| 摘要(英) |
In recent years, in order to serve more and more users and achieve better and better reception quality requirements, resulting in energy consumption and power supply in short supply, energy harvesting technology can maintain small-scale wireless communication devices by harvesting energy from the surrounding environment. To maintain the operational use time of devices in small-scale wireless communication and solve the problem of limited battery capacity. In the wireless transmission environment, the signal will transmit through a complex environment such as complex, reflection, refraction, scattering, diffraction, penetration, interference, etc., so it is difficult to transmit perfectly. The commonly used solutions in the past focused on enhancing the base station and the receiver. However, while the Reconfigurable Intelligent Surface (RIS) technology changed a different way of thinking and made a fuss directly on the wireless transmission channel. RIS is a breakthrough invention in the 6G wireless networks. Unlike the transmitter and receiver, RIS can be deployed anywhere in between and used as a relay station to enhance the performance of the current communication network.
In this thesis, we propose to use solar energy harvesting technology as the energy supply source for rechargeable batteries and provide elements of the RIS to simulate the wireless transmission environment of base station is equipped with single-antenna and user is equipped with single-antenna. With the goal of maximizing the system channel capacity, the phase shift and switching mode of the elements of the RIS are jointly designed. By fixing the switching mode first, it is deduced that each phase shift is independent and corresponding. Then, according to the above, a non-convex optimization problem is formulated, and the recursive method of Successive Convex Approximation (SCA) is used to find the best switching mode to maximize the overall data rate. At last, we will discuss the number of configuration elements of the RIS, the placement position of the RIS, the location of the user′s movement, the amount of solar energy size, and three types of channels: first, BS directly to UE; second, BS to RIS and then RIS to UE; third, it is the combination of the former two types. All these resulting in the relationship among the change in channel capacity so as to optimize the system transmission efficiency.
The simulation results can prove that using the recursive method of Successive Convex Approximation (SCA) in convex optimization can obtain the optimal switching mode of elements of the RIS, and the use of RIS in wireless transmission environment can indeed effectively improve transmission quality. |
| 參考文獻 |
[1] W. Vereecken, W. Van Heddeghem, D. Colle, M. Pickavet, and P. Demeester, “Overall ICT footprint and green communication technologies,” in Proc. IEEE ISCCSP’ 10, pp. 1-6, March 2010.
[2] A. Kumar, K. Singh, and D. Bhattacharya, “Green communication and wireless networking,” in Proc. ICGCE’ 13, pp. 49-52, Dec. 2013.
[3] I. U. Ramirez, and N. A. B. Tello, “A Survey of Challenges in Green Wireless Communications Research,” in Proc. ICMEAE’ 14, pp. 197-200, Nov. 2014.
[4] P. Gandotra, and R. K. Jha, “Next generation cellular networks and green communication,” in Proc COMSNETS’ 18, pp. 522-524, Jan. 2018.
[5] M. Grant and S. Boyd, “CVX: Matlab software for disciplined convex programming, version 2.1,” [Online]. Available: http://cvxr.com/cvx, Dec. 2018.
[6] M.-L. Ku, Y. Chen and K. J. R. Liu, “Data-Driven Stochastic Models and Policies for Energy Harvesting Sensor Communications,” IEEE J. Sel. Areas Commun., vol. 33, no. 8, pp. 1505-1520, Aug. 2015.
[7] O. Ozel, K. Tutuncuoglu, J. Yang, S. Ulukus, and A. Yener, “Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies,” IEEE J. Sel. Areas Commun., vol. 29, no. 8, pp. 1732-1743, Sept. 2011.
[8] M. Tacca, P. Monti, and A. Fumagalli, “Cooperative and Reliable ARQ Protocols for Energy Harvesting Wireless Sensor Nodes,” IEEE Trans. Wireless Commun., vol. 6, no. 7, pp. 2519-2529, July 2007.
[9] S. Reddy and C. R. Murthy, “Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization,” in Proc. IEEE ICC’10, pp. 1-5, 2010.
[10] N. Michelusi, K. Stamatiou, and M. Zorzi, “Transmission Policies for Energy Harvesting Sensors with Time-Correlated Energy Supply,” IEEE Trans. Commun., vol. 61, no. 7, pp. 2988-3001, July 2013.
[11] B. Medepally and N. B. Mehta, “Voluntary Energy Harvesting Relays and Selection in Cooperative Wireless Networks,” IEEE Trans. Wireless commun., vol. 9, no. 11, pp. 3543-3553, Nov. 2010.
[12] S. Zeng, H. Zhang, B. Di, Z. Han, L. Song, “Reconfigurable Intelligent Surface (RIS) Assisted Wireless Coverage Extension: RIS Orientation and Location Optimization,” IEEE Commun. Lett., vol. 25, no. 1, pp. 269-273, Jan. 2021.
[13] L. Ge, P. Dong, H. Zhang, Jun-Bo Wang, X. You, “Joint Beamforming and Trajectory Optimization for Intelligent Reflecting Surfaces-Assisted UAV Communications,” IEEE Access, vol. 8, April. 2020.
[14] C. Huang, A. Zappone, George C. Alexandropoulos, M. Debbah, and C. Yuen,
“Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication,”
IEEE Trans. Wireless Commun., vol. 18, no. 8, pp. 4157-4170, Aug. 2019.
[15] S. Zeng, H. Zhang, B. Di, Z. Han, L. Song, “Reconfigurable Intelligent Surface (RIS) Assisted Wireless Coverage Extension: RIS Orientation and Location Optimization,” IEEE Commun. Lett., pp. 269-273, Sept. 2020.
[16] Y. Liu, L. Zhang, P. V. Klaine, M. Ali Imran,” Optimal Multi-user Transmission based on a Single Intelligent Reflecting Surface,” IEEE 4th ICEICT’16, Aug. 2021.
[17] N. K. Kundu, M. R. McKay, “RIS-Assisted MISO Communication: Optimal Beamformers and Performance Analysis,” 2020 IEEE GC Wkshps, Dec. 2020.
[18] J. Zhang, J. Liu, S. Ma, Chao-Kai Wen, S. Jin, “Large System Achievable Rate Analysis of RIS-Assisted MIMO Wireless Communication With Statistical CSIT,” IEEE Trans. Wireless Commun., vol. 20, Issue.9, pp. 5572-5585, Sept. 2021.
[19] X. Liu, Y. Liu, Y. Chen, H. Vincent Poor, “RIS Enhanced Massive Non-Orthogonal Multiple Access Networks: Deployment and Passive Beamforming Design,” IEEE J. Sel. Areas Commun., vol.39, Issue: 4, pp. 1057-1071, Aug. 2020. |
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