Profil

NGUYEN Ti Ti

University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

Main Referenced Co-authors
CHATZINOTAS, Symeon  (2)
HA, Vu Nguyen  (2)
Angeletti, Piero (1)
Coskun, Adem (1)
CUIMAN MARQUEZ, Raudel  (1)
Main Referenced Keywords
DDQN (1); digital beamforming (DBF) (1); eMBB (1); FPGA implementation (1); Heterogeneous NOMA (1);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM - Signal Processing & Communications (2)
Main Referenced Disciplines
Electrical & electronics engineering (2)
Aerospace & aeronautics engineering (1)

Publications (total 2)

The most downloaded
26 downloads
TRAN, D. D., HA, V. N., Sharma, S. K., NGUYEN, T. T., CHATZINOTAS, S., & Popovski, P. (2024). Energy-Efficient NOMA for 5G Heterogeneous Services: A Joint Optimization and Deep Reinforcement Learning Approach. IEEE Transactions on Communications, 1-16. doi:10.1109/TCOMM.2024.3476083 https://hdl.handle.net/10993/62410

The most cited

2 citations (OpenAlex)

TRAN, D. D., HA, V. N., Sharma, S. K., NGUYEN, T. T., CHATZINOTAS, S., & Popovski, P. (2024). Energy-Efficient NOMA for 5G Heterogeneous Services: A Joint Optimization and Deep Reinforcement Learning Approach. IEEE Transactions on Communications, 1-16. doi:10.1109/TCOMM.2024.3476083 https://hdl.handle.net/10993/62410

GARCES SOCARRAS, L. M., GONZALEZ RIOS, J. L., Palisetty, R., CUIMAN MARQUEZ, R., HA, V. N., VASQUEZ-PERALVO, J. A., EAPPEN, G., NGUYEN, T. T., MERLANO DUNCAN, J. C., CHATZINOTAS, S., OTTERSTEN, B., MARCOS ROJAS, C. L., Coskun, A., King, S., D’Addio, S., & Angeletti, P. (2025). Efficient Digital Beamforming for Satellite Payloads Using a 2D FFT-Based Parallel Architecture. IEEE ISCAS2025 Symposium Proceedings, 1-5. doi:10.1109/iscas56072.2025.11043196
Peer reviewed

TRAN, D. D., HA, V. N., Sharma, S. K., NGUYEN, T. T., CHATZINOTAS, S., & Popovski, P. (2024). Energy-Efficient NOMA for 5G Heterogeneous Services: A Joint Optimization and Deep Reinforcement Learning Approach. IEEE Transactions on Communications, 1-16. doi:10.1109/TCOMM.2024.3476083
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