James Adu Ansere

1.4k total citations
43 papers, 956 citations indexed

About

James Adu Ansere is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, James Adu Ansere has authored 43 papers receiving a total of 956 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Networks and Communications, 26 papers in Electrical and Electronic Engineering and 8 papers in Artificial Intelligence. Recurrent topics in James Adu Ansere's work include IoT and Edge/Fog Computing (10 papers), Advanced MIMO Systems Optimization (10 papers) and Energy Efficient Wireless Sensor Networks (9 papers). James Adu Ansere is often cited by papers focused on IoT and Edge/Fog Computing (10 papers), Advanced MIMO Systems Optimization (10 papers) and Energy Efficient Wireless Sensor Networks (9 papers). James Adu Ansere collaborates with scholars based in China, Ghana and Canada. James Adu Ansere's co-authors include Guangjie Han, Hao Wang, Jinfang Jiang, Yu He, Joseph Henry Anajemba, Celestine Iwendi, Mohsin Kamal, Trung Q. Duong, Hyundong Shin and Yan Peng and has published in prestigious journals such as IEEE Access, Sensors and Information Sciences.

In The Last Decade

James Adu Ansere

40 papers receiving 939 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Adu Ansere China 18 582 460 173 143 129 43 956
Hamid Barati Iran 27 1.2k 2.0× 723 1.6× 204 1.2× 71 0.5× 187 1.4× 64 1.4k
Hassan Chizari Malaysia 14 413 0.7× 271 0.6× 106 0.6× 197 1.4× 95 0.7× 40 673
Sandeep Verma India 20 703 1.2× 577 1.3× 120 0.7× 57 0.4× 156 1.2× 48 1.2k
Fazirulhisyam Hashim Malaysia 19 912 1.6× 646 1.4× 173 1.0× 91 0.6× 211 1.6× 163 1.4k
Young-ri Choi South Korea 12 960 1.6× 391 0.8× 131 0.8× 63 0.4× 161 1.2× 34 1.1k
Walid Osamy Egypt 24 1.1k 1.9× 790 1.7× 116 0.7× 93 0.7× 60 0.5× 70 1.4k
Georgios Z. Papadopoulos France 16 446 0.8× 407 0.9× 122 0.7× 262 1.8× 43 0.3× 57 814
Mahesh K. Banavar United States 18 438 0.8× 470 1.0× 330 1.9× 62 0.4× 73 0.6× 113 1.0k
Lei Xie China 16 475 0.8× 365 0.8× 129 0.7× 213 1.5× 54 0.4× 104 773
Yingyou Wen China 14 379 0.7× 256 0.6× 149 0.9× 48 0.3× 73 0.6× 69 624

Countries citing papers authored by James Adu Ansere

Since Specialization
Citations

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

Fields of papers citing papers by James Adu Ansere

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James Adu Ansere. 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 James Adu Ansere. The network helps show where James Adu Ansere may publish in the future.

Co-authorship network of co-authors of James Adu Ansere

This figure shows the co-authorship network connecting the top 25 collaborators of James Adu Ansere. A scholar is included among the top collaborators of James Adu Ansere 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 James Adu Ansere. James Adu Ansere 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.
Ansere, James Adu, et al.. (2025). Quantum Deep Deterministic Policy Gradient for Digital Twin-Enabled Semantic IoV Networks. IEEE Transactions on Network Science and Engineering. 13. 54–66.
2.
Narottama, Bhaskara, James Adu Ansere, Nidhi Simmons, et al.. (2025). Quantum Deep Reinforcement Learning for Digital Twin-Enabled 6G Networks and Semantic Communications: Considerations for Adoption and Security. IEEE Transactions on Network Science and Engineering. 13. 2053–2076. 1 indexed citations
5.
Ansere, James Adu, et al.. (2023). Dynamic Resource Optimization for Energy-Efficient 6G-IoT Ecosystems. Sensors. 23(10). 4711–4711. 15 indexed citations
6.
Ansere, James Adu, Dũng Trần Trung, Octavia A. Dobre, et al.. (2023). Energy-Efficient Optimization for Mobile Edge Computing With Quantum Machine Learning. IEEE Wireless Communications Letters. 13(3). 661–665. 14 indexed citations
7.
Ansere, James Adu, et al.. (2023). Stochastic geometry modelling and analysis for cooperative NOMA with large transmit antennas for 5G applications and beyond. IET Communications. 17(14). 1730–1740. 4 indexed citations
8.
Chen, Junfeng, et al.. (2022). A Neighborhood Grid Clustering Algorithm for Solving Localization Problem in WSN Using Genetic Algorithm. Computational Intelligence and Neuroscience. 2022. 1–13. 8 indexed citations
9.
Anajemba, Joseph Henry, et al.. (2022). A Counter-Eavesdropping Technique for Optimized Privacy of Wireless Industrial IoT Communications. IEEE Transactions on Industrial Informatics. 18(9). 6445–6454. 27 indexed citations
10.
Duong, Trung Q., Long D. Nguyen, Bhaskara Narottama, et al.. (2022). Quantum-Inspired Real-Time Optimization for 6G Networks: Opportunities, Challenges, and the Road Ahead. IEEE Open Journal of the Communications Society. 3. 1347–1359. 46 indexed citations
11.
Duong, Trung Q., James Adu Ansere, Bhaskara Narottama, et al.. (2022). Quantum-Inspired Machine Learning for 6G: Fundamentals, Security, Resource Allocations, Challenges, and Future Research Directions. IEEE Open Journal of Vehicular Technology. 3. 375–387. 46 indexed citations
12.
Ansere, James Adu, et al.. (2021). Joint user selection and power allocation optimization for energy-efficient MU-MIMO systems with limited feedback. Telecommunication Systems. 77(3). 479–492. 2 indexed citations
13.
Ansere, James Adu, Guangjie Han, & Hao Wang. (2019). A Novel Reliable Adaptive Beacon Time Synchronization Algorithm for Large-Scale Vehicular Ad Hoc Networks. IEEE Transactions on Vehicular Technology. 68(12). 11565–11576. 35 indexed citations
14.
Ansere, James Adu, et al.. (2019). Energy Efficient Clustering Based Routing Technique in WSN using Brain Storm Optimization. 1–6. 15 indexed citations
15.
Anajemba, Joseph Henry, et al.. (2019). Efficient Switched Digital Beamforming Radar System based on SIMO/MIMO Receiver. 411–416. 6 indexed citations
16.
He, Yu, et al.. (2019). A sector-based random routing scheme for protecting the source location privacy in WSNs for the Internet of Things. Future Generation Computer Systems. 96. 438–448. 31 indexed citations
17.
Han, Guangjie, et al.. (2019). District Partition-Based Data Collection Algorithm With Event Dynamic Competition in Underwater Acoustic Sensor Networks. IEEE Transactions on Industrial Informatics. 15(10). 5755–5764. 69 indexed citations
18.
Wang, Hao, et al.. (2018). A source location privacy protection scheme based on ring-loop routing for the IoT. Computer Networks. 148. 142–150. 24 indexed citations
19.
Nti, Isaac Kofi, James Adu Ansere, & Albert Yaw Appiah. (2017). Investigating ATM Frauds In Sunyani Municipality: Customer’s Perspective. International Journal of Science and Engineering Applications. 6(2). 59–65. 5 indexed citations
20.
Ansere, James Adu, et al.. (2014). An evaluation of performance of DF in cooperative MIMO networks using relay strategies. 5(3). 152–152. 4 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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