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ORCIDMuhammad Abdullah Khan
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2020 – today
- 2024
[j4]Muhammad Abdullah Khan, Eesha Adnan, Aena Rasheed, Amna Farrukh, Amna Amin Sethi:
Analysis of Penicillin Binding Sites for Determining Antibiotic Resistance in Pakistan. Int. J. Bioinform. Res. Appl. 20(3) (2024)- 2023
- [j3]Amna Amin Sethi, Amna Farrukh, Aena Rasheed, Eesha Adnan, Muhammad Abdullah Khan:
Analysis of penicillin binding sites for determining antibiotic resistance in Pakistan. Int. J. Bioinform. Res. Appl. 19(5/6): 402-411 (2023) - [c6]Mahnoor Anjum, Muhammad Abdullah Khan, Syed Ali Hassan, Haejoon Jung, Aamir Mahmood, Mikael Gidlund:
A Multi-Level ML-Based Optimization Framework for IIoT Networks with Distributed IRS Assisted UAVs. GLOBECOM (Workshops) 2023: 1338-1343 - [c5]Muhammad Abdullah Khan, Mahnoor Anjum, Syed Ali Hassan, Haejoon Jung:
Machine Learning-Based Resource Allocation for IRS-Aided UAV Networks. GLOBECOM 2023: 3051-3057 - [c4]Mahnoor Anjum, Muhammad Abdullah Khan, Sarah Basharat, Syed Ali Hassan, Haejoon Jung:
Dedicated versus Shared Element-Allotment in IRS-aided Wireless Systems: When to Use What? VTC2023-Spring 2023: 1-6 - 2022
- [j2]Mahnoor Anjum
, Muhammad Abdullah Khan, Syed Ali Hassan, Haejoon Jung, Kapal Dev:
Analysis of time-weighted LoRa-based positioning using machine learning. Comput. Commun. 193: 266-278 (2022) - 2020
- [j1]Mahnoor Anjum, Muhammad Abdullah Khan, Syed Ali Hassan, Aamir Mahmood, Hassaan Khaliq Qureshi, Mikael Gidlund:
RSSI Fingerprinting-Based Localization Using Machine Learning in LoRa Networks. IEEE Internet Things Mag. 3(4): 53-59 (2020) - [i1]Mahnoor Anjum, Muhammad Abdullah Khan, Syed Ali Hassan, Aamir Mahmood, Hassaan Khaliq Qureshi, Mikael Gidlund:
RSSI Fingerprinting-based Localization Using Machine Learning in LoRa Networks. CoRR abs/2006.01278 (2020)
2010 – 2019
- 2019
- [c3]Mahnoor Anjum, Muhammad Abdullah Khan, Syed Ali Hassan, Aamir Mahmood, Mikael Gidlund:
Analysis of RSSI Fingerprinting in LoRa Networks. IWCMC 2019: 1178-1183 - 2015
- [c2]Ahmed Farouk Aref, Renato Negra, Muhammad Abdullah Khan:
2.6 Class-0: A highly linear class of power amplifiers in 0.13μm CMOS for WCDMA/LTE applications. ISSCC 2015: 1-3 - [c1]Muhammad Abdullah Khan, Ahmed Farouk Aref, Muh-Dey Wei, Renato Negra:
Highly linear and reliable low band class-O RF power amplifier in 130 nm CMOS technology for 4G LTE applications. NORCAS 2015: 1-4
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