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Mainak Chatterjee
University of Central Florida
Distributed computingCognitive radioComputer networkComputer scienceReal-time computing
214Publications
27H-index
3,674Citations
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Publications 210
Newest
#1Debashri Roy (UCF: University of Central Florida)H-Index: 4
#2Tathagata Mukherjee (UAH: University of Alabama in Huntsville)H-Index: 3
Last. Eduardo L. Pasiliao (AFRL: Air Force Research Laboratory)H-Index: 14
view all 5 authors...
Recent advances in wireless technologies have led to several autonomous deployments of such networks. As nodes across distributed networks must co-exist, it is important that all transmitters and receivers are aware of their radio frequency (RF) surroundings so that they can adapt their transmission and reception parameters to best suit their needs. To this end, machine learning techniques have become popular as they can learn, analyze and predict the RF signals and associated parameters that ch...
1 CitationsSource
Dec 1, 2019 in GLOBECOM (Global Communications Conference)
#1Debashri Roy (UCF: University of Central Florida)H-Index: 4
#2Tathagata Mukherjee (UAH: University of Alabama in Huntsville)H-Index: 3
Last. Eduardo L. Pasiliao (AFRL: Air Force Research Laboratory)H-Index: 14
view all 4 authors...
Primary user emulation (PUE) attacks can pose a significant threat to the deployment of a robust cognitive radio network implementing dynamic spectrum access, for an intelligent allocation and usage of already crowded spectrum bands. In this paper, we present a solution towards the PUE attacks. We present two generative adversarial net (GAN) based models to successfully emulate the primary users (PUs) in two ways. We propose a (i) dumb generator model without any "prior" knowledge of PU's featur...
1 CitationsSource
#1Debashri Roy (UCF: University of Central Florida)H-Index: 4
#2Tathagata Mukherjee (UAH: University of Alabama in Huntsville)H-Index: 3
Last. Eduardo L. Pasiliao (AFRL: Air Force Research Laboratory)H-Index: 14
view all 4 authors...
The recent advances of wireless technologies in RF environments coupled with large scale usage of such technologies has warranted more autonomous deployments of wireless systems. Machine learning techniques, that include recurrent structures, have shown promise in creating such autonomous deployments using the idea of Radio Frequency Machine Learning (RFML). In large scale autonomous deployments of wireless communication networks, the signals received from one component play a crucial role in th...
Source
#1Debashri Roy (UCF: University of Central Florida)H-Index: 4
#2Tathagata Mukherjee (UA: University of Alabama)
Last. Eduardo L. Pasiliao (AFRL: Air Force Research Laboratory)H-Index: 14
view all 4 authors...
For unlicensed (secondary) users to opportunistically access the shared radio spectrum on a non-interfering basis, it is important that they are able to sense the transmission activities of the licensed (primary) users. However, spectrum sensing expend a considerable amount of energy and time, which can be reduced by reliably predicting the primary user activities. In this paper, we present recurrent neural network models which are able to accurately predict the primary users’ activity in dynami...
Source
A new framework for a secure and robust consensus in blockchain-based IoT networks is proposed. Hyperledger fabric, which is a blockchain platform developed as part of the Hyperledger project, though looks very apt for IoT applications, has comparatively low tolerance for malicious activities in an untrustworthy environment. To that end, we propose a 2-step consensus protocol that uses an outlier detection algorithm for a blockchain-based IoT network implemented on hyperledger fabric platform. T...
1 Citations
With more and more autonomous deployments of wireless networks, accurate knowledge of the RF environment is becoming indispensable. Various techniques have been developed over the years that can not only assess the RF environment but can also characterize the various radio transmitters (sources) that define the ambient RF environment. Machine learning techniques have shown promise for such characterizations through the development of RF machine learning (RFML) systems delivering autonomous contr...
Source
Apr 1, 2019 in WCNC (Wireless Communications and Networking Conference)
#1Debashri Roy (UCF: University of Central Florida)H-Index: 4
#2Tathagata Mukherjee (UAH: University of Alabama in Huntsville)H-Index: 3
Last. Eduardo L. Pasiliao (AFRL: Air Force Research Laboratory)H-Index: 14
view all 4 authors...
Understanding and analyzing the radio frequency (RF) environment have become indispensable for various autonomous wireless deployments. To this end, machine learning techniques have become popular as they can learn, analyze and even predict the RF signals and associated parameters that characterize a RF environment. However, classical machine learning methods have their limitations and there are situations where such methods become ineffective. One such setting is where active adversaries are pr...
7 CitationsSource
#1Enas F. Khairullah (KAU: King Abdulaziz University)H-Index: 2
#2Mainak Chatterjee (UCF: University of Central Florida)H-Index: 27
Abstract In this paper, we propose PreDA– a p reference-based truthful d ouble a uction for dynamic spectrum access (DSA) networks where multiple heterogeneous spectrum bands are sold by the primary users and bought by the secondary users. Unlike existing double auctions, we not only consider channels’ heterogeneity and multi-bids from buyers, but also consider buyers’ preferences for the channels. We use the signal to interference and noise ratio (SINR) as a metric for the preference; channels ...
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Nov 1, 2018 in IPCCC (International Performance, Computing, and Communications Conference)
#1Debashri Roy (UCF: University of Central Florida)H-Index: 4
#2Tathagata Mukherjee (NU: University of Nebraska–Lincoln)H-Index: 8
Last. Eduardo L. Pasiliao (AFRL: Air Force Research Laboratory)H-Index: 14
view all 4 authors...
In this paper we study and implement real-time adaptation schemes for video encoding and channel selection that work in tandem to facilitate HD video streaming for secondary users in a dynamic spectrum access network. Out-of-band feedbacks on instantaneous pathloss of the signal between the transmitter and the receiver, the received signal strength indicator (RSSI) at the receiver and the quality of the reconstructed video are used to continuously determine the most apt encoding parameters. At t...
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#1Mainak ChatterjeeH-Index: 27
#2Shamik SenguptaH-Index: 20
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