Ankita Tondwalkar

Ankita Tondwalkar
Vidyalankar Institute of Technology · Department of Electronics and Telecommunications Engineering

About

11
Publications
457
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
49
Citations

Publications

Publications (11)
Article
Full-text available
This paper studies a deep reinforcement learning technique for distributed resource allocation among cognitive radios operating under an underlay dynamic spectrum access paradigm which does not require coordination between agents during learning. The key challenge that is addressed in this work is that of a non-stationary reinforcement learning env...
Article
Full-text available
Technology innovation for the sixth generation (6G) era should focus on improving quality of life by addressing societal needs, advancing human experience with the fusion of digital and physical worlds, and achieving a sustainable well-being. The 6G networks are expected to bring higher capacity and coverage combined with dependable real-time prope...
Article
Full-text available
Fifth-generation (5G) wireless technology promises to be the critical enabler of use cases far beyond smartphones and other connected devices. This next-generation 5G wireless standard represents the changing face of connectivity by enabling elevated levels of automation through continuous optimization of several Key Performance Indicators (KPIs) s...
Preprint
Full-text available
This paper presents a novel deep reinforcement learning-based resource allocation technique for the multi-agent environment presented by a cognitive radio network where the interactions of the agents during learning may lead to a non-stationary environment. The resource allocation technique presented in this work is distributed, not requiring coord...
Preprint
This paper presents a novel deep reinforcement learning-based resource allocation technique for the multi-agent environment presented by a cognitive radio network that coexists through underlay dynamic spectrum access (DSA) with a primary network. The resource allocation technique presented in this work is distributed, not requiring coordination wi...
Article
Full-text available
The data collected from the sensor network is meaningful to most of the wireless sensor network applications if and only if it is coupled with the exact positioning of the node. Mere localisation solves the problem of locating an unknown node, however applications like battlefield surveillance or enemy tracking, rescue-operations as well as monitor...

Network

Cited By