Gek Hong Sim

737 total citations
26 papers, 498 citations indexed

About

Gek Hong Sim is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Gek Hong Sim has authored 26 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Electrical and Electronic Engineering, 11 papers in Computer Networks and Communications and 2 papers in Artificial Intelligence. Recurrent topics in Gek Hong Sim's work include Advanced MIMO Systems Optimization (19 papers), Millimeter-Wave Propagation and Modeling (15 papers) and Cooperative Communication and Network Coding (7 papers). Gek Hong Sim is often cited by papers focused on Advanced MIMO Systems Optimization (19 papers), Millimeter-Wave Propagation and Modeling (15 papers) and Cooperative Communication and Network Coding (7 papers). Gek Hong Sim collaborates with scholars based in Germany, Spain and Malaysia. Gek Hong Sim's co-authors include Arash Asadi, Matthias Hollick, Anja Klein, Sabrina Klos, Ying Loong Lee, Li‐Chun Wang, Donghong Qin, Joerg Widmer, Adrian Loch and Cristina Cano and has published in prestigious journals such as IEEE Journal on Selected Areas in Communications, IEEE Transactions on Wireless Communications and IEEE/ACM Transactions on Networking.

In The Last Decade

Gek Hong Sim

26 papers receiving 488 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gek Hong Sim Germany 9 443 140 100 44 29 26 498
Mohammad Shehab Finland 12 313 0.7× 194 1.4× 110 1.1× 20 0.5× 25 0.9× 27 420
Seiamak Vahid United Kingdom 10 527 1.2× 475 3.4× 54 0.5× 45 1.0× 22 0.8× 40 636
Kai Yu China 13 305 0.7× 246 1.8× 105 1.1× 16 0.4× 40 1.4× 42 438
Rafay Iqbal Ansari Pakistan 9 364 0.8× 237 1.7× 86 0.9× 19 0.4× 37 1.3× 22 470
José David Vega Sánchez Ecuador 11 340 0.8× 146 1.0× 105 1.1× 18 0.4× 44 1.5× 29 404
Munawwar M. Sohul United States 8 275 0.6× 193 1.4× 73 0.7× 35 0.8× 51 1.8× 14 373
Tommaso Zugno Italy 8 356 0.8× 168 1.2× 68 0.7× 50 1.1× 9 0.3× 22 414
Biljana Bojović Spain 14 481 1.1× 343 2.5× 38 0.4× 77 1.8× 25 0.9× 34 584
Vyacheslav Begishev Russia 9 296 0.7× 126 0.9× 48 0.5× 47 1.1× 14 0.5× 26 356

Countries citing papers authored by Gek Hong Sim

Since Specialization
Citations

This map shows the geographic impact of Gek Hong Sim'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 Gek Hong Sim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gek Hong Sim more than expected).

Fields of papers citing papers by Gek Hong Sim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gek Hong Sim. 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 Gek Hong Sim. The network helps show where Gek Hong Sim may publish in the future.

Co-authorship network of co-authors of Gek Hong Sim

This figure shows the co-authorship network connecting the top 25 collaborators of Gek Hong Sim. A scholar is included among the top collaborators of Gek Hong Sim 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 Gek Hong Sim. Gek Hong Sim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Krishnamoorthy, Aravindh, et al.. (2024). Radio Resource Management Design for RSMA: Optimization of Beamforming, User Admission, and Discrete/Continuous Rates With Imperfect SIC. IEEE Transactions on Mobile Computing. 23(12). 11498–11518. 4 indexed citations
2.
Hollick, Matthias, et al.. (2022). Sequential Parametric Optimization for Rate-Splitting Precoding in Non-Orthogonal Unicast and Multicast Transmissions. ICC 2022 - IEEE International Conference on Communications. 3904–3910. 2 indexed citations
3.
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5.
Sim, Gek Hong, et al.. (2021). Stay Connected, Leave no Trace: Enhancing Security and Privacy in WiFi via Obfuscating Radiometric Fingerprints. ACM SIGMETRICS Performance Evaluation Review. 49(1). 83–84. 1 indexed citations
6.
Lee, Ying Loong, Donghong Qin, Li‐Chun Wang, & Gek Hong Sim. (2020). 6G Massive Radio Access Networks: Key Applications, Requirements and Challenges. IEEE Open Journal of Vehicular Technology. 2. 54–66. 114 indexed citations
7.
Cano, Cristina, Gek Hong Sim, Arash Asadi, & Xavier Vilajosana. (2020). A Channel Measurement Campaign for mmWave Communication in Industrial Settings. IEEE Transactions on Wireless Communications. 20(1). 299–315. 40 indexed citations
8.
Sim, Gek Hong, et al.. (2020). Fairness-Aware Hybrid Precoding for mmWave NOMA Unicast/Multicast Transmissions in Industrial IoT. abs 1903 10502. 1–7. 4 indexed citations
9.
Sim, Gek Hong, et al.. (2020). Joint Relaying and Spatial Sharing Multicast Scheduling for mmWave Networks. Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam). 127–136. 7 indexed citations
10.
Sim, Gek Hong, et al.. (2020). Learning-based Max-Min Fair Hybrid Precoding for mmWave Multicasting. 1–7. 1 indexed citations
11.
Asadi, Arash, et al.. (2019). SCAROS: A Scalable and Robust Self-Backhauling Solution for Highly Dynamic Millimeter-Wave Networks. IEEE Journal on Selected Areas in Communications. 37(12). 2685–2698. 20 indexed citations
12.
Sim, Gek Hong, Sabrina Klos, Arash Asadi, Anja Klein, & Matthias Hollick. (2018). An Online Context-Aware Machine Learning Algorithm for 5G mmWave Vehicular Communications. IEEE/ACM Transactions on Networking. 26(6). 2487–2500. 107 indexed citations
13.
Asadi, Arash, Sabrina Klos, Gek Hong Sim, Anja Klein, & Matthias Hollick. (2018). FML: Fast Machine Learning for 5G mmWave Vehicular Communications. TUbilio (Technical University of Darmstadt). 1961–1969. 58 indexed citations
14.
Sim, Gek Hong, Adrian Loch, Arash Asadi, Vincenzo Mancuso, & Joerg Widmer. (2017). 5G Millimeter-Wave and D2D Symbiosis: 60 GHz for Proximity-Based Services. IEEE Wireless Communications. 24(4). 140–145. 35 indexed citations
15.
Loch, Adrian, Arash Asadi, Gek Hong Sim, Joerg Widmer, & Matthias Hollick. (2017). mm-Wave on wheels: Practical 60 GHz vehicular communication without beam training. TUbilio (Technical University of Darmstadt). 36 indexed citations
16.
Sim, Gek Hong, et al.. (2016). Learning from experience: Efficient decentralized scheduling for 60GHz mesh networks. Edinburgh Research Explorer. 1–9. 3 indexed citations
17.
Sim, Gek Hong, Joerg Widmer, & Balaji Rengarajan. (2015). Opportunistic Finite Horizon Multicasting of Erasure-Coded Data. IEEE Transactions on Mobile Computing. 15(3). 705–718. 7 indexed citations
18.
Sim, Gek Hong, Joerg Widmer, & Balaji Rengarajan. (2014). Opportunistic beamforming for finite horizon multicast. 3 indexed citations
19.
Sim, Gek Hong, Balaji Rengarajan, & Joerg Widmer. (2013). Adaptive modulation for finite horizon multicasting of erasure-coded data. 1. 1–10. 3 indexed citations
20.
Sim, Gek Hong, Yoong Choon Chang, & Teong Chee Chuah. (2011). Adaptive error protection for video transmission over ultra-wideband wireless multimedia sensor networks. Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University). 86–90. 2 indexed citations

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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