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Papers by Arpita Banerjee Chakraborty

Research paper thumbnail of South Asian Countries Are Less Fatal Concerning COVID-19: A Hybrid Approach Using Machine Learning and M-AHP

EAI/Springer Innovations in Communication and Computing, 2021

Research paper thumbnail of Architecture of Cognitive Radio Networks

Advances in Wireless Technologies and Telecommunication

Today’s wireless networks are characterized by fixed spectrum assignment policy. The spectral sca... more Today’s wireless networks are characterized by fixed spectrum assignment policy. The spectral scarcity and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum, opportunistically. Cognitive Radio (CR) is that very paradigm for wireless communication, in which either a network or a wireless node reconfigures its transmission or reception parameters to communicate efficiently avoiding interference with licensed or unlicensed users. CR adapts itself to the newer environment on the basis of its intelligent sensing and captures the best available spectrum to meet user communication requirements. When the radio link features are extended to the network layer, the cognitive radios form the cognitive radio network. This book chapter is focused on cognitive radio network, architecture of the CR, and its relevance in the wireless and mobile Ad Hoc networks.

Research paper thumbnail of A Survey On Agri-Crisis In India Based On Engineering Aspects

Research paper thumbnail of Non-uniform Quantized Data Fusion Rule for Data Rate Saving and Reducing Control Channel Overhead for Cooperative Spectrum Sensing in Cognitive Radio Networks

Wireless Personal Communications, 2018

In this paper a pretty new concept of non-uniform quantized data fusion (N-QDF) rule reducing con... more In this paper a pretty new concept of non-uniform quantized data fusion (N-QDF) rule reducing control channel data overhead has been proposed for energy detection based cooperative spectrum sensing scheme in cognitive radio networks. To strike a balance between efficient detection performance and less complexity, the network has to allow soften hard or quantized data fusion (QDF) technique though this technique incurs few bit overhead on the control channel from each user. Again lower bit QDF causes loss of more information, where as higher bit QDF increases detection probability at the cost of some extra bits per user. Here lies the beauty of NQDF scheme which uses variable number of bits: more number of bits for lower energy region-thus increases detection probability for a given false alarm, and less number of bits for higher energy region-thus data rate gets saved which in turn alleviates control channel overhead. A holistic simulation study has been done in this very paper where the performance of variable bit NQDF scheme is compared with different uniform bit i.e. 2, 3, 4, 5 QDF with respect to different parameters to validate our proposed scheme.

Research paper thumbnail of An Advance Q Learning (AQL) Approach for Path Planning and Obstacle Avoidance of a Mobile Robot

International Journal of Intelligent Mechatronics and Robotics, 2013

The goal of this paper is to improve the performance of the well known Q learning algorithm, the ... more The goal of this paper is to improve the performance of the well known Q learning algorithm, the robust technique of Machine learning to facilitate path planning in an environment. Until this time the Q learning algorithms like Classical Q learning(CQL)algorithm and Improved Q learning (IQL) algorithm deal with an environment without obstacles, while in a real environment an agent has to face obstacles very frequently. Hence this paper considers an environment with number of obstacles and has coined a new parameter, called ‘immediate penalty’ due to collision with an obstacle. Further the proposed technique has replaced the scalar ‘immediate reward’ function by ‘effective immediate reward’ function which consists of two fuzzy parameters named as, ‘immediate reward’ and ‘immediate penalty’. The fuzzification of these two important parameters not only improves the learning technique, it also strikes a balance between exploration and exploitation, the most challenging problem of Reinfo...

Research paper thumbnail of Malicious Node Restricted Quantized Data Fusion Scheme for Trustworthy Spectrum Sensing in Cognitive Radio Networks

JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, 2020

Accuracy in spectrum sensing is very much required in cognitive radio network, which is a revolut... more Accuracy in spectrum sensing is very much required in cognitive radio network, which is a revolutionary paradigm to drift the spectrum underutilization problem. To enhance the detection performance in presence of shadowing or fading multiple SUs cooperate among themselves. But the collaboration and so the detection process is severely affected by the presence of some harmful secondary users known as Malicious users. As a result of this false sensing, spectrum wastage or interference with primary users may happen which are not at all desired for the system. The proposed approach in this paper has intelligently excluded these malicious users from the decision making process and thus improves the efficiency of the system.

Research paper thumbnail of South Asian Countries Are Less Fatal Concerning COVID-19: A Hybrid Approach Using Machine Learning and M-AHP

EAI/Springer Innovations in Communication and Computing, 2021

Research paper thumbnail of Architecture of Cognitive Radio Networks

Advances in Wireless Technologies and Telecommunication

Today’s wireless networks are characterized by fixed spectrum assignment policy. The spectral sca... more Today’s wireless networks are characterized by fixed spectrum assignment policy. The spectral scarcity and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum, opportunistically. Cognitive Radio (CR) is that very paradigm for wireless communication, in which either a network or a wireless node reconfigures its transmission or reception parameters to communicate efficiently avoiding interference with licensed or unlicensed users. CR adapts itself to the newer environment on the basis of its intelligent sensing and captures the best available spectrum to meet user communication requirements. When the radio link features are extended to the network layer, the cognitive radios form the cognitive radio network. This book chapter is focused on cognitive radio network, architecture of the CR, and its relevance in the wireless and mobile Ad Hoc networks.

Research paper thumbnail of A Survey On Agri-Crisis In India Based On Engineering Aspects

Research paper thumbnail of Non-uniform Quantized Data Fusion Rule for Data Rate Saving and Reducing Control Channel Overhead for Cooperative Spectrum Sensing in Cognitive Radio Networks

Wireless Personal Communications, 2018

In this paper a pretty new concept of non-uniform quantized data fusion (N-QDF) rule reducing con... more In this paper a pretty new concept of non-uniform quantized data fusion (N-QDF) rule reducing control channel data overhead has been proposed for energy detection based cooperative spectrum sensing scheme in cognitive radio networks. To strike a balance between efficient detection performance and less complexity, the network has to allow soften hard or quantized data fusion (QDF) technique though this technique incurs few bit overhead on the control channel from each user. Again lower bit QDF causes loss of more information, where as higher bit QDF increases detection probability at the cost of some extra bits per user. Here lies the beauty of NQDF scheme which uses variable number of bits: more number of bits for lower energy region-thus increases detection probability for a given false alarm, and less number of bits for higher energy region-thus data rate gets saved which in turn alleviates control channel overhead. A holistic simulation study has been done in this very paper where the performance of variable bit NQDF scheme is compared with different uniform bit i.e. 2, 3, 4, 5 QDF with respect to different parameters to validate our proposed scheme.

Research paper thumbnail of An Advance Q Learning (AQL) Approach for Path Planning and Obstacle Avoidance of a Mobile Robot

International Journal of Intelligent Mechatronics and Robotics, 2013

The goal of this paper is to improve the performance of the well known Q learning algorithm, the ... more The goal of this paper is to improve the performance of the well known Q learning algorithm, the robust technique of Machine learning to facilitate path planning in an environment. Until this time the Q learning algorithms like Classical Q learning(CQL)algorithm and Improved Q learning (IQL) algorithm deal with an environment without obstacles, while in a real environment an agent has to face obstacles very frequently. Hence this paper considers an environment with number of obstacles and has coined a new parameter, called ‘immediate penalty’ due to collision with an obstacle. Further the proposed technique has replaced the scalar ‘immediate reward’ function by ‘effective immediate reward’ function which consists of two fuzzy parameters named as, ‘immediate reward’ and ‘immediate penalty’. The fuzzification of these two important parameters not only improves the learning technique, it also strikes a balance between exploration and exploitation, the most challenging problem of Reinfo...

Research paper thumbnail of Malicious Node Restricted Quantized Data Fusion Scheme for Trustworthy Spectrum Sensing in Cognitive Radio Networks

JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, 2020

Accuracy in spectrum sensing is very much required in cognitive radio network, which is a revolut... more Accuracy in spectrum sensing is very much required in cognitive radio network, which is a revolutionary paradigm to drift the spectrum underutilization problem. To enhance the detection performance in presence of shadowing or fading multiple SUs cooperate among themselves. But the collaboration and so the detection process is severely affected by the presence of some harmful secondary users known as Malicious users. As a result of this false sensing, spectrum wastage or interference with primary users may happen which are not at all desired for the system. The proposed approach in this paper has intelligently excluded these malicious users from the decision making process and thus improves the efficiency of the system.