Mahnoor Anjum

UNSW, Sydney.

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Level 4, Electrical Engineering Building (G17),

University of New South Wales,

Sydney, NSW 2033

Mahnoor Anjum (Student Member, IEEE) is pursuing her Ph.D. in Electrical Engineering at the University of New South Wales, Sydney, Australia. She received her BS and MS in Electrical Engineering from the National University of Sciences and Technology, Pakistan, in 2019 and 2022, respectively. She has also been a Visiting Researcher at Kyung Hee University, South Korea. Her research interests include integrated sensing and communication systems, massive MIMO, internet-of-things, and artificial intelligence for wireless systems.

She was awarded the IEEE GLOBECOM WKSHPS best paper award in 2023, and received the exemplary reviewer award for IEEE Wireless Communications Letters in 2024. She was also awarded the Development and Research Training Grant from UNSW, Sydney in 2025. She has served as a technical program committee member for flagship conferences such as IEEE VTC and IEEE ICC, and published in reputed conferences and journals, including IEEE Transactions on Green Communications and Networking, IEEE Internet of Things Magazine, Elsevier Computer Communications, MDPI Energies, IEEE ICC, IEEE GLOBECOM, IEEE VTC, and IEEE SPAWC.

news

Jun 29, 2025 Paper titled “Green Transceiver Design and Antenna Selection for QoS-Aware Integrated Sensing and Communication Systems” accepted for publication in IEEE Transactions on Green Communications and Networking.
Jun 19, 2025 Paper titled “Energy-Efficient Near-Field Beamforming: A Review on Practical Channel Models” published in MDPI Energies.
Apr 22, 2025 Awarded the Development and Research Training Grant, amount $3000, from UNSW, Sydney, Australia.
Apr 22, 2025 Two papers accepted for presentation at the 2025 International Conference on Communications (IEEE ICC). Titles:
  • QoS-aware power minimization for fluid antennas assisted integrated sensing and communication
  • Green transceiver design for integrated sensing and backscatter communication with QoS demands
Apr 22, 2025 Paper titled “Service fairness enhancement for BDRIS assisted fluid antenna systems” accepted for presentation at the 2025 IEEE 101st Vehicular Technology Conference (IEEE VTC2025-Spring).

selected publications

  1. lora.png
    Analysis of time-weighted LoRa-based positioning using machine learning
    Mahnoor Anjum, Muhammad Abdullah Khan, Syed Ali Hassan, and 2 more authors
    Computer Communications, 2022
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    RSSI fingerprinting-based localization using machine learning in LoRa networks
    Mahnoor Anjum, Muhammad Abdullah Khan, Syed Ali Hassan, and 3 more authors
    IEEE Internet of Things Magazine, 2020