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215 results on '"Ghosh, Arnob"'

51. Quality Sensitive Price Competition in Spectrum Oligopoly:Part 1

Author

Ghosh, Arnob and Sarkar, Saswati

Subjects
Computer Science - Computer Science and Game Theory
Abstract

We investigate a spectrum oligopoly market where primaries lease their channels to secondaries in lieu of financial remuneration. Transmission quality of a channel evolves randomly. Each primary has to select the price it would quote without knowing the transmission qualities of its competitors' channels. Each secondary buys a channel depending on the price and the transmission quality a channel offers. We formulate the price selection problem as a non co-operative game with primaries as players. In the one-shot game, we show that there exists a unique symmetric Nash Equilibrium(NE) strategy profile and explicitly compute it. Our analysis reveals that under the NE strategy profile a primary prices its channel to render high quality channel more preferable to the secondary; this negates the popular belief that prices ought to be selected to render channels equally preferable to the secondary regardless of their qualities. We show the loss of revenue in the asymptotic limit due to the non co-operation of primaries. In the repeated version of the game, we characterize a subgame perfect NE where a primary can attain a payoff arbitrarily close to the payoff it would obtain when primaries co-operate., Comment: Accepted for publication in IEEE/ACM Transactions on Networking. 41 pages single column format.Conference version is available at arXiv:1305.3351

Published
2014

52. Quality Sensitive Price Competition in Spectrum Oligopoly

Author

Ghosh, Arnob and Sarkar, Saswati

Subjects
Computer Science - Computer Science and Game Theory
Abstract

We investigate a spectrum oligopoly where primary users allow secondary access in lieu of financial remuneration. Transmission qualities of the licensed bands fluctuate randomly. Each primary needs to select the price of its channel with the knowledge of its own channel state but not that of its competitors. Secondaries choose among the channels available on sale based on their states and prices. We formulate the price selection as a non-cooperative game and prove that a symmetric Nash equilibrium (NE) strategy profile exists uniquely. We explicitly compute this strategy profile and analytically and numerically evaluate its efficiency. Our structural results provide certain key insights about the unique symmetric NE., Comment: Presented in ISIT' 2013, Istanbul Version 2 contains some modified versions of proofs of version 1. In IEEE Proceedings of International Symposium on Information Theory, 2013

Published
2013
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53. Comparative analysis of selective area grown Ga- and N-polar InGaN/GaN nanowires for quantum emitters.

Author

Ghosh, Arnob, Khan, Kamruzzaman, Sankar, Shrivatch, Jian, Zhe, Hasan, Syed M. N., Ahmadi, Elaheh, and Arafin, Shamsul

Subjects
*NANOWIRES, *INDIUM gallium nitride, *GALLIUM nitride, *MOLECULAR beams, *COMPARATIVE studies, *EPITAXY, *GALLIUM alloys
Abstract

In this paper, we report the molecular beam epitaxy-grown InGaN-quantum disks embedded within selective area epitaxy of GaN nanowires with both Ga- and N-polarities. A detailed comparative analysis of these two types of nanostructures is also provided. Compared to Ga-polar nanowires, N-polar nanowires are found to exhibit a higher vertical growth rate, flatter top, and reduced lateral overgrowth. InGaN quantum disk-related optical emission is observed from nanowires with both polarities; however, the N-polar structures inherently emit at longer wavelengths due to higher indium incorporation. Considering that N-polar nanowires offer more compelling geometry control compared to Ga-polar ones, we focus on the theoretical analysis of only N-polar structures to realize high-performance quantum emitters. A single nanowire-level analysis was performed, and the effects of nanowire diameter, taper length, and angle on guided modes, light extraction, and far-field emission were investigated. These findings highlight the importance of tailoring nanowire geometry and eventually optimizing the growth processes of III-nitride nanostructures. [ABSTRACT FROM AUTHOR]

Published
2024
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71. Multi Sensor Fusion Using Fitness Adaptive Differential Evolution

Author

Giri, Ritwik, Ghosh, Arnob, Chowdhury, Aritra, Das, Swagatam, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Panigrahi, Bijaya Ketan, editor, Das, Swagatam, editor, Suganthan, Ponnuthurai Nagaratnam, editor, and Dash, Subhransu Sekhar, editor

Published
2010
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72. Offline Parameter Estimation of Induction Motor Using a Meta Heuristic Algorithm

Author

Giri, Ritwik, Chowdhury, Aritra, Ghosh, Arnob, Panigrahi, B. K., Das, Swagatam, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Panigrahi, Bijaya Ketan, editor, Das, Swagatam, editor, Suganthan, Ponnuthurai Nagaratnam, editor, and Dash, Subhransu Sekhar, editor

Published
2010
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73. Electromagnetic Antenna Configuration Optimization Using Fitness Adaptive Differential Evolution

Author

Chowdhury, Aritra, Ghosh, Arnob, Giri, Ritwik, Das, Swagatam, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Panigrahi, Bijaya Ketan, editor, Das, Swagatam, editor, Suganthan, Ponnuthurai Nagaratnam, editor, and Dash, Subhransu Sekhar, editor

Published
2010
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74. Event-Triggered Action-Delayed Reinforcement Learning Control of a Mixed Autonomy Signalised Urban Intersection

Author

Salvato, Erica, Ghosh, Arnob, Fenu, Gianfranco, and Parisini, Thomas

Subjects
Markov processes, reinforcement learning, road traffic control
Abstract

We propose an event-triggered framework for deciding the traffic light at each lane in a mixed autonomy scenario. We deploy the decision after a suitable delay, and events are triggered based on the satisfaction of a predefined set of conditions. We design the trigger conditions and the delay to increase the vehicles’ throughput. This way, we achieve full exploitation of autonomous vehicles (AVs) potential. The ultimate goal is to obtain vehicle-flows led by AVs at the head. We formulate the decision process of the traffic intersection controller as a deterministic delayed Markov decision process, i.e., the action implementation and evaluation are delayed. We propose a Reinforcement Learning based model-free algorithm to obtain the optimal policy. We show - by simulations - that our algorithm converges, and significantly reduces the average wait-time and the queues length as the fraction of the AVs increases. Our algorithm outperforms our previous work [1] by a quite significant amount.

Published
2022

75. A Novel Framework for Cost Constrained Network Sharing

Author

Ruzomberka, Eric, Kim, Kwang Taik, Ghosh, Arnob, Love, David J., and Chiang, Mung

Abstract

Network sharing is widely accepted as a cost effective approach for mobile network deployment. It remains uncertain, however, how regulators will evaluate network sharing agreements (NSA) for future networks in the context of the current competition law. For example, 5G mobile network operators (MNOs) seeking to enter NSAs may risk legal challenges, as regulators have not given MNOs sufficient guidance for self-evaluation of their NSAs. One way for MNOs to reduce the risk of legal challenge is to avoid sharing variable costs in the NSA. However, constraining costs to be non-variable (i.e., fixed) rules out the use of most pricing mechanisms that have been widely adopted for dynamic resource trading between MNOs. In this article, we propose a network sharing framework to allow dynamic resource sharing without the use of resource pricing. To incentivize sharing without pricing, our framework presents sharing as a means for MNOs to differentiate services and better compete in the service market for profit. We evaluate our framework in a duopoly market model and demonstrate the economic and regulatory viability of our framework.

Published
2023
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84. Luminescence and Raman Spectroscopic Properties of Cubic Boron Nitride

Author

Rahaman, Mohammad Mahafuzur, primary, Saha, Shantanu, additional, Hasan, Syed M. N., additional, You, Weicheng, additional, Ghosh, Arnob, additional, Sumon, Md Saiful Islam, additional, Nikor, SK Shafaat Saud, additional, Freeman, Benjamin, additional, Sankar, Shrivatch, additional, Colijn, Hendrik, additional, Sadaf, Sharif Md., additional, Garg, Jivtesh, additional, and Arafin, Shamsul, additional

Published
2022
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85. Traffic-Light Control at Urban Intersections Using Expected Waiting-Time Information

Author

Ghosh, Arnob, Scandella, Matteo, Bin, Michelangelo, and Parisini, Thomas

Subjects
Iterative methods, optimal control, optimisation, road traffic control
Abstract

We consider an optimal traffic-light control framework for urban traffic intersections to alleviate congestion phenomena. We analyze a scenario in which we provide drivers with information about the waiting time at the intersections. We model the drivers’ lane-changing information-based behavior as the solution of a convex optimization problem. We compute the optimal traffic-light control mechanism as the solution to a bi-level optimization problem. We provide a complete analysis in terms of (i) the existence of a solution; (ii) an iterative algorithm to compute it; (iii) sufficient conditions for the solution’s uniqueness and the algorithm’s convergence. Early simulation results show the proposed control scheme’s effectiveness compared with an optimal control algorithm in the absence of waiting-time information.

Published
2021

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