綠色通訊隨著通訊技術發展與環境保護議題的重視逐漸受到關注與討論。節省能
源與採集能源在無線通訊系統中是兩個主要能改善能源消耗的方式。本文中我們著重
於綠色環保概念出發探討與設計在兩種網路架構為異質網路，無線充電通訊網路中的
資源分配和波束成型的議題。在綠色異質網路中，我們探討大型基地台協助小型基地
台的網路架構中能動態調整的將小型基地台關閉，讓小型基地台流量服務的要求轉移
至大型基地台來達到節省能源。在大型基地台協助小型基地台的網路架構中節省能源
的策略包含了很多影響網路能源需求的因素，如: 可用的頻寬、負載使用者的能力、服
務範圍的大小、使用者的速率要求、中斷機率條件、雜訊干擾等；除此之外，強制中
斷小型基地台服務的機率也影響到節省能源的決定。在無線充電通訊網路中，我們探
討在無線網路通訊中讓有採集能源的裝置透過採集電磁訊號轉換成電能儲存或直接使
用。具體來說，我們在無線傳輸能量的系統下行傳輸時傳輸能量給予多使用者儲存後，
讓多使用者在上行的傳輸時間利用採集的電磁訊號轉換後的能量傳輸訊息。在透過波
束成型技術讓基地台能在同時間內讓多使用者在下行傳輸時採集能量，上行傳輸時同
時傳輸訊息。設計無線充電通訊網路中需考量到能量花費的控制、上行時間多使用者
同時傳輸的相互干擾、無線傳輸能量的效益與基地台的能量消耗。
在大型基地台協助小型基地台的網路架構中，設計的問題模型透過條件式馬可夫
決策模型的線性規劃求解後，得到隨機模型來進行最佳的基地台睡眠與喚醒的策略；
在無線充電通訊網路中，聯合設計下行與上行的波束成型、下行與上行的時間分配和
上行時多使用者間的能量控制。其中非凸的最佳化問題，用半正定放寬的方法，先以
固定的時間分配與上行接收波束成型來求得傳輸能量的解，在透過交替迭代更新後得到最佳的時間分配與上行接收波束成型。最後，提出的設計方法也透過電腦模擬驗證
效能，經由電腦模擬結果證實論文中提出的馬可夫決策過程的方法在保證強制平均中
斷機率的前提下可以透過開關小型基地台達到有效率的能源使用，也證實我們提出的
聯合設計資源分配與波束成型可以有效地節省基地台傳輸能源的能源花費。

Green communication has received significant attention and discussions due to its potential
telecom business, recent technology advances, and environmental protection. Saving
energy and harvesting energy are two main perspectives to improve the energy consumption of
wireless communication networks. In this dissertation, we focus on the green designs for two
kinds of wireless networks, namely, heterogeneous networks (HetNets) and wireless-powered
communication networks (WPCNs) from these two perspectives through resource management
and beamforming techniques. For the green HetNets, we investigate a macrocell-assisted small
cell network that allows for saving energy consumption by dynamically switching off the deployed
small cells and offloading the data traffic to the macrocell base station. The power-saving
strategy of the macrocell-assisted small cell networks depends on several network parameters
like power consumption of base stations, available bandwidth, user load in the cells, cell size,
user rate requirement, rate outage probability, and noise power density. Besides, it also affects
the user dropping probability of the small cells. For the WPCNs, we investigate a wireless
network that can utilize energy harvesting technology to capture wireless energy and convert
it into electrical energy that can be used immediately or later. Specifically, we consider that
wireless-powered devices can harvest energy from radio-frequency signals by the base station
in the downlink and then utilize the harvested energy for transmitting data in the uplink. The
base station can concurrently serve multiple users with downlink harvested energy and uplink
data reception by utilizing beamforming techniques. The designed WPCN, however, suffers
from several critical issues such as power control, uplink multiuser interference, power transfer
efficiency, and base station energy consumption.
For the macrocell-assisted small cell networks, the design problem is formulated as a constrained
Markov decision process and solved via linear programming. A randomized strategy is proposed to accomplish the optimal sleep/wake-up policy for small cells. For the WPCNs, the
downlink/uplink beamforming, downlink/uplink time allocation, and uplink multiuser power
control are jointly designed. The non-convex problem is first solved with fixed time allocation
and uplink receive beamforming via a semi-definite relaxation (SDR) approach, based on
which an iterative algorithm is proposed for updating the optimal time allocation and the receive
beamforming. The proposed design methodologies are validated via extensive computer simulations.
The simulation results confirm that the proposed Markov decision process approach can
achieve efficient energy utilization by switching on/off small cells while ensuring the average
user dropping probability. Also, the simulation results confirm that the proposed joint resource
management and beamforming scheme can effectively reduce the charging energy consumption
of the base station.

[1] E. Hossain, M. Rasti, H. Tabassum, and A. Abdelnasser, “Evolution toward 5G multitier
cellular wireless networks: An interference management perspective,” IEEE Wireless
Commun., vol. 21, no. 3, pp. 118-127, Jun. 2014.
[2] A. J. Paulraj, D. A. Gore, R. U. Nadar, and H. Bolcskei, “An overview of MIMO communications
- a key to gigabit wireless,” Proc. IEEE, vol. 92, no. 2, pp. 198-218, Feb.
2004.
[3] G. J. Foschini and M. Gans, “On limits of wireless communications in a fading environment
when using multiple antennas,” Wireless Personal Commun., vol. 6, no. 3, pp. 311-335,
Mar. 1998.
[4] I. Ashraf, F. Boccardi, and L. Ho, “SLEEP mode techniques for small cell deployments,”
IEEE Commun. Mag., vol. 49, no. 8, pp. 72-79, Aug. 2011.
[5] Z. Hasan, H. Boostanimehr, and V. K. Bhargava, “Green cellular networks: a survey, some
research issues and challenges,” IEEE Commun. Surveys Tuts., vol. 13, pp. 524-540, 4th
Quart. 2011.
[6] R. Q. Hu and Y. Qian, “An energy efficient and spectrum efficient wireless heterogeneous
network framework for 5G systems,” IEEE Commun. Mag., vol. 52, no. 5, pp. 94-101,
May 2014.
[7] H. Tabassum, E. Hossain, A. Ogundipe, and D. I. Kim, “Wireless-powered cellular networks:
Key challenges and solution techniques,” IEEE Commun. Mag., vol. 56, no. 6, pp.
63–71, Jun. 2015.
[8] L. Liu, R. Zhang, and K.-C. Chua, “Multi-antenna wireless powered communication with
energy beamforming,” IEEE Trans. Commun., vol. 62, no. 12, pp. 4349–4361, Dec. 2014.
[9] Y. Che, J. Xu, L. Duan, and R. Zhang, “Multiantenna wireless powered communication
with cochannel energy and information transfer,” IEEE Commun. Lett., vol. 19, no. 12, pp.
2266–2269, Dec. 2015.
[10] W. Huang, H. Chen, Y. Li, and B. Vucetic, “On the performance of multi-antenna wirelesspowered
communications with energy beamforming,” IEEE Trans. Veh. Technol., vol. 65,
no. 3, pp. 1801–1808, Mar. 2016.
[11] Q. Sun, G. Zhu, C. Shen, X. Li, and Z. Zhong, “Joint beamforming design and time allocation
for wireless powered communication networks,” IEEE Commun. Lett., vol. 18, no.
10, pp. 1783–1786, Oct. 2014.
[12] A. Ghosh, N. Mangalvedhe, R. Ratasuk, B. Mondal, M. Cudak, E. Visotsky, T. A. Thomas,
J. G. Andrews, P. Xia, H. S. Jo, H. S. Dhillon, and T. D. Novlan, “Heterogeneous cellular
networks: From theory to practice,” IEEE Commun. Mag., vol. 50, no. 6, pp. 54-64, Jun.
2012.
[13] C. de Lima, M. Bennis, and M. Latva-aho, “Statistical analysis of self-organizing networks
with biased cell association and interference avoidance,” IEEE Trans. Veh. Technol., vol.
62, no. 5, pp. 1950–1961, Jun. 2012
[14] W.-H. Yang, Y.-C. Wang, Y.-C. Tseng, and B.-S. Lin, “Energy-efficient network selection
with mobility pattern awareness in an integrated WiMAX and WiFi network,” Int. J. Commun.
Syst., vol. 23, no. 2, pp. 213–230, Feb. 2010.
[15] R. Razavi and H. Claussen, “Urban small cell deployments: Impact on the network energy
consumption,” in Proc. IEEE Wireless Commun. Netw. Conf. Workshops (WCNCW), pp.
47–52, 2012.
[16] J. Wu, Y. Zhang, M. Zukerman, and E. K. N. Yung, “Energy-efficient base-stations sleepmode
techniques in green cellular networks: A survey,” IEEE Commun. Surveys Tuts., vol.
17, no. 2, pp. 803-826, 2nd Quart. 2015.
[17] G. de la Roche, A. Valcarce, D. Lopez-Perez, and J. Zhang, “Access Control Mechanisms
for Femtocells,” IEEE Commun. Mag., vol. 48, no. 1, pp. 33-39, Jan. 2010.
[18] C. S. Chen, V. M. Nguyen, and L. Thomas, “On small cell network deployment: A comparative
study of random and grid topologies,” Proc. IEEE Veh. Technol. Conf. (VTC), pp.
1-5, 2012.
[19] C. Sun, E. Stevens-Navarro, and V. W. S. Wong, “A constrained MDP-based vertical handoff
decision algorithm for 4G wireless networks,” Proc. IEEE Int. Conf. Commun. (ICC),
pp. 2169-2174, 2008.
[20] T. Mao, G. Feng, L. Liang, S. Qin, and B. Wu, “Distributed energy efficient power control
for macro-femto networks,” IEEE Trans. Veh. Technol., vol. 65, no. 2, pp. 718-731, Feb.
2015.
[21] T. Zhang, K. Zhu and J. Wang, “Energy-efficient mode selection and resource allocation
for D2D-enabled heterogeneous networks: a deep reinforcement learning approach,” IEEE
Trans. Wireless Commun., vol. 20, no. 2, pp. 1175–1187, 2021.
[22] M.-L. Ku, W. Li, Y. Chen, and K. J. Ray Liu, “Advances in energy harvesting communications:
Past, present, and future challenges,” IEEE Commun. Surveys Tuts., vol. 18, no.
2, pp. 1384–1412, Second Quarter 2016.
[23] X. Lu, P. Wang, D. Niyato, D. I. Kim, and Z. Han, “Wireless charging technologies: Fundamentals,
standards, and network applications,” IEEE Commun. Surveys Tuts., vol. 18,
no. 2, pp. 1413–1452, Second Quarter 2016.
[24] Y. Liu, Z. Ding, M. Elkashlan, and H. V. Poor, “Cooperative non-orthogonal multiple
access with simultaneous wireless information and power transfer, ” EEE J. Sel. Areas
Commun., vol. 34, no. 4, pp. 938–953, Apr. 2016.
[25] X. Lu, P. Wang, D. Niyato, D. I. Kim, and Z. Han, “Wireless networks with RF energy
harvesting: A contemporary survey,” IEEE Commun. Surveys Tuts., vol. 17, no. 2, pp.
757–789, Second Quarter 2015.
[26] H. Ju and R. Zhang, “Throughput maximization in wireless powered communication networks,”
IEEE Trans. Wireless Commun., vol. 13, no. 1, pp. 418–428, Jan. 2014.
[27] H. Ju and R. Zhang, “Optimal resource allocation in full-duplex wireless-powered communication
network,” IEEE Trans. Commun., vol. 62, no. 10, pp. 3528–3540, Oct. 2014.
[28] X. Kang, C. K. Ho, and S. Sun, “Optimal time allocation for dynamic TDMA-based wireless
powered communication networks,” in Proc. IEEE Global Commun. Conf., 2014, pp.
3157–3161.
[29] Q. Wu, W. Chen, and J. Li, “Wireless powered communications with initial energy: QoS
guaranteed energy-efficient resource allocation,” IEEE Commun. Lett., vol. 19, no. 12, pp.
2278–2281, Dec. 2015.
[30] T. Nguyen, Q. Pham, V. Nguyen, J. Lee, and Y. Kim, “Resource allocation for energy
efficiency in OFDMA-enabled WPCN,” IEEE Wireless Commun. Lett., vol. 9, no. 12, pp.
2049–2053, Dec. 2020.
[31] X. Lin, L. Huang, C. Guo, P. Zhang, M. Huang, and J. Zhang, “Energy efficient resource
allocation in TDMS-based wireless powered communication networks,” IEEE Commun.
Lett., vol. 21, no. 4, pp. 861–864, Apr. 2017.
[32] Q. Wu, W. Chen, D. W. K. Ng, J. Li, and R. Schober, “User-centric energy efficiency
maximization for wireless powered communications,” IEEE Trans. Wireless Commun.,
vol. 15, no. 10, pp. 6898–6912, Oct. 2016.
[33] Y. S. Soh, T. Q. S. Quek, M. Kountouris, and H. Shin “Energy efficient heterogeneous
cellular networks,” IEEE J. Sel. Areas Commun., vol. 31, no. 5, pp. 840-850, May 2013.
[34] Y. Jin, L. Qiu, and X. Liang, “Small cells on/off control and load balancing for green dense
heterogeneous networks,” Proc. IEEE Wireless Commun. Netw. Conf. (WCNC), pp. 1530-
1535, 2015.
[35] J. Wu, J. Liu, and H. Zhao, “Dynamic small cell on/off control for green ultra-dense networks,”
Proc. Int. Conf. on Wireless Commun. Signal Process. (WCSP), pages 1-5, 2016.
[36] C. Liu, B. Natarajan, and H. Xia, “Small cell base station sleep strategies for energy efficiency,”
IEEE Trans. Veh. Technol., vol. 65, no. 3, pp. 1652-1661, Mar. 2016.
[37] H. Celebi, N. Maxemchuk, Y. Li, and I. Guvenc, “Energy reduction in small cell networks
by a random on/off strategy,” Proc. IEEE Globecom Workshops, pp. 176-181, 2013.
[38] L. Falconetti, P. Frenger, H. Kallin, and T. Rimhagen, “Energy efficiency in heterogeneous
networks,” Proc. IEEE Online Conf. Green Commun. (GreenCom), pp. 98-103, 2012.
[39] L. Saker, S. Elayoubi, R. Combes, and T. Chahed, “Optimal control of wake up mechanisms
of femtocells in heterogeneous networks,” IEEE J. Sel. Areas Commun., vol. 30, no. 3, pp.
664-672, Apr. 2012.
[40] Y. H. Chiang and W. Liao, “Genie: An optimal green policy for energy saving and traffic
offloading in heterogeneous cellular networks,” Proc. IEEE Int. Conf. Commun. (ICC), pp.
6230-6234, 2013.
[41] Intel Corporation, “Performance evaluation of small cell on/off (R1-132933),” 3GPP TSG
RAN WG1 Meeting-74, Aug. 2013.
[42] M. Puterman, Markov Decision Process-Discrete Stochastic Dynamic Programming. John
Wiley and Sons, 1994.
[43] G. Auer, O. Blume, V. Giannini, I. Godor, M. A. Imran, Y. Jading, E. Katranaras, M. Olsson,
D Sabella, P. Skillermark, and W. Wajda, “Energy efficiency analysis of the reference
systems, areas of improvements and target breakdown,” EARTH D2.3, Tech. Rep., 2010.
[44] I. J. Lustig, R. E. Marsten, and D. F. Shanno, “Computational experience with a primaldual
interior point method for linear programming,” Linear Algebra Appl., vol. 152, pp.
191-222, Jul. 1991.
[45] G. Auer, V. Giannini, C. Desset, I. Godor, P. Skillermark, M. Olsson, M. Ali Imran, D.
Sabella, M. J. Gonzalez, O. Blume, and A. Fehske, “How much energy is needed to run a
wireless network?” IEEE Commun. Mag., vol. 18, no. 5, pp. 40-49, Oct. 2011.
[46] P. Ramezani and A. Jamalipour, “Toward the evolution of wireless powered communication
networks for the future Internet of Things,” IEEE Netw., vol. 31, no. 6, pp. 62–69,
Nov. 2017.
[47] K. Xiong, C. Chen, G. Qu, P. Fan, and K. Letaief, “Group cooperation with optimal resource
allocation in wireless powered communication networks,” IEEE Trans. Wireless
Commun., vol. 16, no. 6, pp. 3840–3853, Jun. 2017.
[48] K.-Y. Hsieh, F.-S. Tseng, and M.-L. Ku, “A spectrum and energy cooperation strategy in
hierarchical cognitive radio cellular networks,” IEEE Wireless Commun. Lett., vol. 5, no.
3, pp. 252–255, Jun. 2016.
[49] M. Zhang, K. Cumanan, J. Thiyagalingam, W. Wang, A. G. Burr, Z. Ding, and O. A. Dobre,
“Energy efficiency optimization for secure transmission in MISO cognitive radio network
with energy harvesting,” IEEE Access, vol. 7, pp. 126234–126252, Sep. 2019.
[50] H. Lim and T. Hwang, “User-centric energy efficiency optimization for MISO wireless
powered communications,” IEEE Trans. Wireless Commun., vol. 18, no. 2, pp. 864–878,
Feb. 2019.
[51] M. U. Kim and H. J. Yang, “Min-SINR maximization with DL SWIPT and UL WPCN
in multi-antenna interference networks,” IEEE Wireless Commun. Lett., vol. 6, no. 3, pp.
318–321, Jun. 2017.
[52] H. Jin, B. C. Jung, and V. C. M. Leung, “On the CDF-based scheduling for multi-cell uplink
networks,” in Proc. IEEE Commun. Conf., pp. 5012–5017, 2014.
[53] A. Almradi and P. Xiao, “Energy beamforming for MIMO WIPT relaying with arbitrary
correlation,” IEEE Access, vol. 6, pp. 36849–36862, 2018.
[54] H. Boche and M. Schubert, “A general duality theory for uplink and downlink beamforming,”
in Proc. IEEE Veh. Technol. Conf., 2002, pp. 87–91.
[55] S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U. K.: Cambridge Univ.
Press, 2004.
[56] E. K. P. Chong and S. H. Zak, An Introduction to Optimization. New York: Wiley, 2004.
[57] Z. Luo, W. Ma, A. M. So, Y. Ye, and S. Zhang, “Semidefinite relaxation of quadratic
optimization problems,” IEEE Signal Process. Mag., vol. 27, no. 3, pp. 20–34, May 2010.
[58] C. Helmberg, F. Rendl, R. Vanderbei, and H. Wolkowicz, “An interior-point method for
semidefinite programming,” SIAM J. Optim., vol. 6, no. 2, pp. 342–361, May 1996.