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Sheng Chen

8 papers hereh-index 318 citations14 works total

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

author position
  • middle author1
  • last author6

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.NI5
  • eess.SP3
same name
  • Sheng Chen — 17 papers, h 47
  • Sheng Chen — 7 papers, h 6
  • Sheng Chen — 7 papers, h 6
  • Sheng Chen — 7 papers, h 12
  • Sheng Chen — 7 papers, h 3
  • Sheng Chen — 7 papers, h 3

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
20242026
most citedHigh-Speed Ultra-Energy-Efficient Memristor-Based Massive MIMO SIC Detector Circuit with Hybrid Analog-Digital Computing Architecture

4 citations · 12 across the 7 of their papers we have counts for

collaborators
Showing 2024Show all

3 papers · 1 filter

cs.NI2024★ 2 cited

Outage Probability Analysis of Uplink Heterogeneous Non-terrestrial Networks: A Novel Stochastic Geometry Model

Wen-Yu Dong, Shaoshi Yang, Wei Lin +3

In harsh environments such as mountainous terrain, dense vegetation areas, or urban landscapes, a single type of unmanned aerial vehicles (UAVs) may encounter challenges like fligh…

eess.SP2024★ 3 cited

In-Memory Massive MIMO Linear Detector Circuit with Extremely High Energy Efficiency and Strong Memristive Conductance Deviation Robustness

Jia-Hui Bi, Shaoshi Yang, Ping Zhang +1

The memristive crossbar array (MCA) has been successfully applied to accelerate matrix computations of signal detection in massive multiple-input multiple-output (MIMO) systems. Ho…

eess.SP2024★ 3 cited

Amplifier-Enhanced Memristive Massive MIMO Linear Detector Circuit: An Ultra-Energy-Efficient and Robust-to-Conductance-Error Design

Jia-Hui Bi, Shaoshi Yang, Ping Zhang +1

The emerging analog matrix computing technology based on memristive crossbar array (MCA) constitutes a revolutionary new computational paradigm applicable to a wide range of domain…

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