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Assistant Professor


Education : Ph.D. (IISc Bangalore)

Dr. Priyanka Das received the Ph.D. degree in Electrical Communication Engineering from the Indian Institute of Science, Bangalore, India in 2018. She obtained the M.Tech. degree in Digital Signal Processing from the Indian Institute of Technology, Guwahati, India in 2011, and the B.Tech. degree in Radio Physics and Electronics from the University of Calcutta, West Bengal, India in 2009. She also received the B.Sc. degree in Physics Hons. from the University of Burdwan, West Bengal, India in 2006. She worked in Nokia Solutions Networks, Bangalore, India as a summer intern in 2015. She worked in Dell Research and Development, Bangalore, India as a software associate engineer from 2011 to 2012. Presently, she is an Assistant Professor at IIIT Bangalore, India. Her primary research interest broadly lies at the intersection of probability theory, optimization, and wireless communication, where she seeks to develop new analytical tools for understanding and enhancing the spectral and energy efficiency of next generation wireless communication systems.  


Welcome to my webpage! Our research work focuses on performance analysis and design of next generation cellular mobile radio systems such as machine learning for wireless communication systems, spectrum sharing networks, physical layer security, Intelligent reflecting surfaces (IRS) for 6G, cooperative communications, and multiple antenna systems. "Highly motivated students who are interested in pursuing PhD, Master of Science (Research), and undergraduate project in cutting-edge and challenging research problems in wireless communications may email to priyanka.das@iiitb.ac.in."

To get more details about our reaserch area, click on lab page https://www.iiitb.ac.in/labs/advanced-wireless-communications-lab/about-us-2

Please see brief description of our research areas below:

  • Physical-Layer Security (PLS): Wireless networks have become pervasive in order to guarantee global digital connectivity. Multiuser multiple-input multiple-output wireless techniques meet this demand by achieving high spectral efficiency. Security is also regarded as critical in wireless multiuser networks because users rely on these networks to transmit sensitive data. Because of the broadcast nature of the physical medium, wireless communication is very susceptible to eavesdropping, and it is essential to protect transmitted information. Wireless communications have traditionally been secured by network layer key-based cryptography. However, in large, dynamic wireless networks, classical cryptography might not be suitable. Classical cryptography tends to cause problems in terms of key distribution and management and computational complexity. Recently, methods have been proposed to provide an additional level of protection and to achieve almost perfect secrecy without encryption keys. These methods, collectively referred to as physical layer security, exploit the randomness inherent in noisy channels. It is considered to be a critical part for public safety, IoT, commercial use cases and beyond. Our research in this area has focused on how confidentiality and integrity can be maintained without decreasing the user’s experience? We investigate on developing physical–layer techniques for security enhancement and analyze performance metrics such as secrecy outage probability, secrecy throughput, and secrecy-reliability tradeoffs.   
    • Member: Pradyumna Hegade, Rajalakshmy G


  • Antenna Selection for MIMO Spectrum-Sharing Networks: Due to an ever-increasing demand on wireless communications and limited spectrum resources in the sub-6 GHz bands, spectrum sharing is being developed as a key solution to alleviate the spectrum scarcity problem. It has been considered in standards such as 5G NR unlicensed and upcoming IEEE 802.11be. The spectral efficiency and reliability of communications of the underlay secondary users in underlay CR can substantially be improved through the extra degrees of freedom available with multiple antenna systems. However, the performance gain comes at the cost of increased hardware complexity at the radio front end because each antenna element requires an expensive radio frequency chain to process the signal to or from the antenna. Antenna selection can be used to reduce this complexity while retaining much of the benefits of multiple antennas. For these reasons, antenna selection has been incorporated in LTE and IEEE 802.11n, and is also a promising solution to improve the error performance of the interference-constrained underlay spectrum sharing networks.
    • Member: Prathyusha Appalla and Pradyumna Hegade


  • Cooperative Relay Networks: Cooperative relay transmission, which has been considered an enabling technology in the LTE Release 16 and beyond is an attractive, practicable solution to improve the coverage extension and reliability of the wireless networks. In a relay-based cooperative wireless network, one or more relays forward a message from the source to the destination. Ideally, having more relays to forward a message helps improve performance. However, this is practically difficult since tight symbol-level synchronization needs to be ensured at all the separated relays. Selection is a solution that solves this problem. In selection, depending on the current channel realizations, only the best relay, which is the one that has the most favourable channel realization, is selected to forward the message. Selection circumvents the synchronization problem since only the selected node transmits. Yet, despite its simplicity, it achieves the highest diversity order - as was also the case with antenna selection.
    • Member: Prathyusha Appalla and Pradyumna Hegade


  • Joint antenna and relay selection for MIMO Spectrum-Sharing: Considering multiple relay-assisted MIMO underlay spectrum-sharing network, we investigate on antenna selection and cooperative relay selection jointly to improve the performance of the secondary network. Our research has mainly focused on developing joint optimal antenna and relay selection policy in order to maximize the SINR or to minimize the symbol error rate (SER) at the secondary destination (D). We employ either maximum-ratio combining (MRC) or selection combining (SC) strategy while receiving, and control the transmit powers of the secondary source (S) and relays to satisfy suitable interference constraint for the primary network. It is through training that the receiver estimates the channel gains of the various antennas and relays, and determines which antenna/relay has to select. The inevitable presence of noise during the estimation process and the time-varying nature of the wireless channel can lead to inaccurate selection and incorrect data decoding, both of which together increase the overall SER and outage probability observed in the secondary system.
    • Member: Prathyusha Appalla, Aditya Savaliya


  • Intelligent Reflecting Surface (IRS): Spectral efficiency and energy efficiency are becoming two essential criteria for designing cost-effective, sustainable, and green 6G wireless networks. The recent advent of intelligent reflecting surfaces (IRS) enables network operators to control the propagation environment itself. It creates line of sight link by smart reflection to bypass obstacle. A new hybrid network with an active base station and passive IRS can enhance signal power at cell edge or hot spot, and boost network capacity without additional energy consumption.  We mostly focus on developing optimization algorithms to jointly control the transmit power at the base station and the phase shifts of the reflecting units at the IRS for various scenarios. We further focus on robust channel estimation algorithm design for IRS-aided communication systems. The research outcomes will provide a low cost alternative for energy-inefficient ultra-dense network and massive MIMO, and thus, can also be applied in enhanced Mobile Broadband (eMBB)-plus feature of 6G to provide a high-quality experience in dense population areas, e.g., airport, stadium, and shopping mall.   
    • Member: Sumukha Kashyap and Agrim Agarwal


  • Machine Learning for Channel Estimation in Millimeter Wave (mmWave) Communications: The fifth-generation (5G) of cellular networks and beyond requires massive connectivity, high data rates, and low latency. Millimeter-wave (mmWave) communications is a key 5G enabling technology to meet these requirements thanks to its technical potentials that can be integrated with other 5G enablers such as ultra-dense networks (UDNs) and massive multiple-input-multiple-output (massive MIMO) systems. Obtaining accurate channel state information (CSI) is essential to ensure the benefits of the mmWave massive MIMO systems. Our research mainly focuses on understanding the state-of-the-art channel estimation techniques in this area. Then, we aim to apply deep-learning-based methods keeping in mind that the huge number of antennas at the BS will lead to overwhelming feedback overhead.
    • Member: Looking for potential PhD/MSR candidate



  • [Nov 2023] Our paper on "TSDSI Standards Driven Implementation of Smart Radio Environment," accepted in IEEE ANTS 2023
  • [Sept 2023] Our paper on "Binary Power Control and Passive Beamforming for RIS-Assisted Spectrum Sharing Network," accepted in IEEE Global Communications Conference (GLOBECOM) Workshop, Malaysia, 2023
  • [June 2022] Our paper on ``Secrecy Performance with Optimal Relay and Antenna Selection in Spectrum-Sharing Networks,’’ accepted for publication in IEEE International Conference on Signal Processing and Communications (SPCOM), IISc, India
  • [June 2022] Our paper on ``Outage Performance of Optimal Relay and Antenna Selection Schemes with TAS/MRC and TAS/SC for Spectrum-Sharing Network under Imperfect CSI,’’ accepted for publication in IEEE International Conference on Signal Processing and Communications (SPCOM), IISc, India

  • [May 2022] Organised a workshop "Intelligent Reflecting Surfaces: Fundamentals and Applications". The Workshop received 250+ registrations. [Link]

  • [March 2022] Our paper on ``Secrecy-Aware Relay and Antenna Selection for MIMO Wiretap Spectrum-Sharing Network,’’ accepted for publication in IEEE Vehicular Technology Conference: VTC2022-Spring, in Hensinki, Jun. 2022.

Google Scholar                  Research Gate


Peer-Reviewed Journal Papers

  • P. Das and N. B. Mehta, ``Rate-optimal relay selection for average interference-constrained underlay CR,’’ IEEE Trans. Commun., vol. 65, no. 12, pp. 5137-5148, Dec. 2017 

  • P. Das, N. B. Mehta, and G. Singh, ``Novel relay selection rules for average interference-constrained cognitive AF relay networks,’’ IEEE Trans. Wireless Commun., vol. 14, no. 8, pp. 4304-4315, Aug. 2015.

  • P. Das and N. B. Mehta, ``Direct link-aware optimal relay selection and a low feedback variant for underlay CR,’’ IEEE Trans. Commun., vol. 63, no. 6, pp. 2044-2055, Jun. 2015.

  • P. Das, K. Karthik, and B. C. Garai, ``A robust alignment-free fingerprint hashing algorithm based on minimum distance graphs,’’ Elsevier J. Pattern Recognition, vol. 45, no. 9, pp. 3373-3388, Sep. 2012.

  • B. C. Garai, P. Das, and A. K. Mishra, ``Group delay reduction in FIR digital filters,’’ Elsevier J. Signal Process., vol. 91, no. 8, pp. 1812-1825, Aug. 2011


Peer-Reviewed Conference Papers

  • P. Das, S. Kashyap, R. Sarvendranath, and A. Mishra, "Binary Power Control and Passive Beamforming for RIS-Assisted Spectrum Sharing Network", in IEEE Global Communications Conference (GLOBECOM) Workshop, Malaysia, 2023.
  • A. Srivastava et al, "TSDSI Standards Driven Implementation of Smart Radio Environment'" in IEEE ANTS 2023.
  • A. Agarwal, A. Mishra, and P. Das, ``Sparse Bayesian Learning-Based Channel Estimation for IRS-Aided Millimeter Wave Massive MIMO Systems,’’ in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, Canada, Sep. 2023.
  • P. Das and P. Hegade, ``Secrecy Performance with Optimal Relay and Antenna Selection in Spectrum-Sharing Networks,’’ accepted for publication in IEEE International Conference on Signal Processing and Communications (SPCOM), in IISc, India, Jul. 2022.

  • A. L. Prathyusha and P. Das, ``Outage Performance of Optimal Relay and Antenna Selection Schemes with TAS/MRC and TAS/SC for Spectrum-Sharing Network under Imperfect CSI,’’ accepted for publication in IEEE International Conference on Signal Processing and Communications (SPCOM), in IISc, India, Jul. 2022.

  • P. Das and P. Hegade, ``Secrecy-Aware Relay and Antenna Selection for MIMO Wiretap Spectrum-Sharing Network,’’ accepted for publication in IEEE Vehicular Technology Conference: VTC2022-Spring, in Hensinki, Jun. 2022.

  • P. Das and R. Sarvendranath, ``Optimal Relay and Antenna Selection in MIMO Cognitive Relay Network with Imperfect CSI," in IEEE Wireless Communications and Networking Conference (WCNC), Seoul, Korea (South), Jun. 2020.

  • P. Das, ``Outage Performance of Cognitive Relay Networks with Optimal Relay and Antenna Selection," in IEEE National Conference on Communication (NCC), Kharagpur, India, Apr. 2020.

  • P. Das, ``Average Rate of Optimal Incremental Relaying with Selection: Analysis and Insights," in IEEE National Conference on Communication (NCC), Kharagpur, India, Apr. 2020.

  • P. Das, N. B. Mehta, and P. N. Arya, ``Cognitive relay selection with incomplete channel state information of interference links,’’ in IEEE International Conference on Communications (ICC), Paris, May 2017.

  • P. Das and N. B. Mehta, ``Revisiting incremental relaying and relay selection for underlay cognitive radio,’’ in IEEE Global Communications Conference (GLOBECOM), San Diego, Dec. 2015.

  • P. Das and N. B. Mehta, ``Direct link-aware optimal relay selection and a low feedback variant for underlay CR,’’ in IEEE International Conference on Communications (ICC), London, Jun. 2015.

  • P. Das, K. Karthik, and B. C. Garai, ``An efficient hybrid fingerprint matching algorithm,’’ in Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), Hubli, Karnataka, Dec. 2011.

  • B. C. Garai, P. Das, and S. Rajaraajeswari, ``Improving the fingerprint matching accuracy by using both phase-correlation and minutiae based features," in International Conference on Cloud Computing and Service Engineering, Bangalore, Apr. 2012.

EC-303: Principle of Communication Systems 

  • Aim of the course: Communication systems are basic workhorses behind the information age. This course aims to introduce the underlying principles behind the design and analysis of communication systems. The labs will be conducted using Matlab and FM radio experiments will be conducted using Raspberry Pi.
  •  Course overview: Key components of the communication system designer’s toolbox are mathematical modeling and signal processing. Beginning with various basic tools such as Fourier Series/Transform and complex baseband representations of passband signals, the course will cover several important analog communication techniques for Amplitude Modulation, Frequency Modulation, and Phase Modulation. It will also cover superhet receiver and the core concept of phase-locked loop (PLL) and its applications in system design. The later part of the course is focused on digital modulation techniques such as ASK, QAM, PSK, and orthogonal modulation. Nyquist criterion for avoiding intersymbol interference will also be dealt with in the course.  Thereafter, the course will cover review of probability, random variables, and random processes with the application in noise modelling. These techniques will then be used in analyzing digital communication performance metric such as bit error probability.
  • Prerequisite: Signals and Systems
  • Reference book: Upamanyu Madhow, “Introduction to Communication Systems”, Cambridge University Press


EC-306: Digital Communication 

  • Course Overview: This course is a sequel to Principles of Communication Systems (EC-303) course and covers fundamental concepts of modern digital communication systems. The mathematical background necessary to understand communication theory often intimidates the undergraduate students. The purpose of this course is to provide such a lecture style exposition to provide an accessible, yet rigorous, introduction to the subject of digital communication with its practical applications. Beginning with Nyquist sampling theorem, pulse code modulation, and delta modulation, the course will introduce the foundation of information theory, source coding, and source compression algorithms. It will cover several channel coding schemes such as linear block codes, cyclic codes, and convolution code in detail. The later part of the course is focused on optimal receiver design for additive white Gaussian noise (AWGN) channels and their error rate performance considering digital modulation techniques such as Binary Phase Shift Keying (BPSK), Frequency Shift Keying (FSK), Quadrature Amplitude Modulation (QAM), M-ary Phase Shift Keying (MPSK). Spread-spectrum techniques will be dealt with in the course with focus on its anti-jamming property. Finally, the course will treat communication through fading channels, including the characterization of fading channels and the key important parameters: path loss, shadowing, multipath effect, coherence time, coherence bandwidth, and Doppler spread. Link budget analyses for wireline and radio communication systems will also be treated.
  • Prerequisite: Principles of communication systems (EC-303)
  • Reference books:

 1Bernard Sklar and Pabitra Kumar Ray, “Digital Communication”, Pearson Education

 2. Simon Haykin, “Digital communication systems”, Wiley Edition


NC-827: Wireless Communication

  • Course Overview: The course is designed to help students get an in-depth grasp of the fundamentals of wireless technologies, and gain a better understanding of modern 5G wireless communication systems from physical layer perspective, and its extension towards 6G. While the potential benefits of such technologies are promising, there are numerous challenges in the design and implementation of such wireless systems. The course will address the following topics: wireless channel modeling, fading and its countermeasures, diversity techniques, channel coding schemes, orthogonal frequency division multiplexing (OFDM), space-time coding, and MIMO systems.  This will also lay the foundation for advanced wireless communication techniques such as Cooperative Communication, Massive MIMO, and Millimeter Wave Communication. Finally, students are expected to prepare a mini project that will focus on an in-depth study and analysis of any cutting-edge wireless technology of their choice.
  • Prerequisite:
    • Digital Communication (EC-306)
    • Basics of Probability and Random Variables
  • Reference books:
  1. David Tse and P. Viswanath, “Fundamentals of Wireless Communication”, Cambridge University Press
  2. Andrea Goldsmith, “Wireless Communication”, Cambridge University Press
  3. Aditya K. Jagannatham, “Principles of Modern Wireless Communications Systems: Theory and Practice”, Mc Graw Hill Education


AI-512: Math for Machine Learning 

  • Course Overview: This course intends to provide the advanced mathematics background essential for Machine Learning and other advanced courses, and can be viewed as a combination of three main topics: Advanced Linear Algebra, Convex optimization, and Advanced Probability. This course is an essential prerequisite to advanced Machine Learning theory and practice, including domain specific areas such as networking and communication, visual-recognition, automatic speech recognition, and natural language processing.
  •  Prerequisite: Basics of mathematics and probability theory
  • Reference books:
  1. Kevin Murphy, “Machine Learning A Probabilistic Perspective”, The MIT Press, 2012
  2. John E Hopcroft and Ravindran Kannan, “Foundations of Data Science”, 2013

CS/NC 297E: Special Topics - Detection and Estimation Theory 

Course Overview:

In many electronic signal processing systems are designed to decide when an event of interest occurs and then extract more information about that event. Detection and Estimation theory can be found at the core of those systems. Some typical applications involving the use of the detection and the estimation theory principles include: Radar Systems, Communication Systems, Image Processing and Pattern Recognition. In detection theory, we first describe different types of detection criteria using hypothesis testing framework. It is followed by brief introduction to non-parametric detection methods. Finally, we describe a detection of deterministic and random signals in white Gaussian noise. In estimation theory, we begin with classical estimation methods which include: minimum variance unbiased estimator (MVUE), best linear unbiased estimator (BLUE), maximum likelihood estimator (MLE) and least squares estimator (LSE). It is followed by Cramer-Rao bound and the Bayesian estimation methods.


Basics of probability theory and signal and systems

Reference books:
  • Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory, S.M. Kay, Prentice Hall 1993
  • Fundamentals of Statistical Signal Processing, Volume II: Detection Theory, S.M. Kay, Prentice 1993
  • An Introduction to Signal Detection and Estimation, H.V. Poor, Springer, 2nd edition, 1998


  1. CoPrincipal Investigator: Priyanka Das, IIITB: July 2020 to July 2025
    • Title: Advanced Communication System
    • PI: Prof. Jyotsna Bapat
    • Sponsored by: Department of Science and Technology (DST), Govt. of India, Under National Mission on Interoperable Cyber Physical System (NM-ICPS)
  2. ​Principal Investigator (PI): Priyanka Das, IIITB: June 2021 to July 2024
    • Title: Modeling, Optimization, and Channel Estimation of Intelligent Reflecting Surface (IRS)-Assisted Underlay Spectrum Sharing for 6G
    • CoPI: Dr. Amrita Mishra
    • Sponsored by: Science and Engineering Research Board (SERB)-POWER Research Grant, Govt. of India
  3. Principal Investigator (PI): Priyanka Das, IIITB: June 2019 to July 2021
    1. Title: Joint Antenna and Path Selection for Multi-Relay Cooperative Communication Systems for 5G
    2. Sponsored by: IIITB start up research grant


Open Project Staff Position:

We are looking for expert and highly self-motivated machine learning algorithm developer with a good understanding of wireless technology used in innovative 6G wireless networks. To apply for this, please send your current resume to priyanka.das@iiitb.ac.in

Name of the position: Junior Research Fellow (JRF)  or Senior Research Fellow (SRF)

Key Qualifications: M.E/M.Tech./PhD in ECE/EE/CSE or Equivalent

  • Knowledge in Algorithms, Optimization, Probability, Statistics, Signal processing, Wireless Communications
  • Working experience in one or more of the following research directions in Neural Networks: Deep Reinforcement Learning, Federated Learning, Online Learning etc.
  • Basic knowledge of communication system theory and wireless systems, understanding of the practical challenges of applying Machine Learning to wireless communications
  • Programming experience in C, C++, Python, MATLAB
  • Demonstrate clarity of thought and strong analytical and problem-solving skills

Location/Duration: IIITB, India / 03 years (for interns – max. 12 months)

I am looking for motivated students interested in working on state-of-the-art problems in 5G and next-generation wireless communications systems. Please send me an email with your resume, if interested. Please see Research/Publications/Cunsultency tabs for more details.

Research Collaborators and Co-authors

  1. Prof. Neelesh B. Mehta, IISc Bangalore [Link]

  2. Prof. Amit Mishra, University of Cape Town [Link]

  3. Dr. Kannan Karthik, Associate Professor, IIT Guwahati [Link]

  4. Dr. Sarvendranath Rimalapudi, Assistant Professor, IIT Guwahati [Link]

  5. Dr. Amrita Mishra, Assistant Professor, IIIT Bangalore [Link]



  • July 2012 - June 2018, Ph.D in Dept. of ECE, Indian Institute of Science (IISc), Bangalore (CPI: 6.7/8)

  • July 2009 - June 2011, M.Tech. in Digital Signal Processing, Dept. of EEE, IIT Guwahati (CPI: 9.3/10)

  • July 2006 - June 2009, B.Tech. in Radio Physics and Electronics, University of Calcutta, West Bengal (CPI: 9.2/10)

  • July 2003 -  June 2006, B.Sc. in Physics (Hons.), Dept. of Physics, University of Burdwan, West Bengal (Percentage: 75.75%, University Rank - 1)



  • July 2019 - Present, Assistant Professor, IIIT Bangalore, India.

  • June 2015 - Sept. 2015, Internship in Nokia Solutions and Networks Bangalore, India.

  • Aug. 2011 - July 2012, Software Associate Engineet, DELL R&D bangalore, India



Served as a reviewer for the following journals:

  • IEEE Transaction on Wireless Communications (TWC)

  • IEEE Transaction on Vehicular Technology (TVT)

  • IEEE Wireless Communications Letters (WCL)

  • Sadhana - Academy Proceedings in Engineering Science

  • IET Communication

 Served as a reviewer for the following conferences:

  • National Conference on Communications (NCC)

  •  Signal Processing and Communications (SPCOM)

  •  IEEE Wireless Communications and Networking Conference (WCNC)


Technical Talks

  • Talk on " Joint Optimal Relay and Antenna Selection for Cooperative Cognitive Radio Networks " in Samvaad-2020, IIIT Bangalore [Link

  • Talk on “Impact of Channel State Information Uncertainty on the Performance of Cooperative Cognitive Radio Networks” in Samvaad-2019, IIIT Bangalore [Link

  • University Gold Medalist in B.Sc. Physics Hons, University of Burdwan, West Bengal, 2003-2006