Bhaskara Narottama

514 total citations
22 papers, 282 citations indexed

About

Bhaskara Narottama is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Bhaskara Narottama has authored 22 papers receiving a total of 282 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Electrical and Electronic Engineering, 11 papers in Artificial Intelligence and 5 papers in Computer Networks and Communications. Recurrent topics in Bhaskara Narottama's work include Advanced MIMO Systems Optimization (6 papers), Advanced Wireless Communication Technologies (6 papers) and Quantum Computing Algorithms and Architecture (6 papers). Bhaskara Narottama is often cited by papers focused on Advanced MIMO Systems Optimization (6 papers), Advanced Wireless Communication Technologies (6 papers) and Quantum Computing Algorithms and Architecture (6 papers). Bhaskara Narottama collaborates with scholars based in South Korea, Canada and Indonesia. Bhaskara Narottama's co-authors include Soo Young Shin, Trung Q. Duong, James Adu Ansere, Hyundong Shin, Sonia Aı̈ssa, Long D. Nguyen, Vishal Sharma, Dang Van Huynh, Octavia A. Dobre and Rina Pudji Astuti and has published in prestigious journals such as IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology and IEEE Internet of Things Journal.

In The Last Decade

Bhaskara Narottama

21 papers receiving 276 citations

Peers

Bhaskara Narottama

EEE

CNC

Akbar Rahman Indonesia

Fabian Lim United States

Mostafa E. Salehi Iran

А. А. Львов Russia

Celso B. Carvalho Brazil

Moulhime El Bekkali Morocco

Haiqing Jiang China

Yunfeng Peng China

Gongbin Qian China

Yao Zhu Germany

Akbar Rahman Indonesia

Bhaskara Narottama

133 ×1.1

EEE

82 ×0.8

143 ×1.7

CNC

13 ×0.3

26 ×0.5

Citations per year, relative to Bhaskara Narottama Bhaskara Narottama (= 1×) peers Akbar Rahman

Countries citing papers authored by Bhaskara Narottama

Since Specialization

Citations

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

Fields of papers citing papers by Bhaskara Narottama

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bhaskara Narottama. 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 Bhaskara Narottama. The network helps show where Bhaskara Narottama may publish in the future.

Co-authorship network of co-authors of Bhaskara Narottama

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

All Works

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20 of 20 papers shown

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

Narottama, Bhaskara & Sonia Aı̈ssa. (2024). Quantum Machine Learning for Performance Optimization of RIS-Assisted Communications: Framework Design and Application to Energy Efficiency Maximization of Systems With RSMA. IEEE Transactions on Wireless Communications. 23(10). 12830–12843. 5 indexed citations

Narottama, Bhaskara, et al.. (2023). Quantum Deep Unfolding Based Resource Allocation Optimization for Future Wireless Networks. The Journal of Korean Institute of Communications and Information Sciences. 48(8). 897–905.

Narottama, Bhaskara, et al.. (2023). Quantum Machine Learning for Next-G Wireless Communications: Fundamentals and the Path Ahead. IEEE Open Journal of the Communications Society. 4. 2204–2224. 22 indexed citations

Narottama, Bhaskara, et al.. (2023). Layerwise Quantum Deep Reinforcement Learning for Joint Optimization of UAV Trajectory and Resource Allocation. IEEE Internet of Things Journal. 11(1). 430–443. 11 indexed citations

Narottama, Bhaskara & Soo Young Shin. (2023). Federated Quantum Neural Network with Quantum Teleportation for Resource Optimization in Future Wireless Communication. IEEE Transactions on Vehicular Technology. 1–16. 12 indexed citations

Narottama, Bhaskara & Sonia Aı̈ssa. (2023). Modular Quantum Machine Learning for Channel Estimation in STAR-RIS Assisted Communication Systems. 4 indexed citations

Narottama, Bhaskara, et al.. (2023). Quantum Neural Network With Parallel Training for Wireless Resource Optimization. IEEE Transactions on Mobile Computing. 23(5). 5835–5847. 4 indexed citations

Narottama, Bhaskara, et al.. (2022). Quantum-inspired evolutionary algorithms for NOMA user pairing. ICT Express. 8(1). 11–17. 10 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.

Narottama, Bhaskara & Trung Q. Duong. (2022). Quantum Neural Networks for Optimal Resource Allocation in Cell-Free MIMO Systems. GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 2444–2449. 8 indexed citations

13.

Narottama, Bhaskara & Soo Young Shin. (2021). Quantum Neural Networks for Resource Allocation in Wireless Communications. IEEE Transactions on Wireless Communications. 21(2). 1103–1116. 26 indexed citations

14.

Narottama, Bhaskara & Soo Young Shin. (2019). Dynamic Power Allocation for Non-Orthogonal Multiple Access with User Mobility. 442–446. 12 indexed citations

15.

Narottama, Bhaskara, et al.. (2017). Device Discovery Schemes for Energy-efficient Cluster Head Rotation in D2D. TELKOMNIKA (Telecommunication Computing Electronics and Control). 15(1). 203–203. 3 indexed citations

16.

Narottama, Bhaskara, et al.. (2017). Selective Green Device Discovery for Device-to-Device Communication. TELKOMNIKA (Telecommunication Computing Electronics and Control). 15(4). 1666–1666. 1 indexed citations

17.

Narottama, Bhaskara, et al.. (2017). Base station energy efficiency of D2D device discovery. 257–261. 2 indexed citations

18.

Astuti, Rina Pudji, et al.. (2017). Optimum UAV flying path for Device-to-Device communications in disaster area. 318–322. 30 indexed citations

19.

Narottama, Bhaskara, et al.. (2015). Impact of number of devices and data rate variation in clustering method on device-to-device communication. 233–238. 10 indexed citations

20.

Narottama, Bhaskara, et al.. (2015). Cluster head rotation: a proposed method for energy efficiency in d2d communication. 89–90. 9 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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