pp. 1416-1430, Jan. 2020.
L. Ferdouse, A. Anpalagan, and S. Erkucuk, ”Joint communication and computing resource allocation in 5G cloud radio access networks”, in IEEE Transactions on Vehicular Technology, vol. 68, no. 9, pp. 9122-9135, Jan. 2019.
L. Ferdouse, A. Anpalagan, and M. Nadarajah, "Performance of Dynamic Access Class Barring Method in Cellular M2M Networks" , Springer, Wireless Personal Communications, pp.1-17,2016.
L. Ferdouse, A.Anpalagan, A.Misra,"Congestion and Overload Control Techniques in Massive M2M Systems: A Survey." Wiley, Transactions on Emerging Telecommunications Technologies, Mar 2015.
L. Ferdouse, A.Anpalagan, " Relay Selection Based on Bayesian Decision Theory in Cooperative Wireless Networks", IEEE Canadian Journal of Electrical and Computer Engineering, vol. 38, no. 2,pp.116-124, May 2015.
L. Ferdouse, O.Das and A. Anpalagan, "Auction based Distributed Resource Allocation for Delay Aware OFDM based Cloud-RAN System ", IEEE Globecom, Singapore, Dec. 2017.
L. Ferdouse, A. Noman, A. Bulzacki and A. Anpalagan, "Energy Efficient Multiple Association in CoMP based 5G Cloud-RAN Systems", IEEE 85th Vehicular Technology Conference: VTC2017-Fall, Toronto, Canada, Sep. 2017.
L. Ferdouse, W. Ejaz, A. Anpalagan and A. M. Khattak, "Joint Workload Scheduling and BBU Allocation in Cloud-RAN for 5G Networks," The 32nd ACM Symposium on Applied Computing, Marrakesh, Morocco, Apr. 2017.
L. Ferdouse and A. Anpalagan, "A dynamic access class barring scheme to balance massive access requests among base stations over the cellular M2M networks " in Proc. of IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Hong Kong, pp. 1283-1288, Sep. 2015.
- CP322: Machine Learning
- CP372: Computer Networks
- CP104: Introduction to Programming
Contact Info:
Office location: N2079, Science Building
Office hours:
Monday 11 a.m. to 1 p.m., Wednesday 11 a.m. to 1 p.m.