output
20162026
most citedGAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

353 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2019 · eess.SPShow all

4 papers · 2 filters

eess.SP2019

Mobility and Coverage Evaluation of New Radio PDCCH for Point-to-Multipoint Scenario

Hongzhi Chen, De Mi, Belkacem Mouhouche +2

This paper provides the mobility and coverage evaluation of New Radio (NR) Physical Downlink Control Channel (PDCCH) for Point-to-Multipoint (PTM) use cases, e.g., eMBMS (evolved M…

eess.SP2019

Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions

Manijeh Bashar, Alister G. Burr, Katsuyuki Haneda +4

A low complexity massive multiple-input multiple-output (MIMO) technique is studied with a geometry-based stochastic channel model, called COST 2100 model. We propose to exploit th…

eess.SP2019★ 7 cited

Techno-economic analyses for vertical use cases in the 5G domain

Sandrine Roblot, Mythri Hunukumbure, Nadège Varsier +5

This paper provides techno-economic analyses on the network deployments to cover 4 key verticals, under 5G-NR. These verticals, namely Automotive, Smart city, Long range connectivi…

eess.SP2019

MIND: Model Independent Neural Decoder

Yihan Jiang, Hyeji Kim, Himanshu Asnani +1

Standard decoding approaches rely on model-based channel estimation methods to compensate for varying channel effects, which degrade in performance whenever there is a model mismat…