Toshihiko Nishimura
About
In The Last Decade
Toshihiko Nishimura
131 papers receiving 832 citations
Peers
Comparison fields: 5 of 78
- Electrical and Electronic Engineering 571
- Computer Networks and Communications 297
- Signal Processing 160
- Aerospace Engineering 148
- Artificial Intelligence 62
Countries citing papers authored by Toshihiko Nishimura
This map shows the geographic impact of Toshihiko Nishimura'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 Toshihiko Nishimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toshihiko Nishimura more than expected).
Fields of papers citing papers by Toshihiko Nishimura
This network shows the impact of papers produced by Toshihiko Nishimura. 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 Toshihiko Nishimura. The network helps show where Toshihiko Nishimura may publish in the future.
Co-authorship network of co-authors of Toshihiko Nishimura
This figure shows the co-authorship network connecting the top 25 collaborators of Toshihiko Nishimura. A scholar is included among the top collaborators of Toshihiko Nishimura based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Toshihiko Nishimura. Toshihiko Nishimura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | A Study on Signal Detection in Massive MIMO Using MCMC | 1 |
| 3 | Evaluation of Loose Beamforming with a Genetic Algorithm in a Multiuser Massive MIMO System | 2 |
| 4 | Considerations on Computational Complexity Reduction of Receive Weight Matrices in Massive MIMO SC-FDE | 0 |
| 5 | Node selection and LLR damping for channel equalization with belief propagation | 2 |
| 6 | Channel Prediction Using 2-Step Compressed Sensing in a Time-Varying Multi-User MIMO Environment | 1 |
| 7 | Performance Evaluation of Full-Dimension MIMO Systems with Consideration for User Density Using a Ray-tracing Technique | 1 |
| 8 | Performance Evaluation of Full-Dimension MIMO Systems with a Different Number of BS Antenna Elements Using a Ray-tracing Technique | 1 |
| 9 | Channel Prediction Using Compressed Sensing in a Multi-User MIMO Environment with Moving Scatterers | 1 |
| 10 | A Study on LLR Damping in Belief Propagation for Channel Equalization | 1 |
| 11 | Considerations on a Channel Prediction Scheme Using Compressed Sensing in Multi-User MIMO Systems | 2 |
| 12 | Considerations on Channel Prediction Schemes Using Compressed Sensing | 2 |
| 13 | Study on Parameter Dependence of DOA Estimation of Multi-band Signals Using a Compressed Sensing Technique | 1 |
| 14 | Considerations on a Multi-User Single-Carrier E-SDM Scheme in Wideband Transmissions | 0 |
| 15 | A fundamental study on routing and scheduling for multi-hop wireless networks with adaptive array | 0 |
| 16 | A Study on Precoding Prediction in LTE Downlink | 0 |
| 17 | A study on transmit-antenna selection for multiuser-MIMO uplink | 2 |
| 18 | Performance Comparison of MIMO-SDM Depending on Array Configurations Based on Indoor Measurements | 1 |
| 19 | An impact of channel state information error on SDM applications | 2 |
| 20 | Downlink weight control using channel response estimation in TDD/SDMA | 1 |
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.