Speakers

Speakers

ICTASI 2021 SPEAKER

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Engr Dr Adnan Ahmed Khan

National University of Sciences and Technology, Pakistan


Speech Title: Novel Symbol Detection Techniques in a Multi-Antenna 5G and Beyond Communications System

Speech Abstract: Significant performance gains are achievable in wireless communication systems using a Multi-Input Multi-Output (MIMO) communications system employing multiple antennas, being used in 5G and beyond Mobile Cellular Systems. This architecture is suitable for higher data rate multimedia reliable communications. One of the challenges in building a MIMO and Massive MIMO communications system is the tremendous processing power required at the receiver side. MIMO Symbol detection involves detecting symbol from a complex signal at the receiver and this symbol detection problem becomes even more complex in a massive MIMO system. The existing MIMO detection techniques can be broadly divided into linear, non-linear and exact detection methods. Linear methods like Zero-Forcing offer low complexity with degraded Bit Error Rate (BER) performance as compared to non-linear methods like VBLAST. Non-linear detectors are computational not very expansive with acceptable performance. Exact solutions like Sphere Decoder provide optimal performance however do suffer from exponential complexity under certain conditions. Computational Swarm Intelligence based Meta-heuristics can be applied for Symbol detection in a MIMO and Massive MIMO system with acceptable performance as compared to classical techniques. This approach is particularly attractive as Swarm Intelligence (SI) is well suited for physically realizable, real-time applications, where low complexity and fast convergence is of absolute importance. Application of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms has shown promise in this regards. While an optimal Maximum Likelihood (ML) detection using an exhaustive search method is prohibitively complex, we present that the Swarm Intelligence optimized MIMO detection algorithms gives near-optimal Bit Error Rate (BER) performance in fewer iterations, thereby reducing the ML computational complexity significantly. Therefore, novel non-conventional MIMO detection approaches based on Swarm-Intelligence techniques provides an alternative symbol detection technique that possess significant application in 5G and beyond Cellular Systems. The results of above work have already been published in several renowned journals and conference proceedings.

A brief introduction to Dr Adnan Ahmed Khan:  

Dr. Adnan Ahmed Khan graduated as a Telecommunications Engineer in 1993 from the College of Telecommunications Engineering, University of Engineering and Technology, Lahore, Pakistan. Completed MS and PhD in Computer Engineering from the Centre of Advanced Studies in Engineering (CASE) Islamabad, University of Engineering and Technology (UET), Taxila, Pakistan in 2005 and 2009, respectively.

Dr. Khan is Higher Education Commission (HEC), Pakistan’s approved PhD Supervisor. Possesses more than 20 years experience in Telecommunications Industry and along with 12 years research and teaching experience in Advanced Wireless Systems in leading Universities of Pakistan. Qualified CDMA, Long Term Evolution (LTE), High Speed Packet Data Access (HSPA), Universal Mobile Universal Mobile Telecommunications Standard (UMTS)/ Wideband Code Division Multiple Access (WCDMA) and WiMax Trainings by QUALCOMM, USA. Qualified in Advanced Networks courses from China. 

His research interests include Massive Multi-Input Multi-Output (MIMO) based 5G Wireless Communications Systems, , Software Defined Radios (SDR), Multi User and Massive MIMO, Cognitive and Cooperative Communications System, Satellite Communication systems, etc. In addition, recent interests include application of Artificial Intelligence Have completed several funded projects including Advanced Wireless Systems test-bed based on MIMO-OFDM systems for LTE systems. Conducted several professional trainings on Advanced Technology attended by several hundred participants. Several funded projects have been completed in the domain of wireless system. A recent proposal of Artificial Intelligence related project amounting US$ 36M is being perused currently. 

Dr. Khan, has 65 International Publications including IEEE/ ACM Conferences including 12 ISI Indexed IF Journals. One book on Advanced Wireless Systems and one Chapter (Swarm Intelligence Based MIMO Detection Techniques in Wireless Systems) in IET Book Swarm Intelligence - From Concepts to Applications (eBook: 978-1-78561-314-2) (IET, UK). 



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Dr. Farooq Ahmad

Director IntelliFAB Lab

HOD, Department of Biomedical Engineering  (NWL)

Faculty of Electrical Engineering 

University of Engineering and Technology Lahore. 

Punjab, Pakistan.


Speech Title: to be updated

Speech Abstract: to be updated


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Prof.Jiri Matas

Center for Machine Perception

Czech Technical University in Prague

Czech Republic


Speech Title: to be updated

Speech Abstract: to be updated

A brief introduction to Prof.Jiri Matas: 

Jiri Matas is a full professor at the Center for Machine Perception, Czech Technical University in Prague. He holds a PhD degree from the University of Surrey, UK (1995). He has published more than 250 papers in refereed journals and conferences. His publications have about 45000 citations registered in Google Scholar and 20000 in the Web of Science. His h-index is 80 (Google scholar) and 54 (Clarivate Analytics Web of Science) respectively.

He received the best paper prize e.g. at the British Machine Vision Conferences in 2002 and 2005, at the Asian Conference on Computer Vision in 2007 and at Int. Conf. on Document analysis and Recognition in 2015.

 J. Matas has served in various roles at major international computer vision conferences (e.g. ICCV, CVPR, ICPR, NIPS, ECCV), co-chairing ECCV 2004, 2016, 2022 and CVPR 2007 and 2022. He is an Editor-in-Chief of IJCV and was the Associate Editor-in-Chief of IEEE T. PAMI. He served on the computer science panel of ERC.

His research interests include visual tracking, object recognition, image matching and retrieval, sequential pattern recognition, and RANSAC- type optimization metods. He has co-founded two companies, Eyedea Recognition (computer vision) and Locksley (combinatorial optimization) 







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