Simulasi Distributed Binary Power Allocation Pada Sistem Radio Kognitif

  • erwan darmawan Universitas Faletehan
  • Iqbal Fernando Universitas Faletehan
Keywords: Cognitive Radio Network, Distributed Binary Power Allocation

Abstract

Cognitive radio is a technology for wireless communication networks that employ the upcoming Dynamic Spectrum Access ( DSA ) . DSA technology allows users who do not have a license called the secondary spectrum users to use the licensed spectrum that primary users while not in use. Application of DSA by secondary users to improve the spectrum utilization efficiency without disrupting or causing interference to the primary user. Later developed into a multi - user cognitive radio or cognitive radio networks use frequency spectrum together with a primary user ( PU ).

Methods switch 'off' the user who gives the biggest interference to PU is the best method with the greatest increase in performance, both the capacity and the number of active SU while the combination of methods switch 'off' the user who raised the largest overall interference with the method switches 'off' user given biggest interference to the PU is an alternative method that shows the consistency of performance improvement in the number of potential users over 10 and able to dominate the entire method over another is begun saturation and decreased capacity.

Abstracts are made in two languages, English and Bahasa Indonesia. Abstract more about background, purpose, up to, the results of research, and manai research. Abstract contains up to 250 words, single write spaces with italics (Italics) for English abstracts. Below the abstract are listed keywords consisting of six words, where the first word is again the forward. Abstract in Indonesian can be a translation of an English translation. Tiff editor for abstract syncing for reasons of abstract content

References

1. Akyildiz, I., Won-Yeol, L., Vuran, M.,&Mohanty, S.(2006). NeXt generation/dynamic spectrumaccess/cognitive radio wireless networks: A survey.ComputerNetworks Journal, pp 2127-2159. Elsevier.
2. Alaydrus, Mudrik. (2010). Cognitive Radio: Sistim Radio Cerdas. InComTech, Jurnal Telekomunikasi danKomputer, 1( 2).
3. Bayat, Siavash., Louie,Raymond H. Y., Li, Yonghui.,&Vucetic,Branka. (2011). Cognitive Radio Relay Networks with MultiplePrimary and Secondary Users: Distributed Stable Matching Algorithms for Spectrum Access, IEEE ICC 2011 proceedings.
4. Chen, Kwang-Cheng., Chen, Peng-Yu., Prasad, Neeli., Liang, Ying-Chang.,& Sun, Sumei.(2009). Trusted cognitive radio networking, WIRELESS COMMUNICATIONS AND MOBILE COMPUTING, Wiley Interscience.
5. COST Action 231.(1999). Digital mobile radio towards future generation systems, finalreport. Technical report, COST Telecom.
6. Devroye, Natasha, Mai Vu, & Tarokh, Vahid. (2008). Cognitive radio networks: Highlights of information theoretic limits, models and design. IEEE Signal Processing Magazine 25(6): 12-23.
7. Dybdahl, S. (2007). Radio Resource Allocation for Increased Capacity in Cellular Networks, Norwegian University of Science and Technology.
8. Garcia, Ivan. (2010). Interference Management in Cognitive Radio Systems, Aalto University, Finland.
9. He, Hao., & Li, Shaoqian. (2010). Distributed Relay Selection and Channel Choice in Cognitive Radio Network, International Journal of Information and Communication Engineering, 6:3.
10. Ifeh,Kennedy. (2012).Transmit Power Control for Cognitive Radio Networks:Challenges, Requirements, and Options, University of the Witwatersrand, Johannesburg, South Africa.
11. Li, Y., Wang, P., &Niyato, D. (2009).Optimal Power Allocation for Secondary Users in Cognitive Relay Networks, Nanyang Technological University, Singapore.
12. Luo, Changqing ., Yu, F. Richard., Ji, Hong.,& Leung, Victor C.M. (2010). Distributed Relay Selection and Power Control inCognitive Radio Networks with Cooperative Transmission, IEEE ICC 2010 proceedings.
13. Mitola III, Joseph. (2000). Cognitive radio: An integrated agent architecture for software defined radio. Royal Inst. Technology. (KTH), Stockholm, Sweden.
14. M. Haddad, A.M. Hayar, G.E. Øien, S.G. Kiani. (2008).Uplink distributedbinary power allocation for cognitive radio networks, proceedingof CrownCom 2008, Singapore.
15. Nieto, R., & Ortega, D. (2008). Power Allocation in Cognitive Radio, Norwegian Univ. of Science and Technology, Norway.
16. Wyglinski, A., Nekovee, M., &Hou, Y.(2008). Cognitive RadioCommunications and NetworksPrinciples and Practice, Elsevier.
17. Zayen, B., Haddad, M., Hayar, A., &Øien, G. (2008). Binary power allocation for cognitive radio networks with centralized and distributed user selection strategies, Journal of Physical Communication, 1(3),pp. 183-193, Elsevier.
18. Anders Gjendemsjø. Simulating Wireless Communications α-version. Tutorial on simulations for wireless communications.
19. Denny setiawan, (2010).Alokasi frekuensikebijakan dan perencanaanspektrum Indonesia.
Published
2023-08-11
How to Cite
darmawan, erwan, & Fernando, I. (2023). Simulasi Distributed Binary Power Allocation Pada Sistem Radio Kognitif. Jurnal Ilmiah Sains Dan Teknologi, 7(2), 99-111. https://doi.org/10.47080/saintek.v7i2.2709