Variation of Distributed Power Control Algorithm in Co-Tier Femtocell Network
Keywords:
Co-Tier Femtocell Network, Convergence, Distributed Power Control, Feasibility, Power Treatment
Abstract
The wireless communication network has seen rapid growth, especially with the widespread use of smartphones, but resources are increasingly limited, especially indoors. Femtocell, a spectrum-efficient small cellular network solution, faces challenges in distributed power control (DPC) when deployed with distributed users, impacting power levels, and causing interference in the main network. The aim of this research is optimizing user power consumption in co-tier femtocell networks by using the user power treatment. This study proposed the Distributed Power Control (DPC) variation methods such as Distributed Constrained Power Control (DCPC), Half Distributed Constrained Power Control (HDCPC), and Generalized Distributed Constrained Power Control (GDCPC) in co-tier femtocell network. The research examines scenarios where user power converges but exceeds the maximum threshold or remains semi-feasible, considering factors like number of users, distance, channel usage, maximum power values, non-negative power vectors, Signal-to-Interference-plus-Noise Ratio (SINR), and link gain matrix values. In Distributed Power Control (DPC), distance and channel utilization affect feasibility conditions: feasible, semi-feasible, and non-feasible. The result shows that Half Distributed Constrained Power Control (HDCPC) is more effective than Distributed Constrained Power Control (DCPC) in semi-feasible conditions due to its efficient power usage and similar Signal-to-Interference-plus-Noise Ratio (SINR). Half Distributed Constrained Power Control (HDCPC) is also easier to implement than Generalized Distributed Constrained Power Control (GDCPC) as it does not require user deactivation when exceeding the maximum power limit. Distributed Power Control (DPC) variations can shift the power and Signal-to-Interference-plus-Noise Ratio (SINR) conditions from non-convergence to convergence at or below the maximum power level. We concluded that the best performance of Distributed Power Control (DPC) is Half Distributed Constrained Power Control (HDCPC).
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References
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[19] O. Alamu, A. Gbenga-Ilori, M. Adelabu, A. Imoize, and O. Ladipo, “Energy efficiency techniques in ultra-dense wireless heterogeneous networks: An overview and outlook,” Eng. Sci. Technol. Int. J., vol. 23, no. 6, pp. 1308–1326, Dec. 2020, https://doi.org/10.1016/j.jestch.2020.05.001 [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2215098619328745?via%3Dihub
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[22] F. H. Costa Neto, D. Costa Araujo, M. Pontes Mota, T. Maciel, and A. De Almeida, “Uplink Power Control Framework Based on Reinforcement Learning for 5G Networks,” IEEE Trans. Veh. Technol., vol. 70, no. 6, pp. 5734–5748, Jun. 2021, https://doi.org/10.1109/TVT.2021.3074892 [Online]. Available: https://ieeexplore.ieee.org/document/9410444
[23] A. F. Isnawati, “Feasibility Analysis of Distributed Power Control System for Cognitive Radio Networks,” J. Nas. Tek. ELEKTRO, vol. 11, no. 1, pp. 29–35, Mar. 2022, https://doi.org/10.25077/jnte.v11n1.994.2022 [Online]. Available: https://jnte.ft.unand.ac.id/index.php/jnte/article/view/994
[24] A. F. Isnawati and M. A. Afandi, “Performance Analysis of Game Theoretical Approach for Power Control System in Heterogeneous Network,” Int. J. Intell. Eng. Syst., vol. 15, no. 3, pp. 397–405, Jun. 2022, http://dx.doi.org/10.22266/ijies2022.0630.33 [Online]. Available: https://inass.org/wp-content/uploads/2022/01/2022063033-2.pdf
[25] X. Li, J. Fang, W. Cheng, H. Duan, Z. Chen, and H. Li, “Intelligent Power Control for Spectrum Sharing in Cognitive Radios: A Deep Reinforcement Learning Approach,” IEEE Access, vol. 6, pp. 25463–25473, 2018, https://doi.org/10.1109/ACCESS.2018.2831240 [Online]. Available: https://ieeexplore.ieee.org/document/8352517
[2] A. Nedić and J. Liu, “Distributed Optimization for Control,” Annu. Rev. Control Robot. Auton. Syst., vol. 1, no. 1, pp. 77–103, May 2018, https://doi.org/10.1146/annurev-control-060117-105131 [Online]. Available: https://asu.elsevierpure.com/en/publications/distributed-optimization-for-control
[3] H. Hua, Z. Wei, Y. Qin, T. Wang, L. Li, and J. Cao, “Review of distributed control and optimization in energy internet: From traditional methods to artificial intelligence‐based methods,” IET Cyber-Phys. Syst. Theory Appl., vol. 6, no. 2, pp. 63–79, Jun. 2021, https://doi.org/10.1049/cps2.12007 [Online]. Available: https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cps2.12007
[4] S. Najeh and A. Bouallegue, “Distributed vs centralized game theory-based mode selection and power control for D2D communications,” Phys. Commun., vol. 38, p. 100962, Feb. 2020, https://doi.org/10.1016/j.phycom.2019.100962 [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S1874490719303064?via%3Dihub
[5] R. Aslani and M. Rasti, “A Distributed Power Control Algorithm for Energy Efficiency Maximization in Wireless Cellular Networks,” IEEE Wirel. Commun. Lett., vol. 9, no. 11, pp. 1975–1979, Nov. 2020, https://doi.org/10.1109/LWC.2020.3010156 [Online]. Available: https://ieeexplore.ieee.org/document/9143131
[6] Z. Liu, Y. Yuan, H. Yuan, and X. Guan, “Power Allocation Based on Proportional-Integral Controller in Femtocell Networks With Consideration of Maximum Power Constraint,” IEEE Syst. J., vol. 13, no. 1, pp. 88–97, Mar. 2019, https://doi.org/10.1109/JSYST.2018.2794508 [Online]. Available: https://ieeexplore.ieee.org/document/8279391
[7] O. Sevim, H. Y. Oksuz, and M. Akar, “Joint Frequency and Power Control for Self–Organizing OFDMA Femtocell Networks,” IEEE Trans. Veh. Technol., vol. 69, no. 5, pp. 5089–5101, May 2020, https://doi.org/10.1109/TVT.2020.2978945 [Online]. Available: https://ieeexplore.ieee.org/document/9027963
[8] Z. Li, Z. Li, and Z. Ding, “Distributed Generalized Nash Equilibrium Seeking and Its Application to Femtocell Networks,” IEEE Trans. Cybern., vol. 52, no. 4, pp. 2505–2517, Apr. 2022, https://doi.org/10.1109/tcyb.2020.3004635 [Online]. Available: https://ieeexplore.ieee.org/document/9146360
[9] S. Alotaibi, “Femtocell Networks Interference Management Approaches,” Int. J. Comput. Sci. Netw. Secur., vol. 22, no. 4, pp. 329–339, Apr. 2022, https://doi.org/10.22937/IJCSNS.2022.22.4.39 [Online]. Available: http://paper.ijcsns.org/07_book/202204/20220439.pdf
[10] A. F. Isnawati, J. Hendry, and E. F. Cahyadi, “Coverage Planning for Co-tier Femtocell Networks Using Voronoi Diagram and Gradient-based Optimization Method,” Int. J. Intell. Eng. Syst., vol. 13, no. 4, pp. 389–398, Aug. 2020, http://dx.doi.org/10.22266/ijies2020.0831.34 [Online]. Available: https://www.inass.org/2020/2020083134.pdf
[11] S. Alotaibi, “Radio Resource Scheduling Approach For Femtocell Networks,” Int. J. Comput. Sci. Netw. Secur., vol. 22, no. 4, pp. 394–400, Apr. 2022, https://doi.org/10.22937/IJCSNS.2022.22.4.46 [Online]. Available: http://paper.ijcsns.org/07_book/202204/20220446.pdf
[12] M. S. Al-omari, M. A. Alomari, A. R. Ramli, A. Sali, R. S. Azmir, and M. H. Yusoff, “Effects of Femtocell Ultradense Deployment on Downlink Performance in LTE Heterogeneous Networks,” Wirel. Commun. Mob. Comput., vol. 2021, pp. 1–21, Sep. 2021, https://doi.org/10.1155/2021/2735935 [Online]. Available: https://onlinelibrary.wiley.com/doi/10.1155/2021/2735935
[13] T. U. Hassan and F. Gao, “An Active Power Control Technique for Downlink Interference Management in a Two-Tier Macro–Femto Network,” Sensors, vol. 19, no. 9, p. 2015, Apr. 2019, https://doi.org/10.3390/s19092015 [Online]. Available: https://www.mdpi.com/1424-8220/19/9/2015
[14] Y. Liu, L. Hao, Z. Liu, K. Sharif, Y. Wang, and S. K. Das, “Mitigating Interference via Power Control for Two-Tier Femtocell Networks: A Hierarchical Game Approach,” IEEE Trans. Veh. Technol., vol. 68, no. 7, pp. 7194–7198, Jul. 2019, https://doi.org/10.1109/TVT.2019.2916715 [Online]. Available: https://ieeexplore.ieee.org/document/8713889
[15] R. Aljijakli and K. Abdullah, “Cross-Tier Interference Avoidance Technique for LTE-A Femtocell Networks Using Fractional Frequency Reuse,” in 2020 IEEE 5th International Symposium on Telecommunication Technologies (ISTT), Shah Alam, Malaysia: IEEE, Nov. 2020, pp. 117–122. https://doi.org/10.1109/ISTT50966.2020.9279383 [Online]. Available: https://ieeexplore.ieee.org/document/9279383
[16] R. Nikbakht, R. Mosayebi, and A. Lozano, “Uplink Fractional Power Control and Downlink Power Allocation for Cell-Free Networks,” IEEE Wirel. Commun. Lett., vol. 9, no. 6, pp. 774–777, Jun. 2020, https://doi.org/10.1109/LWC.2020.2969404 [Online]. Available: https://ieeexplore.ieee.org/document/8968623
[17] D. Widiatmoko, A. Aripriharta, K. Kasiyanto, D. Irmanto, and M. Wahyu Prasetyo, “Power Efficiency using Bank Capacitor Regulator on Field Service Shoes with Fast Charge Method,” MATRIK J. Manaj. Tek. Inform. Dan Rekayasa Komput., vol. 23, no. 2, pp. 273–284, Feb. 2024, https://doi.org/10.30812/matrik.v23i2.3494 [Online]. Available: https://journal.universitasbumigora.ac.id/index.php/matrik/article/view/3494
[18] A. F. Isnawati, W. Pamungkas, and J. Hendry, “Power Control Game Performance in Cognitive Femtocell Network,” J. Commun., vol. 14, no. 2, pp. 121–127, Feb. 2019, http://dx.doi.org/10.12720/jcm.14.2.121-127 [Online]. Available: https://www.jocm.us/index.php?m=content&c=index&a=show&catid=217&id=1319
[19] O. Alamu, A. Gbenga-Ilori, M. Adelabu, A. Imoize, and O. Ladipo, “Energy efficiency techniques in ultra-dense wireless heterogeneous networks: An overview and outlook,” Eng. Sci. Technol. Int. J., vol. 23, no. 6, pp. 1308–1326, Dec. 2020, https://doi.org/10.1016/j.jestch.2020.05.001 [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2215098619328745?via%3Dihub
[20] A. F. Isnawati and M. Aly Afandi, “Game Theoretical Power Control in Heterogeneous Network,” in 2021 9th International Conference on Information and Communication Technology (ICoICT), Yogyakarta, Indonesia: IEEE, Aug. 2021, pp. 149–154. http://dx.doi.org/10.1109/ICoICT52021.2021.9527439 [Online]. Available: https://ieeexplore.ieee.org/document/9527439
[21] W. Lee, T.-W. Ban, and B. C. Jung, “Distributed Transmit Power Optimization for Device-to-Device Communications Underlying Cellular Networks,” IEEE Access, vol. 7, pp. 87617–87633, 2019, https://doi.org/10.1109/ACCESS.2019.2926310 [Online]. Available: https://ieeexplore.ieee.org/document/8753530
[22] F. H. Costa Neto, D. Costa Araujo, M. Pontes Mota, T. Maciel, and A. De Almeida, “Uplink Power Control Framework Based on Reinforcement Learning for 5G Networks,” IEEE Trans. Veh. Technol., vol. 70, no. 6, pp. 5734–5748, Jun. 2021, https://doi.org/10.1109/TVT.2021.3074892 [Online]. Available: https://ieeexplore.ieee.org/document/9410444
[23] A. F. Isnawati, “Feasibility Analysis of Distributed Power Control System for Cognitive Radio Networks,” J. Nas. Tek. ELEKTRO, vol. 11, no. 1, pp. 29–35, Mar. 2022, https://doi.org/10.25077/jnte.v11n1.994.2022 [Online]. Available: https://jnte.ft.unand.ac.id/index.php/jnte/article/view/994
[24] A. F. Isnawati and M. A. Afandi, “Performance Analysis of Game Theoretical Approach for Power Control System in Heterogeneous Network,” Int. J. Intell. Eng. Syst., vol. 15, no. 3, pp. 397–405, Jun. 2022, http://dx.doi.org/10.22266/ijies2022.0630.33 [Online]. Available: https://inass.org/wp-content/uploads/2022/01/2022063033-2.pdf
[25] X. Li, J. Fang, W. Cheng, H. Duan, Z. Chen, and H. Li, “Intelligent Power Control for Spectrum Sharing in Cognitive Radios: A Deep Reinforcement Learning Approach,” IEEE Access, vol. 6, pp. 25463–25473, 2018, https://doi.org/10.1109/ACCESS.2018.2831240 [Online]. Available: https://ieeexplore.ieee.org/document/8352517
Published
2024-11-06
How to Cite
Harahap, F. R., Isnawati, A. F., & Ni’amah, K. (2024). Variation of Distributed Power Control Algorithm in Co-Tier Femtocell Network. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 24(1), 39-60. https://doi.org/https://doi.org/10.30812/matrik.v24i1.3992
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