Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS
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doi.org/10.1109/tvt.2018.2878891 →Countries where authors are citing Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS
This map shows the geographic impact of Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS. 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 Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS more than expected).
Fields of papers citing Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS
This network shows the impact of Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS.
About Practical Pulse-Shaping Waveforms for Reduced-Cyclic-Prefix OTFS
This paper, published in 2018, received 443 indexed citations . Written by Patchava Raviteja, Yi Hong, Emanuele Viterbo and E. Biglieri covering the research area of Aerospace Engineering and Electrical and Electronic Engineering. It is primarily cited by scholars working on Electrical and Electronic Engineering (418 citations), Aerospace Engineering (93 citations), Computer Networks and Communications (46 citations), Computer Vision and Pattern Recognition (17 citations) and Artificial Intelligence (16 citations). Published in IEEE Transactions on Vehicular Technology.
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.
This paper is also available at doi.org/10.1109/tvt.2018.2878891.