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20132023
most cited6G White Paper on Machine Learning in Wireless Communication Networks

94 citations · 233 across the 14 of their papers we have counts for

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5 papers · 1 filter

eess.SP2023★ 1 cited

Meeting IMT 2030 Performance Targets: The Potential of OTFDM Waveform and Structural MIMO Technologies

Spandan Bisoyi, Murali Mohan Pasupuleti, Kiran Kuchi +5

The white paper focuses on several candidate technologies that could play a crucial role in the development of 6G systems. Two of the key technologies explored in detail are Orthog…

eess.SP2022★ 61 cited

A Spatially Separable Attention Mechanism for massive MIMO CSI Feedback

Sharan Mourya, SaiDhiraj Amuru, Kiran Kumar Kuchi

Channel State Information (CSI) Feedback plays a crucial role in achieving higher gains through beamforming. However, for a massive MIMO system, this feedback overhead is huge and…

eess.SP2019

Low PAPR Reference Signal Transceiver Design for 3GPP 5G NR Uplink

M. Sibgath Ali Khan, Sai Dhiraj Amuru, Kiran Kuchi

Low peak-to-average-power ratio (PAPR) transmissions significantly improve the cell coverage as they enable high power transmissions without saturating the power amplifier. A new m…

eess.SP2019

Beam Learning -- Using Machine Learning for Finding Beam Directions

Saidhiraj Amuru

Beamforming is the key enabler for wireless communications in the mmWave bands. 802.11ad and WiGig are wireless technologies that currently use the 60 GHz unlicensed mmWave spectru…

eess.SP2019★ 1 cited

A Novel Beamformed Control Channel Design for LTE with Full Dimension-MIMO

Pavan Reddy M., Harish Kumar D., Saidhiraj Amuru +1

The Full Dimension-MIMO (FD-MIMO) technology is capable of achieving huge improvements in network throughput with simultaneous connectivity of a large number of mobile wireless dev…