This study investigates a multi-carrier cognitive wireless powered communication network (CW-PCN) with a wirelessly powered primary user (PU). A two-stage cooperative protocol between the PU and the secondary user (SU) is adopted so that the PU can harvest energy from the SU while the SU gains transmission opportunities. It is assumed that the energy harvested by the PU can be accumulated for future usage, and the quality of service of the PU is guaranteed by satisfying the required minimum number of data bits for a given deadline. Herein, we maximize the SU rate by considering the time allocation, subcarrier allocation, and power allocation in both an offline setting (in which the future channel gains are known a priori) and an online setting (in which only the current channel gains are known). In the offline and online schemes, the maximization problem is solved using the block-coordinate descent method and the Lagrange duality method. The effectiveness of the proposed schemes is evaluated and verified via simulation experiments against benchmark schemes.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Zaidi SAR, Afzal A, Hafeez M, et al. Solar energy empowered 5G cognitive metro-cellular networks. IEEE Commun Mag, 2015, 53: 70–77
Xu D, Li Q. Price-based time and energy allocation in cognitive radio multiple access networks with energy harvesting. Sci China Inf Sci, 2017, 60: 108302
Mohjazi L, Dianati M, Karagiannidis G K, et al. RF-powered cognitive radio networks: technical challenges and limitations. IEEE Commun Mag, 2015, 53: 94–100
Xu D, Li Q. Joint power control and time allocation for wireless powered underlay cognitive radio networks. IEEE Wirel Commun Lett, 2017, 6: 294–297
Wang D, Ren P, Wang Y, et al. Energy cooperation for reciprocally-benefited spectrum access in cognitive radio networks. In: Proceedings of IEEE Global Communications Conference, Washington, 2014. 1320–1324
Shafie A El, Dhahir N Al, Hamila R. Cooperative access schemes for efficient SWIPT transmissions in cognitive radio networks. In: Proceedings of IEEE Global Communications Conference Workshops, San Diego, 2015. 1–6
Zhai C, Liu J, Zheng L. Cooperative spectrum sharing with wireless energy harvesting in cognitive radio networks. IEEE Trans Veh Technol, 2016, 65: 5303–5316
Zhai C, Chen H, Wang X, et al. Opportunistic spectrum sharing with wireless energy transfer in stochastic networks. IEEE Trans Commun, 2018, 66: 1296–1308
Xu D, Li Q. Cooperative resource allocation in cognitive radio networks with wireless powered primary users. IEEE Wirel Commun Lett, 2017, 6: 658–661
Xu D, Li Q. Resource allocation in cognitive wireless powered communication networks with wirelessly powered secondary users and primary users. Sci China Inf Sci, 2019, 62: 029303
Yang J, Yang Q, Shen Z, et al. Suboptimal online resource allocation in hybrid energy supplied OFDMA cellular networks. IEEE Commun Lett, 2016, 20: 1639–1642
Yousaf R, Ahmad R, Ahmed W, et al. A unified approach of energy and data cooperation in energy harvesting WSNs. Sci China Inf Sci, 2018, 61: 082303
Wang Z, Wang X, Aggarwal V. Transmission with energy harvesting nodes in frequency-selective fading channels. IEEE Trans Wirel Commun, 2016, 15: 1642–1656
Zhang B, Dong C, El-Hajjar M, et al. Outage analysis and optimization in single- and multiuser wireless energy harvesting networks. IEEE Trans Veh Technol, 2016, 65: 1464–1476
Yao Q, Huang A, Shan H, et al. Delay-aware wireless powered communication networks-energy balancing and optimization. IEEE Trans Wirel Commun, 2016, 15: 5272–5286
Morsi R, Michalopoulos D S, Schober R. Performance analysis of near-optimal energy buffer aided wireless powered communication. IEEE Trans Wirel Commun, 2018, 17: 863–881
López O L A, Fernández E M G, Souza R D, et al. Wireless powered communications with finite battery and finite blocklength. IEEE Trans Commun, 2018, 66: 1803–1816
Zhang R, Chen H, Yeoh P L, et al. Full-duplex cooperative cognitive radio networks with wireless energy harvesting. In: Proceedings of IEEE International Conference on Communications, Paris, 2017. 1–6
Hoang D T, Niyato D, Wang P, et al. Opportunistic channel access and RF energy harvesting in cognitive radio networks. IEEE J Sel Areas Commun, 2014, 32: 2039–2052
Hoang D T, Niyato D, Wang P, et al. Performance optimization for cooperative multiuser cognitive radio networks with RF energy harvesting capability. IEEE Trans Wirel Commun, 2015, 14: 3614–3629
Boyd S, Vandenberghe L. Convex Optimization. Cambridge: Cambridge University Press, 2004
Bland R G, Goldfarb D, Todd M J. The ellipsoid method: a survey. Oper Res, 1981, 29: 1039–1091
Bertsekas D P. Nonlinear Programming. Belmont: Athena Scientific Press, 1999
Potra F A, Wright S J. Interior-point methods. J Comput Appl Math, 2000, 124: 281–302
Ju H, Zhang R. Throughput maximization in wireless powered communication networks. IEEE Trans Wirel Commun, 2014, 13: 418–428
This work was supported by National Science and Technology Major Project of China (Grant No. 2017ZX03001008), Postdoctoral Research Plan of Jiangsu Province (Grant No. 1701167B), Postdoctoral Science Foundation of China (Grant No. 2017M621795), and NUPTSF (Grant Nos. NY218007, NY218026).
About this article
Cite this article
Xu, D., Li, Q. Cooperative resource allocation in cognitive wireless powered communication networks with energy accumulation and deadline requirements. Sci. China Inf. Sci. 62, 82302 (2019). https://doi.org/10.1007/s11432-018-9813-9
- wireless powered communication networks
- energy harvesting
- cognitive radio
- deadline constraint
- energy accumulation