activity
20142022
most citedFederated Learning Using Three-Operator ADMM

7 citations · 7 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2022★ 7 cited

Federated Learning Using Three-Operator ADMM

Shashi Kant, José Mairton B. da Silva, Gabor Fodor +3

Federated learning (FL) has emerged as an instance of distributed machine learning paradigm that avoids the transmission of data generated on the users' side. Although data are not…

eess.SP2022

EVM Mitigation with PAPR and ACLR Constraints in Large-Scale MIMO-OFDM Using TOP-ADMM

Shashi Kant, Mats Bengtsson, Gabor Fodor +2

Although signal distortion-based peak-to-average power ratio (PAPR) reduction is a feasible candidate for orthogonal frequency division multiplexing (OFDM) to meet standard/regulat…

eess.SP2020

EVM-Constrained and Mask-Compliant MIMO-OFDM Spectral Precoding

Shashi Kant, Mats Bengtsson, Gabor Fodor +2

Spectral precoding is a promising technique to suppress out-of-band emissions and comply with leakage constraints over adjacent frequency channels and with mask requirements on the…

eess.SP2019

Low-Complexity OFDM Spectral Precoding

Shashi Kant, Gabor Fodor, Mats Bengtsson +2

This paper proposes a new large-scale mask-compliant spectral precoder (LS-MSP) for orthogonal frequency division multiplexing systems. In this paper, we first consider a previousl…

cs.IT2014

A Robust Low-Complexity MIMO Detector for Rank 4 LTE/LTE-A Systems

Shashi Kant, Fredrik Rusek, Basuki E. Priyanto

This paper deals with MIMO detection for rank 4 LTE systems. The paper revolves around a previously known detector [1, by Inkyu Lee, TCOM'2010] which we shall refer to as RCSMLD (R…