Niranjay Ravindran

1.4k citations
17 papers · 911 · 1 hit paper · h-index 10

Impact in

Papers in

Niranjay Ravindran

16 papers receiving 880 citations

Niranjay Ravindran's Hit Papers

Multiuser MIMO achievable rates with downlink training and channel state feedback 2010 · 366 citations
3660+5+10Years since publication100200300

Peers

Niranjay Ravindran
Comparison fields: 5 of 32
  • Computational Mathematics 144
  • Computer Networks and Communications 591
  • Hardware and Architecture 99
  • Electrical and Electronic Engineering 744
  • Artificial Intelligence 81
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Citations per year

Countries citing papers authored by Niranjay Ravindran

Since Specialization
Citations

This map shows the geographic impact of Niranjay Ravindran's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Niranjay Ravindran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niranjay Ravindran more than expected).

Fields of papers citing papers by Niranjay Ravindran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Niranjay Ravindran. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Niranjay Ravindran. The network helps show where Niranjay Ravindran may publish in the future.

Co-authors

The 13 scholars most cited alongside Niranjay Ravindran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Niranjay Ravindran Line = papers co-authored together Niranjay Ravindran links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
Multiuser MIMO achievable rates with downlink training and channel state feedback
Hit paper breakdown →
2010366
2 2008171
3 2015137
4 200746
5
Multiuser MIMO Downlink Made Practical: Achievable Rates with Simple Channel State Estimation and Feedback Schemes
200745
6 201232
7 200731
8 200828
9 201425
10 200711
11 20216
12 20075
13 20103
14 20062
15 20212
16 20251
17 20070

About Niranjay Ravindran

Niranjay Ravindran is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computational Mathematics, Artificial Intelligence and Atomic and Molecular Physics, and Optics, having authored 17 papers that have together received 911 indexed citations. Recurring topics across this work include Cooperative Communication and Network Coding (10 papers), Advanced MIMO Systems Optimization (9 papers), Advanced Wireless Network Optimization (5 papers), Energy Harvesting in Wireless Networks (4 papers), Wireless Networks and Protocols (3 papers), Mobile Ad Hoc Networks (3 papers), Tensor decomposition and applications (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Computational Mathematics (144 citations), Computer Networks and Communications (591 citations), Hardware and Architecture (99 citations), Electrical and Electronic Engineering (744 citations) and Artificial Intelligence (81 citations). Niranjay Ravindran has collaborated with scholars based in United States, France and Puerto Rico. Frequent co-authors include Nihar Jindal, Giuseppe Caire, Mari Kobayashi, Nicholas D. Sidiropoulos, George Karypis, Shaden Smith, Howard Huang, S. Radha, Rick Galbraith and Jian-Gang Zhu. Their work appears in journals such as IEEE Transactions on Magnetics, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Wireless Communications, IETE Journal of Research and 2014 48th Asilomar Conference on Signals, Systems and Computers.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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