•  
  •  
 

Abstract

In heterogeneous networks (HetNets) where femtocell base stations (FBSs) are deployed within the radio coverage of macrocell base stations (MBSs) to increase network capacity, co-channel interference limits overall system performance with universal frequency reuse. This paper investigates new distributed downlink discrete power control scheme for FBSs in HetNets with FBSs cooperation. The objective of the proposed power control scheme is to maximize the number of simultaneous FBSs transmissions in a single transmission wireless channel where each FBS is allowed to transmit only if the signal-to-interference-noise ratio (SINR) requirements for both FBSs and MBS users are satisfied. We apply a stochastic learning automata technique to FBSs where each FBS is treated as a learning automaton and maintains a probability vector to select its discrete transmit power. During the learning process, each FBS adjusts its probability vector based on the feedback from FGW that indicates the number of FBSs transmissions that can be supported under the SINR requirement constraints of FUEs and MUEs. Simulation results show the proposed algorithm can achieve more than twice the number of simultaneous FBS transmissions achieved by existing schemes in the literature.

Bahasa Abstract

Kontrol Daya Terpisah dalam Jaringan Heterogen. Dalam jaringan heterogen (HetNets) di mana BTS femtocell (FBS) dikerahkan dalam cakupan radio BTS macrocell (MBS) untuk meningkatkan kapasitas jaringan, interferensi saluran bersama (co-channel) membatasi kinerja sistem secara keseluruhan dengan menggunakan kembali frekuensi universal. Makalah ini menyelidiki skema kontrol daya terpisah downlink yang baru didistribusikan untuk FBS di HetNets dengan kerjasama sejumlah FBS. Tujuan dari skema kontrol listrik yang diusulkan adalah untuk memaksimalkan jumlah transmisi FBS simultan dalam saluran nirkabel transmisi tunggal di mana setiap FBS diperbolehkan untuk mengirimkan hanya jika persyaratan rasio signal-to-interference-noise (SINR) untuk kedua FBS dan pengguna MBS terpenuhi. Kami menerapkan teknik stochastic learning automata untuk FBS, di mana setiap FBS diperlakukan sebagai learning automaton dan mempertahankan vektor probabilitas untuk memilih daya pancar terpisah. Selama proses belajar, masing-masing FBS menyesuaikan vektor probabilitas berdasarkan umpan balik dari FGW yang menunjukkan jumlah transmisi FBS yang dapat didukung di bawah kendala persyaratan SINR dari FUE dan MUE. Hasil simulasi menunjukkan algoritma yang diusulkan dapat mencapai lebih dari dua kali jumlah transmisi FBS simultan yang dicapai berbagai skema lain yang ada dalam literatur.

References

  1. G. Mansfield, ATT, London, U.K., 2008.
  2. D. Lopez-Perez, A. Valcarce, G. de la Roche, J. Zhang, IEEE Comm. Mag. 47/9 (2009) 41.
  3. V. Chandrasekhar, J.G. Andrews, A. Gatherer, IEEE Comm. Mag. 46/9 (2008) 59.
  4. P. Lin, J. Zhang, Y. Chen, Q. Zhang, IEEE Trans. Wireless Commun. 18/3 (2011) 64.
  5. H. Claussen, Proceeding IEEE International Symposium Personal, Indoor, & Mobile Radio Comm, Athens, Greece, 2007, p.5.
  6. H.S. Jo, C. Mu, J. Moon, J.G. Yook, IEEE Trans. Wirel. Commun. 8/10 (2009) 4906.
  7. M. Morita. Y. Matsunaga, K. Hamabe, IEEE VTC’10. 6-9 (2010) 5.
  8. X. Li, L. Qian, D. Kataria, Proceedings on 43rd Ann. Conference Inf. Sci. Syst. (CISS), Baltimore, 2009, p.383.
  9. V. Chandrasekhar, J.G. Andrews, T. Muharemovic, Z. Shen, A. Gatherer, IEEE Trans. Wireless Commun. 8/8 (2009) 4316.
  10. N. Bambos, S.C. Chen, G.J. Pottie, IEEE/ACM Trans. Netw. 8/5 (2000) 583.
  11. W. Hardjawana, B. Vucetic, Y. Li, IEEE J. 3/6 (2009) 1079.
  12. K.S. Narendra, M.A.L. Thathachar, IEEE Trans. Syst. Man. Cybern. SMC-4/4 (1974) 323.
  13. Y. Akaiwa, Introduction to Digital Mobile Communication, 2nd ed., John Wiley & Sons, Inc,
  14. New Jersey, 2015, p.648.
  15. 3GPP TR 36.814 V 9.0.0, Further advancements for E-UTRA physical layer aspects, Technical Report, 3GPP Organizational Partners (ARIB, ATIS, CCSA, ETSI, TTA, TTC), March 2010. www.qtc.jp/3GPP/Specs/36814-900.pdf.
  16. Y. Xing, R. Chandramouli, IEEE/ACM Trans. Netw. 16/4 (2008) 932.
  17. Y. Xu, J. Wang, Q. Wu, A. Anpalagan, Y.D. Yao, IEEE Trans. Wireless Commun. 11/4 (2012) 1380.
  18. R.G. Neville, C.R. Nicol, P. Mars, Electron. Lett. 14/13 (1978) 396.
  19. P. Varaiya, IEEE Control Syst. 28 (2008) 126.
  20. M.A.L. Thathachar, V.V. Phansalkar, IEEE Trans. Syst. Man. Cybern. 25/11 (1995) 1459.
  21. V.V. Phansalkar, Ph.D Thesis, Department of Electrical Engineering, Indian Institute of ScienceEducation and Research Pune, India, 1991.
  22. Z. Han, D. Niyato, W. Saad, T. Basar, A. Hjorungnes, Game Theory in Wireless and
  23. Communication Networks: Theory, Models and Applications, Cambridge University Press, UK, 2011, p.554.
  24. P.S. Sastry, V.V. Phansalkar, M.A.L. Thathachar, Decentralized learning of Nash equilibria in multiperson stochastic games with incomplete information, IEEE Trans. Syst. Man. Cybern. 24/5 (1994) 769.
  25. International Telecommunication Union (ITU-R). Guidelines for Evaluation of Radio Interface Technologies for IMT-Advanced, REPORT ITU-R M.2135, Geneva, 2008, p.72.
  26. M. Chiang, P. Hande, T. Lan, C.W. Tan, Power Control in Wireless Cellular Networks, now Publishers Inc, USA, 2008, p.158.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.