Shamik Sarkar

Orcid: 0000-0001-5083-8352

According to our database1, Shamik Sarkar authored at least 25 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
GAN-RXA: A Practical Scalable Solution to Receiver-Agnostic Transmitter Fingerprinting.
IEEE Trans. Cogn. Commun. Netw., April, 2024

2023
A Novel Software Defined Radio for Practical, Mobile Crowdsourced Spectrum Sensing.
IEEE Trans. Mob. Comput., March, 2023

AviSense: A Real-time System for Detection, Classification, and Analysis of Aviation Signals.
ACM Trans. Sens. Networks, February, 2023

Fingerprinting IoT Devices Using Latent Physical Side-Channels.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2023

RadYOLOLet: Radar Detection and Parameter Estimation Using YOLO and WaveLet.
CoRR, 2023

REM-U-net: Deep Learning Based Agile REM Prediction with Energy-Efficient Cell-Free Use Case.
CoRR, 2023

ProSpire: Proactive Spatial Prediction of Radio Environment Using Deep Learning.
Proceedings of the 20th Annual IEEE International Conference on Sensing, 2023

Agile Radio Map Prediction Using Deep Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
A Non-Cooperative Game-Based Distributed Beam Scheduling Framework for 5G Millimeter-Wave Cellular Networks.
IEEE Trans. Wirel. Commun., 2022

Uncoordinated Spectrum Sharing in Millimeter Wave Networks Using Carrier Sensing.
IEEE Trans. Wirel. Commun., 2022

Millimeter-wave user association and low-interference beam scheduling: invited paper.
Proceedings of the mmNets@MobiCom 2022: Proceedings of the 6th ACM Workshop on Millimeter-Wave and Terahertz Networks and Sensing Systems, 2022

2021
Adaptive Intelligent Radio Spectrum Sharing for Wireless Networks.
PhD thesis, 2021

DeepRadar: a deep-learning-based environmental sensing capability sensor design for CBRS.
Proceedings of the ACM MobiCom '21: The 27th Annual International Conference on Mobile Computing and Networking, 2021

A Q-Learning-Based Approach for Distributed Beam Scheduling in mmWave Networks.
Proceedings of the IEEE International Symposium on Dynamic Spectrum Access Networks, 2021

A Non-cooperative Game-based Approach to Distributed Beam Scheduling in Millimeter-Wave Networks.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
A Non-cooperative Game-based Distributed Beam Scheduling for 5G mm-Wave Networks.
CoRR, 2020

LLOCUS: learning-based localization using crowdsourcing.
Proceedings of the Mobihoc '20: The Twenty-first ACM International Symposium on Theory, 2020

A Stochastic Optimization Framework for Distributed Beam Scheduling in 5G mm-Wave Networks over Non-cooperative Operators.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Enabling Uncoordinated Spectrum Sharing in Millimeter Wave Networks Using Carrier Sensing.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Sitara: Spectrum Measurement Goes Mobile Through Crowd-Sourcing.
Proceedings of the 16th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2019

Demo Abstract: Cost-Effective Crowdsensing: Spectrum Monitoring with Sitara.
Proceedings of the 16th IEEE International Conference on Mobile Ad Hoc and Sensor Systems Workshops, 2019

2018
Privacy Enabled Crowdsourced Transmitter Localization Using Adjusted Measurements.
Proceedings of the 2018 IEEE Symposium on Privacy-Aware Computing, 2018

Privacy Enabled Noise Free Data Collection in Vehicular Networks.
Proceedings of the 15th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2018

2017
Enabling WiFi in Open Access Networks.
Proceedings of the 4th ACM Workshop on Hot Topics in Wireless, 2017

Simultaneous Power-Based Localization of Transmitters for Crowdsourced Spectrum Monitoring.
Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking, 2017


  Loading...