M
Meenakshi Rawat
Researcher at Indian Institute of Technology Roorkee
Publications - 127
Citations - 1429
Meenakshi Rawat is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Predistortion & Amplifier. The author has an hindex of 16, co-authored 105 publications receiving 1053 citations. Previous affiliations of Meenakshi Rawat include Ohio State University & Indian Institutes of Technology.
Papers
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Adaptive Digital Predistortion of Wireless Power Amplifiers/Transmitters Using Dynamic Real-Valued Focused Time-Delay Line Neural Networks
TL;DR: In this paper, a real-valued focused time-delay neural network (RVFTDNN) was proposed for the linearization of third-generation power amplifier (PA) behavioral modeling.
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A Ray Launching-Neural Network Approach for Radio Wave Propagation Analysis in Complex Indoor Environments
TL;DR: A novel deterministic approach to model the radio wave propagation channels in complex indoor environments reducing computational complexity is proposed, which allows the use of a lower number of launched rays in the simulation scenario whereas intermediate points can be predicted using neural network.
Convergence Analysis in Deterministic 3D Ray Launching Radio Channel Estimation in Complex Environments
Leire Azpilicueta,Meenakshi Rawat,Karun Rawat,Fadhel M. Ghannouchi,Francisco Falcone,Ahmed M. Kord,I. A. Eshrah,Y. An,Z. Fan,D. Ding,R. Chen,Y. Li,W. Li,W. Yu,C. Liu,J. Chen,M. Zhu,M. Y. Wang,S. Li,Xin Li,F. Liu,G. Sun,J. Wang,R. Du,R. Araneo,S. Celozzi,Nasser Ojaroudi,N. Ghadimi,Yasser Ojaroudi,Gang Zhang,Y. Dou,H. Cui,L. Y. Xiang,S. G. Zuo,L. C. He,M. H. Zhang,J. J. Hu,G. Long +37 more
TL;DR: In this paper, a convergence analysis to obtain the optimal calculation parameters in an in-house 3D ray launching algorithm to model the radio wave propagation channel in complex indoor environments is presented.
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Linearization of Concurrent Tri-Band Transmitters Using 3-D Phase-Aligned Pruned Volterra Model
TL;DR: In this article, a 3D phase-aligned pruned Volterra DPD was proposed for concurrent tri-band power amplifiers (PAs), which can effectively compensate for the crosstalk effects between the fundamental frequencies, their harmonics, and intermodulation products.
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Composite Neural Network Digital Predistortion Model for Joint Mitigation of Crosstalk, $I/Q$ Imbalance, Nonlinearity in MIMO Transmitters
TL;DR: With the increase in the dimensions of MIMO transmitter, the proposed NN-based DPD model provides a better compensation for transmitter imperfections and also reduces the complexity as compared to the state-of-the-art DPD methods.