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Faculty
Faculty

Imtiaz Ahmed

Assistant Professor

  • Department of Electrical Engineering and Computer Science, CEA
  • College of Engineering and Architecture (CEA)

Biography

Dr. Ahmed works in the areas of wireless communications, signal processing, and computer networks. He finished his undergrad and Masters in Electrical and Electronic Engineering (EEE) from Bangladesh University of Engineering and Technology (BUET). He completed his Ph.D. in Electrical and Computer Engineering (ECE) from the University of British Columbia (UBC), Vancouver, BC, Canada in 2014. He then worked as a postdoctoral fellow at McGill University during 2014-15. Dr. Ahmed worked as a wireless systems engineer in Intel Corporation, San Diego, California for more than 3 years. He worked in developing performance simulation framework and baseband demodulation algorithms for LTE and 5G NR in Intel. He also worked as a visiting staff engineer in Oppo US research facility. Dr. Ahmed was involved with a California-based start-up, where he developed innovative algorithms for human-emotion detection and monitoring. Before joining Howard University, he worked as an Assistant Professor in Marshall University, Huntington, WV.

Currently, Dr. Ahmed is working on diversified topics in the areas of 5G and beyond 5G cellular communication systems. In particular, his research interests include artificial intelligence in physical layer design, UAV and HAPS assisted communications for beyond 5G,  energy harvesting communications for mIoT, beamforming and beamcombining design for mmW communications for 5G NR, etc.

Education & Expertise

Education

Electrical and Computer Engineering

Ph.D.
University of British Columbia
2014

Electrical and Electronic Engineering

M.Sc. Engg.
Bangladesh University of Engineering and Technology
2008

Electrical and Electronic Engineering

B.Sc. Engg.
Bangladesh University of Engineering and Technology
2006

Expertise

Research in Artificial Intelligence Assisted Physical Layer Design

The baseband physical layers for wireless communications are designed with robust and efficient digital signal processing algorithms. In general, the algorithms are optimal for a given block in the system chain. Our plan is to replace a number of communication blocks with deep neural networks, train the networks with practical datasets, observe the end-to-end performance, and further optimize the system behavior. Furthermore, we aim at reducing the real-time computational complexity of the physical layer design.

Research in UAV Assisted Communications

UAVs, or drones, being increasingly popular among researchers, engineers, and hobbyists, have found a widespread and versatile new set of applications in different fields of engineering. The United States Federal Aviation Administration (FAA) forecasts that the number of commercial fleet of drones will be more than 450,000, whereas the number of units of personal and hobbyist drones will exceed 2.4 million by 2022. The UAV system infrastructure strongly depends on the communications between two UAVs and between a UAV and a ground station. Recently, UAVs have been envisioned by third generation partnership project (3GPP) to be adopted in cellular communication systems for 5G or beyond 5G systems to provide an ad-hoc coverage to ensure the seamless or urgent communications. Currently, we are working on wireless channel modeling for air-to-air and air-to-ground communication links and implementing different routing protocols for UAV network.

Research in Advanced Signal Processing for 5G NR

5G new radio (NR) standardized the use of millimeter wave (mmW) electromagnetic spectrum for carrier waves. Therefore, some of the existing signal processing techniques are required to be revisited. For instance, in order to encounter the high transmission path loss, massive multiple input multiple output (MIMO) has been envisioned to be exploited at the cellular base station. Channel state information (CSI) is required to obtain for accurate beamforming and beamcombining codebook design to compensate severe free-space path loss for mmW propagation. Our focus is to develop advanced signal processing tools for channel estimation and parameter calculations for mmW and massive MIMO systems.

Research in Energy Harvesting Communications

EH nodes harvest renewable energies from their surrounding environment to carry out their functions. Energy can be harvested using solar, thermoelectric, and motion effects, or through other physical phenomena. EH nodes can be regarded as a promising option for deployment as they ensure a long system lifetime without the need for periodic battery replacements. In EH systems, energy is harvested at random times and in random amounts. A potential application area of EH nodes in massive Internet-of-Things (mIoT) for 5G. Randomness in incoming renewable energy along with physical (form-factor) constraints and limited computational resources of IoT nodes make the design problems for 5G mIoT network highly challenging. We solve resource allocation and dynamic control problems for EH nodes for different practical use-cases.

Academics

Academics

EECE 460: Wireless Communications (Spring 2021)

Related Articles

Selected Journal Publications

I. Ahmed, M. S. Alam, M. J. Hossain, and G. Kaddoum, “Deep Learning for MMSE Estimation of a Gaussian Source in the Presence of Bursty Impulsive Noise,” IEEE Commun. Letters, doi: 10.1109/LCOMM.2020.3045665, 2020M. S. Alam, H. Yanikomeroglu, I. Ahmed, and G. Kaddoum, “Bursty Impulsive Noise Mitigation in NOMA: AMAP Receiver-based Approach,” submitted in IEEE Commun. Letters, 2020C. Pu, I. Ahmed, E. Allen, and K. K. R. Choo, “SPA: Stochastic Packet Forwarding Algorithm in Flying Ad Hoc Networks,” submitted in IEEE/ACM Transactions on Networking, 2020I. Ahmed, I. Ahmed, and M. J. Hossain, “Optimal Stochastic Power Allocation and Relay Selection for Energy Harvesting Systems”, IEEE Wireless Commun. Letters, vol. 6, no. 4, pp. 546-549, Aug. 2017O. Alhussein, I. Ahmed, J. Liang, and S. Muhaidat, “Unified Analysis of Diversity Reception in the Presence of Impulsive Noise”, IEEE Trans. on Vehicular Tech. vol. 66, no. 2, pp. 1408-1417, Feb. 2017L. Mohjazi, I. Ahmed, and S. Muhaidat, “Downlink Beamforming in Multi-User MISO Systems for RF-powered Cognitive Radio Networks ”, IEEE Wireless Communications Letter vol. 21, no. 2, pp. 434-437, Feb. 2017I. Ahmed, K. T. Phan, and T. Le-Ngoc, “Optimal Stochastic Power Control for Energy Harvesting Systems with Delay Constraints”, IEEE J. Sel. Areas Commun., vol. 34, pp. 3512-3527, Dec. 2016I. Ahmed, A. Ikhlef, R. Schober, and R. K. Mallik, “Power Allocation for Conventional and Buffer-Aided Link Adaptive Relaying Systems with Energy Harvesting Nodes,” IEEE Trans. on Wireless Commun., vol.13, pp. 1182-1195, Mar. 2014I. Ahmed, A. Ikhlef, D. W. K. Ng, and R. Schober, “Power Allocation for a Hybrid Energy Harvesting Transmitter,” IEEE Trans. on Wireless Commun., vol. 12, pp. 6255–6267, Dec. 2013I. Ahmed, A. Ikhlef, R. Schober, and R. K. Mallik, “Joint Power Allocation and Relay Selection in Energy Harvesting AF Relay Systems,” IEEE Wireless Commun. Letters., vol. 2, pp. 239–242, Apr. 2013I. Ahmed, A. Nasri, D. S. Michalopoulos, R. Schober, and R. K. Mallik, “Relay Subset Selection and Fair Power Allocation for Best and Partial Relay Selection in Generic Noise and Interference,” IEEE Trans. on Wireless Commun., vol. 11, pp. 1828–1839, May 2012I. Ahmed, A. Nasri, R. Schober, and R. K. Mallik, “Asymptotic Performance of Generalized Selection Combining in Generic Noise and Fading,” IEEE Trans. on Commun., vol. 60, pp. 916–922, May 2012

Selected Conference Publications

I. Ahmed, W. Xu, R. Annavajjala, and W. S. Yoo, “Joint Demodulation and Decoding with Multi-Label Classification Using Deep Neural Networks,” submitted in IEEE ICAIIC, 2021, Jeju Island, Korea.I. Ahmed and R. Annavajjala, “Bayesian CRLB for Joint AoA, AoD, and Channel Estimation Using UPA in Millimeter-wave Communications,” Proc. of IEEE VTC Spring, 2020, Antwerp, Belgium.I. Ahmed and E. Allen, “Diversity Combining with Deep Neural Network for Generic Noise and Interference,” Proc. of IEEE VTC Spring, 2020, Antwerp, Belgium.I. Ahmed, I. Ahmed, M. J. Hossain, and S. Sadeque, “Performance Analysis of Dual-hop Relay Systems for Generalized Fading Channels and Energy Harvesting Nodes,” Proc. of IEEE WiSEE, 2019I. Ahmed, K. T. Phan, and T. Le-Ngoc, “Stochastic User Scheduling and Power Control for Energy Harvesting Networks with Statistical Delay Provisiong,” Proc. of IEEE PIMRC, 2015, Hong Kong.I. Ahmed, K. T. Phan, and T. Le-Ngoc, “Optimal Stochastic Power Control for Energy Harvesting Systems with Statistical Delay Constraint,” Proc. of IEEE Globecom, 2015, San Diego, USA.I. Ahmed, M. J. Hossain, and I. Ahmed, “Resource Allocation for Decode–and–Forward Relayed System with Interference Aided Energy Harvesting,” Proc. of IEEE ICUWB, 2015, Montreal, Canada.I. Ahmed, A. Ikhlef, D. W. K. Ng, and R. Schober, “Power Allocation for a Hybrid Energy Harvesting Relay System with Imperfect Channel and Energy State Information,” Proc. of IEEE WCNC, 2014, Istanbul, Turkey.I. Ahmed, A. Ikhlef, D. W. K. Ng, and R. Schober, “Optimal Resource Allocation for Energy Harvesting Two-way Relay Systems with Channel Uncertainty,” Proc. of IEEE GlobalSIP, 2013, Austin, Texas, USA.I. Ahmed, A. Ikhlef, D. W. K. Ng, and R. Schober, “Optimal Power Allocation for a Hybrid Energy Harvesting Transmitter,” Proc. of IEEE ICC, June 2013, Hungary, Budapest.I. Ahmed, A. Ikhlef, R. Schober, and R. K. Mallik, “Power Allocation in Energy Harvesting Relay Systems,” Proc. of IEEE VTC, 2012, Yokohama, Japan.I. Ahmed, A. Nasri, D. S. Michalopoulos, R. Schober, and R. K. Mallik, “Performance Analysis and Power Allocation of AF Best Relay Selection in Generic Noise,” Proc. of IEEE WCNC, 2012, Paris, France.I. Ahmed, R. Schober, and R. K. Mallik, “Asymptotic Performance of Lp-Norm MIMO Detection,” Proc. of IEEE VTC, 2010, Ottawa, Canada.