本論文研製之異質性網路資源分配，6G次世代通訊設備系統是未來的趨勢，為此我們需要準備足夠的訊號發送源以應付6G次世代通訊的到來，在這過程中原有的4G/5G大型基地台仍可作為訊號傳送的來源，但缺點是頻譜的覆蓋率不足，因此需要開發許多微小型基地台(Small Cell)來填補訊號缺口，微小型基地台的優點是體積小，且佈建靈活，很方便能夠擺置在訊號源不足的地方。我的研究會考量到上述狀況，為了使6G次世代網路通訊協定能完美的銜接舊有的通訊系統，必須在通訊協定上做些改良與研究，當訊號封包碰上資訊遺失的問題，遇到訊號延遲時就需要判斷是什麼原因造成的，從模擬平台的建立來整理出一套可行的系統，希望能透過參數的調整來避免這樣的資源浪費。研究內容以模擬平台的順利運作和多參數連動調整後仍不失真的模擬結果為核心，並在模擬平台中分別建置LAA的基地台和Wi-Fi的基地台，讓兩種基地台同時運作，作為異質性網路偕同系統的核心，並從異質性網路運作系統中參數的變化研究出適當的參數設置，使得LAA基地台與Wi-Fi基地台在異質性網路中能順利運作。

The heterogeneous network resource allocation developed in this paper, 6G next-generation communication equipment system is the future trend, so we need to prepare enough signal transmission sources to cope with the arrival of 6G next-generation communication, in the process of the original 4G/5G Large-scale base stations can still be used as a source of signal transmission, but the disadvantage is that the spectrum coverage is insufficient, so many micro-base stations need to be developed to fill the signal gap. The advantages of micro-base stations are small size, flexible deployment, and very convenient It can be placed in places where the signal source is insufficient.

My research will take the above situation into consideration, hoping to avoid resource waste through parameter adjustment. The research content focuses on the smooth operation of the simulation platform and the undistorted simulation results after multi-parameter linkage adjustment. The base station of LAA and the base station of Wi-Fi are respectively built in the simulation platform, and the system is operated from the heterogeneity network. Appropriate parameter settings are studied through the changes of the parameters in the medium, so that the LAA base station and the Wi-Fi base station can operate smoothly in the heterogeneous network.

[1]M. Cavalcante, E. Almeida, R. D. Vieira, S. Choudhury, E. Tuomaala,K. Doppler, F. Chaves, R. C. D. Paiva, and F. Abinader, “Performance Evaluation of LTE and Wi-Fi Coexistence in Unlicensed Bands,” in IEEE 77th Vehicular Technology Conference, June 2013, pp. 1–6.
[2]Junjie Tan, Sa Xiao, Shiying Han, Ying-Chang Liang, and Victor C. M. Leung, “QoS-Aware User Association and Resource Allocation in LAA-LTE/ Wi-Fi Coexistence Systems”, IEEE Transaction on Wireless Communications, VOL. 18, NO. 4, April 2019
[3]B. Chen, J. Chen, Y. Gao and J. Zhang, "Coexistence of LTE-LAA and Wi-Fi on 5 GHz With Corresponding Deployment Scenarios: A Survey," in IEEE Communications Surveys & Tutorials, vol. 19, no. 1, pp. 7-32, Firstquarter 2017.
[4] S. Saadat, D. Chen, K. Luo, M. Feng and T. Jiang, "License assisted access-Wi-Fi coexistence with TXOP backoff for LTE in unlicensed band", China Commun., vol. 14, no. 3, pp. 1-14, Mar. 2017.
[5]Jie Xiao; Jun Zheng ; Liangyu Chu ; Qilei Ren(Oct. 2018). Performance Modeling of LAA LBT with Random Backoff and a Variable Contention Window, IEEE 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP), Hangzhou, China
[6]Chin-Ta Lin, Pu-Chen Wey, Chun-Chou Chien，2006，LBT with Random Backoff and a Variable,ICL,ECHNICAL,JOURNAH
http://faculty.stust.edu.tw/~cwycwy/951/N9590008.pdf
[7]Wipawin, N., Wongkaew, C., & Sarawanawong, J. (2015, August 20-24). Shouold OA journals be sealed?: Case of journals in Thai-Journal Citation Indax [Paper presentation]. World Library and Infonacation Congress: 84th IFLA General Conference and Assembly, Kuala Limpur, Malaysian. http://library.ifla.org/2192/1/163-chan-en.pdf
[8]K. Doppler, M. Rinne, C. Wijting, C. B. Ribeiro, and K. Hugl, "Device-to-device communication as an underlay to LTE-advanced networks," IEEE Communications Magazine, vol. 47, pp. 42-49, 2009.
[9]Y. S. Nasir and D. Guo, “Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,” IEEE J. Sel. Areas Commun., vol. 37, no. 10, pp. 2239–2250, Oct. 2019.
[10] M. Simsek, M. Bennis, and A. Czylwik, “Dynamic inter-cell interference coordination in HetNets: A reinforcement learning approach,” in Proc. IEEE Global Commun. Conf. (GLOBECOM), Anaheim, CA, USA, Dec. 2012, pp. 5446–5450.
[11] N. Bitar, M. O. Al Kalaa, S. J. Seidman and H. H. Refai, "On the Coexistence of LTE-LAA in the Unlicensed Band: Modeling and Performance Analysis", in IEEE Access, vol. 6, pp. 52668-52681, 2018, doi: 10.1109/ACCESS.2018.2870757.
[12] J. Xiao, J. Zheng, L. Chu and Q. Ren, "Performance Modeling and Analysis of the LAA Category-4 LBT Procedure," in IEEE Transactions on Vehicular Technology, vol. 68, no. 10, pp. 10045-10055, Oct. 2019, doi: 10.1109/TVT.2019.2933012.
[13] C. J. C. H. Watkins and P. Dayan. Q-learning. Machine Learning, 8:279–292, 1992.
[14] S. Toumi, M. Hamdi and M. Zaied, "An adaptive Q-learning approach to power control for D2D communications," 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), Hammamet, 2018, pp. 206-209, doi: 10.1109/ASET.2018.8379860.
[15]V. Maglogiannis, D. Naudts, A. Shahid and I. Moerman, "A Q-Learning Scheme for Fair Coexistence Between LTE and Wi-Fi in Unlicensed Spectrum," in IEEE Access, vol. 6, pp. 27278-27293, 2018, doi: 10.1109/ACCESS.2018.2829492.
[16] U. Challita, L. Dong and W. Saad, "Proactive Resource Management for LTE in Unlicensed Spectrum: A Deep Learning Perspective", IEEE Transactions on Wireless Communications, vol. 17, no. 7, pp. 4674-4689, July 2018.
[17] Junjie Tan, Sa Xiao, Shiying Han, Ying-Chang Liang, and Victor C. M. Leung, “QoS-Aware User Association and Resource Allocation in LAA-LTE/ Wi-Fi Coexistence Systems”, IEEE Transaction on Wireless Communications, VOL. 18, NO. 4, April 2019