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Jeffrey H. Reed

35 papers hereh-index 5514.3k citations380 works total

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

author position
  • first author1
  • middle author10
  • last author23

Across the 34 of 35 papers where every author was matched, so the position is known.

fields
  • cs.NI15
  • eess.SP15
  • cs.IT4
  • cs.OH1
same name
  • Jeffrey H. Reed — 11 papers, h 13
  • Jeffrey H. Reed — 7 papers, h 4
  • Jeffrey H. Reed — 4 papers, h 2
  • Jeffrey H. Reed — 2 papers, h 4
  • Jeffrey H. Reed — 2 papers, h 4
  • Jeffrey H. Reed — 1 paper, h 2

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
20112022
most citedVulnerability of LTE to Hostile Interference

86 citations · 222 across the 33 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.IT2021

Optimizing Number, Placement, and Backhaul Connectivity of Multi-UAV Networks

Javad Sabzehali, Vijay K. Shah, Qiang Fan +3

Multi-Unmanned Aerial Vehicle (UAV) Networks is a promising solution to providing wireless coverage to ground users in challenging rural areas (such as Internet of Things (IoT) dev…

cs.NI2021

AoI-minimizing Scheduling in UAV-relayed IoT Networks

Biplav Choudhury, Vijay K. Shah, Aidin Ferdowsi +2

Due to flexibility, autonomy and low operational cost, unmanned aerial vehicles (UAVs), as fixed aerial base stations, are increasingly being used as \textit{relays} to collect tim…

cs.IT2021

3D Placement and Orientation of mmWave-based UAVs for Guaranteed LoS Coverage

Javad Sabzehali, Vijay K. Shah, Harpreet S. Dhillon +1

Unmanned aerial vehicles (UAVs), as aerial base stations, are a promising solution for providing wireless communications, thanks to their high flexibility and autonomy. Moreover, e…

cs.NI2021

Deep Learning for Fast and Reliable Initial Access in AI-Driven 6G mmWave Networks

Tarun S. Cousik, Vijay K. Shah, Tugba Erpek +2

We present DeepIA, a deep neural network (DNN) framework for enabling fast and reliable initial access for AI-driven beyond 5G and 6G millimeter (mmWave) networks. DeepIA reduces t…

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