Shashi KANT

About

Shashi Kant is a senior data scientist at Ericsson AB, Stockholm, Sweden. He received a Ph.D. and M.Sc. degree in Electrical Engineering from KTH Royal Institute of Technology, Sweden, and Aalborg University, Denmark, in 2022 and 2007, respectively. Since September 2007, he has worked with many organizations in Denmark and Sweden. His current research interests include distributed intelligence, machine learning, (large-scale) distributed optimization, signal processing, and their applications to wireless communications.

Employment

• Ericsson AB 5G/LTE Concept and System Developer
  2014 - Present
• Huawei Technologies Co Ltd Research Engineer (Independent Contractor)
  2012 - 2014
• Ericsson AB Senior Software Engineer
  2008 - 2012
• KTH Royal Institute of Technology

Education

• Aalborg Universitet M.Sc.E.E. in Signal and Information Processing
  2004 - 2007

Projects & Funding

Projects & funding information is unavailable.

Publications (10)

• Federated Learning Using Three-Operator ADMM
  IEEE Journal of Selected Topics in Signal Processing 2023 DOI: 10.1109/JSTSP.2022.3221681
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• EVM Mitigation With PAPR and ACLR Constraints in Large-Scale MIMO-OFDM Using TOP-ADMM
  IEEE Transactions on Wireless Communications 2022 DOI: 10.1109/TWC.2022.3177136
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• Efficient Optimization for Large-Scale MIMO-OFDM Spectral Precoding
  IEEE Transactions on Wireless Communications 2021 DOI: 10.1109/TWC.2021.3068207
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• EVM-Constrained and Mask-Compliant MIMO-OFDM Spectral Precoding
  IEEE Transactions on Wireless Communications 2021 DOI: 10.1109/TWC.2020.3027345
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• Low-Complexity OFDM Spectral Precoding
  2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019 DOI: 10.1109/spawc.2019.8815554
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• A robust low-complexity MIMO detector for rank 4 LTE/LTE-A systems
  IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2014 DOI: 10.1109/PIMRC.2014.7136298
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• Robust UE receiver with interference cancellation in LTE advanced heterogeneous network
  IEEE Vehicular Technology Conference 2013 DOI: 10.1109/VTCFall.2013.6692396
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• Fast link adaptation for MIMO OFDM
  IEEE Transactions on Vehicular Technology 2010 DOI: 10.1109/TVT.2010.2053727
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• Mutual information metrics for fast link adaptation in IEEE 802.11n
  IEEE International Conference on Communications 2008 DOI: 10.1109/ICC.2008.920
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• Spectrum sharing for next generation wireless communication networks
  1st International Workshop on Cognitive Radio and Advanced Spectrum Management, CogART 2008 2008 DOI: 10.1109/COGART.2008.4509982
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