THEODOROS TSIFTSIS
@jnu.edu.cn
School of Intelligent Systems Science and Engineering
Jinan University
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Haoxuan Liu, Nan Qi, Kewei Wang, Theodoros A. Tsiftsis, Wenjing Wang, and Yawen Liu
Elsevier BV
Leila Tlebaldiyeva, Sultangali Arzykulov, Theodoros A. Tsiftsis, and Galymzhan Nauryzbayev
Elsevier BV
Nan Qi, Zhe Su, Wen-Jing Wang, Rugui Yao, and Theodoros A. Tsiftsis
Institute of Electrical and Electronics Engineers (IEEE)
Vaibhav Sharma, Raviteja Allu, Sandeep Kumar Singh, Keshav Singh, Trung Q. Duong, and Theodoros A. Tsiftsis
Institute of Electrical and Electronics Engineers (IEEE)
Min Wu, Kefeng Guo, Xingwang Li, Zhi Lin, Yongpeng Wu, Theodoros A. Tsiftsis, and Houbing Song
Institute of Electrical and Electronics Engineers (IEEE)
Kefeng Guo, Haifeng Shuai, Xingwang Li, Liang Yang, Theodoros A. Tsiftsis, Arumugam Nallanathan, and Min Wu
Institute of Electrical and Electronics Engineers (IEEE)
Nikolaos I. Miridakis, Theodoros A. Tsiftsis, Panagiotis A. Karkazis, Helen C. Leligou, and Fotis Foukalas
Institute of Electrical and Electronics Engineers (IEEE)
Hongjiang Lei, Fangtao Yang, Hongwu Liu, Imran Shafique Ansari, Kyeong Jin Kim, and Theodoros A. Tsiftsis
Institute of Electrical and Electronics Engineers (IEEE)
Miaomiao Zhu, Kefeng Guo, Yinghui Ye, Liang Yang, Theodoros A. Tsiftsis, and Hongwu Liu
Institute of Electrical and Electronics Engineers (IEEE)
Tong Li, Rugui Yao, Ye Fan, Xiaoya Zuo, N. I. Miridakis, and T. A. Tsiftsis
Institute of Electrical and Electronics Engineers (IEEE)
Zhiqiang Liu, Di Zhang, Jingjing Guo, Theodoros A. Tsiftsis, Yuwei Su, Battulga Davaasambuu, Sahil Garg, and Takuro Sato
Institute of Electrical and Electronics Engineers (IEEE)
Rugui Yao, Yongsong Yu, Peng Wang, Ye Fan, Xudong Li, Xiaoya Zuo, Nan Qi, Nikolaos I. Miridakis, and Theodoros A. Tsiftsis
Institution of Engineering and Technology (IET)
Hongjiang Lei, Fangtao Yang, Imran Shafique Ansari, Hongwu Liu, Kyeong Jin Kim, and Theodoros A. Tsiftsis
Institute of Electrical and Electronics Engineers (IEEE)
Liang Yang, Wei Zhang, Petros S. Bithas, Hongwu Liu, Mazen O. Hasna, Theodoros A. Tsiftsis, and Derrick Wing Kwan Ng
Institute of Electrical and Electronics Engineers (IEEE)
Qiang Sun, Hongwu Liu, Shen Yan, Theodoros A. Tsiftsis, and Jinhong Yuan
Institute of Electrical and Electronics Engineers (IEEE)
Peixu Liu, Gang Jing, Hongwu Liu, Liang Yang, and Theodoros A. Tsiftsis
Elsevier BV
Pengxu Chen, Hongwu Liu, Yinghui Ye, Liang Yang, Kyeong Jin Kim, and Theodoros A. Tsiftsis
Institute of Electrical and Electronics Engineers (IEEE)
Xingwang Li, Qunshu Wang, Ming Zeng, Yuanwei Liu, Shuping Dang, Theodoros A. Tsiftsis, and Octavia A. Dobre
Institute of Electrical and Electronics Engineers (IEEE)
Haifeng Shuai, Kefeng Guo, Kang An, Yuzhen Huang, Theodoros A. Tsiftsis, and Shibing Zhu
Institute of Electrical and Electronics Engineers (IEEE)
Muthukrishnan Senthil Kumar, Aresh Dadlani, Masoumeh Moradian, Ahmad Khonsari, and Theodoros A. Tsiftsis
Institute of Electrical and Electronics Engineers (IEEE)
Prajwalita Saikia, Anand Jee, Keshav Singh, Cunhua Pan, Theodoros A. Tsiftsis, and Wan-Jen Huang
IEEE
In this paper, we consider Simultaneous Transmission and Reflection (STAR) Reconfigurable Intelligent Surface (S-RIS) and passive RIS (P-RIS) assisted integrated sensing and communication system (ISAC), where S-RIS is enabled to broadcast communication signal, and P-RIS assists sensing functionalities. In particular, we jointly optimize the beamforming vector at the multi-antenna ISAC transmitter, and phase shift vector to maximize the weighted sum-rate (WSR) at the communication users while taking care of the maximum power limit at ISAC transmitter while ensuring the performance of sensing model to detect targets in its vicinity and limitations of phase and amplitude of S-RIS elements. To address the non-convexity of the above problem, we propose a low-complexity alternating optimization (AO) algorithm. Furthermore, we provide a comprehensive simulation-based graphical results to verify the viability of the proposed framework with its P-RIS assisted counterpart. Eventually, exhaustive simulation results are demonstrated to present the impact of RIS elements and the number of antennas at the ISAC transmitter. Accordingly, we illustrate the impact of S-RIS and the number of targets to highlight the trade-off between sensing and communication.
Sonia Pala, Mayur Katwe, Keshav Singh, Theodoros A. Tsiftsis, and Chih-Peng Li
IEEE
The proliferation of multiple devices and acceleration of spectral efficiency has become a pivotal requirement for the unprecedented connectivity and performance of vehicle-to-everything (V2X) networks. This paper investigates an unconventional framework of reconfigurable intelligent surface (RIS)-integrated full-duplex (FD) rate-splitting multiple access (RSMA) communication systems, which aims to maximize the spectral efficiency of uplink (UL) and downlink (DL) vehicles in V2X network. In particular, a robust spectral-efficient design for the considered RIS-integrated FD-RSMA system via joint beamforming design and power allocation at UL vehicles under imperfect channel state information is investigated. To tackle the non-convexity of the original sum-rate maximization problem, we adopt a deep reinforcement learning (DRL)-based proximal policy optimization (PPO) algorithm which leverages Markov decision process formulation. Simulation results demonstrate the effectiveness of the integration of RIS, RSMA, and FD schemes for V2X networks over half-duplex (HD) and multi-user linear precoding schemes. Furthermore, the superiority of the proposed PPO algorithm is validated over the counterpart deep deterministic policy gradient algorithm (DDPG).
Vaibhav Sharma, Raviteja Allu, Sandeep Kumar Singh, Keshav Singh, and Theodoros A. Tsiftsis
IEEE
This work investigates the performance of simultaneous wireless information and power transfer (SWIPT) in a reconfigurable intelligent surface (RIS)-aided green multiple input single output (MISO) communications under imperfect channel state information (CSI). With an aim to provide green and robust transmission, we formulate a multi-objective optimization problem (MOOP) to design transmit precoding vector (TPV) at the base station (BS) and phase shift matrix (PSM) at the RIS that maximizes the energy efficiency at the information receivers and harvested power at the energy receivers under the norm bounded CSI error model. Due to the conflicting objective functions and non-convex nature, the MOOP is simplified using the $\\epsilon$-constraint method. We then propose an alternating optimization-based iterative algorithm that utilizes semidefinite programming to determine the optimal TPV and PSM one by one until convergence is achieved. Via exhaustive simulations, we graphically demonstrate the effectiveness and robustness of the proposed algorithm. Furthermore, we assess the impact of several key parameters such as the number of RIS elements, available transmit power at BS and the minimum harvested power at each energy receiver on the performance of the considered system.
Jiawen Tian, Wenwen Guan, Xiao Li, Theodoros A. Tsiftsis, and Hongwu Liu
IEEE
Due to dynamic change of the wireless environment, devising the local phase shift matrix for reconfigurable intelligent surface (RIS) can be a thought-provoking task. Therefore, in this paper, we come up with a deep reinforcement learning (DRL)-based beamforming optimization algorithm for RIS-aided multiple-input single-output communication systems. To be precise, we exploit a DRL-based structure based on twin-delayed-deep-deterministic-policy-gradient (TD3) algorithm to automatically adjust the phase shift of each unit at RIS to maximize the downlink received signal-to-noise ratio (SNR). Simulation results show that the raised TD3 algorithm performs a higher received SNR than the conventional DRL algorithm with a reduced running time.
Xueyu Kang, Hongjiang Lei, Liang Yang, Gaofeng Pan, Theodoros A. Tsiftsis, and Hongwu Liu
Institute of Electrical and Electronics Engineers (IEEE)