The week's pick
Random Articles
Reseach Article
Medium Access Probability of Cognitive Radio Network at 1900 MHz and 2100 MHz
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 124 - Number 5 |
| Year of Publication: 2015 |
| Authors: Risala Tasin Khan, Md. Imdadul Islam, M.R. Amin |
10.5120/ijca2015905490
|
Risala Tasin Khan, Md. Imdadul Islam, M.R. Amin . Medium Access Probability of Cognitive Radio Network at 1900 MHz and 2100 MHz. International Journal of Computer Applications. 124, 5 ( August 2015), 42-45. DOI=10.5120/ijca2015905490
Abstract
Conventionally fading analysis of wireless LAN or MAN means small scale fading i.e. wide fluctuation of received signal with small variation of time and distance. In analysis of fading channel we consider the received signal in power, voltage or SNR as a random variable then statistical probability density function (pdf) like Rayleigh, Rician or Nakagami-m is used to get the probability of different phenomena. Most of the pdf is governed by two parameters: mean and variance of the random variable. In recent literature the mean value is taken constant but in this paper we consider the mean value as a slowly varying random variable and depend on the parameters of large scale fading. In this paper the concept of large and small scale fading is combined, in analysis of performance of cognitive radio network in context of medium access probability specially at 1900MHz and 2100MHz.
References
- “Report of the spectrum efficiency group”, FCC Spectrum Policy Task Force, Report, November 2002.
- M. M. Buddhikot, “Understanding dynamic spectrum access: models, taxonomy and challenges”, IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), pp. 649-663, April 2007
- I. Akyildiz, W. Lee, M. Vuran and S. Mohanty, “Next Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey,” Comp. Networks, Vol. 50, no. 13, pp. 2127-2159, 2006.
- Steven M. Kay, “Fundamentals of Statistical Signal Processing”, Volume II, Pearson
- Zhiqiang Li, F.R.Yu, Minyi Huang, “A Distributed Consensus-Based Cooperative Spectrum Sensing Scheme in Cognitive Radios,” IEEE Trans. Veh. Technol., vol. 59, no. 1, pp. 383-393, Jan. 2010
- Yuli Yang, Sonia Aissa, “Cross-Layer Combining of Information-Guided Transmission with Network Coding Relaying for Multiuser Cognitive Radio System,” IEEE Wireless Commun. Lett., vol.2, no. 1, Feb. 2013.
- Weijia Han, Jiandong Li, Qin Liu and Linjing Zhao, “Spatial False Alarms in Cognitive Radio,” IEEE Commun. Lett., vol. 15, no. 5, pp. 518-520, May, 2011.
- Rezwan Khan, Md. Imdadul Islam, and M. R. Amin, “Determination of Total Medium Access Probability of Cognitive Radio Under Rayleigh and Nakagami-m Fading Channels,” IJSCE, vol. 2, issue. 2, July 2012.
- Risala T. Khan, Md. Imdadul Islam and M. R. Amin “Traffic Analysis of a Cognitive Radio Network Based on the Concept of Medium Access Probability”, Journal of Inf. Process Syst, Vol. 10, No. 4, pp. 602-617, December 2014
- Maninder Jeet Kaur, Moin Uddin, Harsh K Verma, “Role of Cognitive Radio on 4G communications, A Review”, Journal of Emerging Trends in Computing and Information Sciences, VOL. 3, NO. 2, pp. 272-276, February 2012
- R. Datta, N. Michailow, S. Krone, M. Lentmaier, and G. Fettweis, “Generalized Frequency Division Multiplexing in Cognitive Radio,” in 20th European Signal Processing Conference (EUSIPCO),Bucharest, Romania, 2012, pp. 2679–2683.
- L.S. Cardoso, M. Kobayashi, Oyvind Ryan, and M. Debbah, “Vander-monde Frequency Division Multiplexing for Cognitive Radio,” in 9th IEEE Workshop on Signal Processing Advances in Wireless Communi-cations (SPAWC), Recife, Brazil, July 2008, pp. 421–425.
- Danneberg, M., R. Datta, A. Festag, and G. Fettweis, “Experimental Testbed for 5G Cognitive Radio Access in 4G LTE Cellular Systems”, Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM'14), A Coruna, Spain, 06/2014.
Index Terms
Keywords