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Optimal Time Switching-Based Policies for Efficient Transmit Power in Wireless Energy Harvesting Small Cell Cognitive Relaying Networks

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Abstract

In this paper, we consider a half-duplex decode-and-forward small cell cognitive relay network, in which the source and the relay node are allocated with spectrum shared by the macro cell primary transmitter (MPT). In order to develop a practical design, we propose two time switching-based policies to optimize the maximum transmit power at source and relay so-called Optimal Time for Transmit Power at Source and Optimal Time for Transmit Power at Relay related to wireless energy harvesting for the considered network, thanks to the advantages of MPT. Additionally, we provide closed-form expressions for outage probability for the proposed policies. Furthermore, to achieve more genuine understandings of the successful data transmission of the small cells, we also consider the delay-constraint throughput, the rate-energy trade-off and the average energy efficiency by giving numerical and simulation results.

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References

  1. Zhang, H., Jiang, C., Beaulieu, N., Chu, X., Wen, X., & Tao, M. (2014). Resource allocation in spectrum-sharing OFDMA femtocells with heterogeneous services. IEEE Transactions of Communications, 62(7), 2366–2377. https://doi.org/10.1109/TCOMM.2014.2328574.

    Article  Google Scholar 

  2. Ouyang, J., Zhu, W. P., Massicotte, D., & Lin, M. (2016). Energy efficient optimization for physical layer security in cognitive relay networks, In Proceedings of IEEE international conference on communications (ICC), May 2016, pp. 1–6. https://doi.org/10.1109/ICC.2016.7510895.

  3. Wang, X., Ho, P., & Chen, K. (2012). Interference analysis and mitigation for cognitive-empowered femtocells through stochastic dual control. IEEE Transactions on Wireless Communications, 11(6), 2065–2075. https://doi.org/10.1109/TWC.2012.032712.110197.

    Article  Google Scholar 

  4. Xu, C., Zheng, M., Liang, W., Yu, H., & Liang, Y. C. (2016). Outage performance of underlay multihop cognitive relay networks with energy harvesting. IEEE Communications Letters, 20(6), 1148–1151. https://doi.org/10.1109/LCOMM.2016.2547985.

    Article  Google Scholar 

  5. Hecke, J. V., Fiorentino, P. D., Lottici, V., Giannetti, F., Vandendorpe, L., & Moeneclaey, M. (2017). Distributed dynamic resource allocation for cooperative cognitive radio networks with multi-antenna relay selection. IEEE Transactions on Wireless Communications, 16(99), 1236–1249. https://doi.org/10.1109/TWC.2016.2642942.

    Article  Google Scholar 

  6. Le, L. B., Niyato, D., Hossain, E., Kim, D. I., & Hoang, D. T. (2013). QoS-aware and energy-efficient resource management in OFDMA femtocells. IEEE Transactions on Wireless Communications, 12(1), 180–194. https://doi.org/10.1109/TWC.2012.120412.120141.

    Article  Google Scholar 

  7. Dai, J., & Wang, S. (2017). Clustering-based spectrum sharing strategy for cognitive radio networks. IEEE Journal on Selected Areas in Communications, 35(1), 228–237. https://doi.org/10.1109/JSAC.2016.2633698.

    Google Scholar 

  8. Huang, X., Liu, S., Li, Y., Zhu, F., & Chen, Q. (2016). Dynamic cell selection and resource allocation in cognitive small cell networks, IEEE 27th annual international symposium on personal, indoor, and mobile radio communications (PIMRC), 2016, pp. 1–8. https://doi.org/10.1109/PIMRC.2016.7794899.

  9. Sardellitti, S., & Barbarossa, S. (2013). Joint optimization of collaborative sensing and radio resource allocation in small-cell networks. IEEE Transactions on Signal Processing, 61(18), 4506–4520. https://doi.org/10.1109/TSP.2013.2267737.

    Article  MathSciNet  Google Scholar 

  10. H. Huang, Z. Li, B. Ai, G.Wang, & M. S. Obaidat, (2016). Impact of hardware impairment on spectrum underlay cognitive multiple relays network, In Proceedings of IEEE international conference on communications (ICC), 2016, pp. 1–6. https://doi.org/10.1109/ICC.2016.7511543.

  11. Qian, L. P., Feng, G., & Leung, V. C. M. (2016). Optimal transmission policies for relay communication networks with ambient energy harvesting relays. IEEE Journal on Selected Areas in Communications, 34(12), 3754–3768. https://doi.org/10.1109/JSAC.2016.2621356.

    Article  Google Scholar 

  12. Nguyen, H.-S., Do, D.-T., Bui, A.-H., & Voznak, M. (2017). Self-powered wireless two-way relaying networks: Model and throughput performance with three practical schemes, Wireless Personal Communications (Springer), pre-published, pp. 1–19, (Q4, SCIE). https://doi.org/10.1007/s11277-017-4526-3

  13. Adeli, M. H., Mohammadian, F., Taherpour, A., & Khattab, T. (2016). Optimized collaborative spectrum sensing in energy harvesting cognitive radio networks, In Proceedings of IEEE wireless communications and networking conference (WCNC), April 2016, pp. 1–7. https://doi.org/10.1109/WCNC.2016.7564792.

  14. He, P., & Zhao, L. (2015). Optimal power control for energy harvesting cognitive radio networks, In Proceedings of IEEE international conference on communications (ICC), June 2015, pp. 92–97. https://doi.org/10.1109/ICC.2015.7248304

  15. Wang, S., Ge, M., & Zhao, W. (2013). Energy-efficient resource allocation for OFDM-based cognitive radio networks. IEEE Transactions on Communications, 61(8), 3181–3191. https://doi.org/10.1109/TCOMM.2013.061913.120878.

    Article  Google Scholar 

  16. Atapattu, S., & Evans, J. (2016). Optimal Energy Harvesting Protocols for Wireless Relay Networks. IEEE Transactions on Wireless Communications, 15(8), 5789–5803. https://doi.org/10.1109/TWC.2016.2569097.

    Article  Google Scholar 

  17. Zheng, M., Liang, W., & Yu, H. (2016). Harvesting-throughput tradeoff for CDMA-based underlay cognitive radio networks with wireless energy harvesting. IEEE Systems Journal,. https://doi.org/10.1109/JSYST.2016.2636278.

    Google Scholar 

  18. Do, D.-T., & Nguyen, H.-S. (2016). A tractable approach to analyze the energy-aware two-way relaying networks in presence of co-channel interference. EURASIP Journal on Wireless Communications and Networking, 2016, 271. https://doi.org/10.1186/s13638-016-0777-z.

    Article  Google Scholar 

  19. Liu, L., Zhang, R., & Chua, K. C. (2013). Wireless information and power transfer: a dynamic power splitting approach. IEEE Transactions on Communications, 61(9), 3990–4001. https://doi.org/10.1109/TCOMM.2013.071813.130105.

    Article  Google Scholar 

  20. Nguyen, H. S., Do, D. T., & Voznak, M. (2016). Two-way relaying networks in green communications for 5G: Optimal throughput and tradeoff between relay distance on power splitting-based and time switching-based relaying SWIPT. International Journal of Electronics and Communications, 70(3), 1637–1644. https://doi.org/10.1016/j.aeue.2016.10.002.

    Article  Google Scholar 

  21. Xiong, K., Fan, P., Zhang, C., & Letaief, K. B. (2015). Wireless information and energy transfer for two-hop non-regenerative MIMO-OFDM relay networks. IEEE Journal on Selected Area in Communications, 33(8), 1595–1611. https://doi.org/10.1109/JSAC.2015.2391931.

    Google Scholar 

  22. Gradshteyn, I. S., & Ryzhik, I. M. (1980). Table of Integrals, Series, and Products (4th ed.). Campbridge: Academic Press Inc.

    MATH  Google Scholar 

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Acknowledgements

This research was funded by the grant SGS Reg. No. SP2017/174 conducted at VSB-Technical University of Ostrava, Czech Republic.

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Authors and Affiliations

  1. Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hoang-Sy Nguyen

  2. Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Thanh-Sang Nguyen & Miroslav Voznak

  3. Binh Duong University, Thu Dau Mot City, Binh Duong Province, Vietnam

    Minh-Tung Nguyen

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  1. Hoang-Sy Nguyen
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  2. Thanh-Sang Nguyen
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  3. Minh-Tung Nguyen
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  4. Miroslav Voznak
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Correspondence to Miroslav Voznak.

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Nguyen, HS., Nguyen, TS., Nguyen, MT. et al. Optimal Time Switching-Based Policies for Efficient Transmit Power in Wireless Energy Harvesting Small Cell Cognitive Relaying Networks. Wireless Pers Commun 99, 1605–1624 (2018). https://doi.org/10.1007/s11277-018-5296-2

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