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Shi Jin

14 papers hereh-index 10353 citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author12
  • last author2

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • eess.SP5
  • cs.IT4
  • cs.AI2
  • cs.LG1
  • cs.NI1
  • eess.IV1
same name
  • Shi Jin — 165 papers, h 82
  • Shi Jin — 62 papers, h 49
  • Shi Jin — 34 papers, h 8
  • Shi Jin — 32 papers, h 10
  • Shi Jin — 22 papers, h 32
  • Shi Jin — 22 papers, h 23

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedDeep Learning for MIMO Channel Estimation: Interpretation, Performance, and Comparison

9 citations · 13 across the 14 of their papers we have counts for

collaborators
Showing cs.ITShow all

4 papers · 1 filter

cs.IT2026

A Graph Foundation Model for Large-Scale MIMO Detection

Xingyu Zhou, Le Liang, Hao Ye +5

Large-scale multiple-input multiple-output (MIMO) detection is fundamental to modern wireless networks but constrained by performance-complexity trade-offs. Existing detectors, whe…

cs.IT2024

Semantic Communication for Cooperative Perception using HARQ

Yucheng Sheng, Le Liang, Hao Ye +2

Cooperative perception, offering a wider field of view than standalone perception, is becoming increasingly crucial in autonomous driving. This perception is enabled through vehicl…

cs.IT2023

Semantic Communication for Cooperative Perception based on Importance Map

Yucheng Sheng, Hao Ye, Le Liang +2

Cooperative perception, which has a broader perception field than single-vehicle perception, has played an increasingly important role in autonomous driving to conduct 3D object de…

cs.IT2023★ 1 cited

Meta Reinforcement Learning for Fast Spectrum Sharing in Vehicular Networks

Kai Huang, Le Liang, Shi Jin +1

In this paper, we investigate the problem of fast spectrum sharing in vehicle-to-everything communication. In order to improve the spectrum efficiency of the whole system, the spec…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.