Pyung-soo KIM, Jeong-hun CHOI, Eung-hyuk LEE, Doo-hee JUNG, Eung-tae KIM
System Software Solution Laboratory, Dept. of Electronics Enginee ring,Korea Polytechnic University, Shiheung 429-793, Korea
Abstract-This paper proposes new interference estimation for p ower control in broadband wireless data networks. The proposed approach gives th e filtered interference power in real-time removing undesired effects such as t he fluctuation of interference power and the measurement noise due to receiver n oise. The well-known Finite Impulse Response (FIR) structure filter is adopted for both the interference and the noise covariance estimation. The proposed mech anism provides both the filtered interference power and the filtered number of a ctive co-channel interferers, which shows good inherent properties. And the fil tered interference power is not affected by the constant number of active co-ch annel interferes. It is also shown that the filtered number of active co-channe l interference is separated from the filtered interference power. From discussio ns about the choice of design parameters such as window length and covariance ra tio, they can make the estimation performance of the proposed FIR filtering base d mechanism as good as possible. Via e xtensive computer simulations, the performance of the proposed mechanism is show n to be superior to the existing Kalman filtering based mechanism.
Key words-power control; interference estimation; FIR f iltering; Kalman filtering
Manuscript Number: 1674-8042(2010)02-0152-05
dio: 10.3969/j.issn.1674-1357.2010.02.13
References
[1]J. Zander, 1992. Performance of optimum transmitter power control in cellular radio systems. IEEE Transactions on Vehecle Technology, 41(2): 57-62.
[2]N. Bambos, S. Kandukuri, 2002. Power-controlled matiple access sche mes for next-generation wireless packet networks. IEEE Transactions o n Wireless Communications, 9(3): 58-64.
[3]M. Huang, P. Caines, R. Malhame, 2004. Uplink power adjustment in w ireless communication systems: a stochastic control analysis. IEEE Tra nsactions on Automat. Contr., 49(10): 1693-1708.
[4]A. Agrawal, J. Andrews, J. Cioffi, T. Meng, 2005. Iterative power co ntrol for imperfect successive interference cancellation. IEEE Transac tions on Wireless Communications, 4(3): 878-884.
[5]Z. Dziong, M. Jia, P. Mermelstein, 1996. Adaptive traffic admission for integrated services in CDMA wireless-access networks. IEEE Journa l on Selected Areas in Communications,14(12): 1737-1747.
[6]K. K. Leung, 1999. A Kalman-filter Method for Power Control in Broa dband Wireless Networks. Proc. INFOCOM, New York, NY, USA, p. 948-956.
[7]K. Leung, J. Winters, L. Cimini, 2001. Interference Estimation with Noisy Measurements in Broadband Wireless Packet Networks. Proc. IEEE 54th Vehicu lar Technology Conference (VTC 2001 Fall), p. 1125-1129.
[8]K. Leung, 2002. Power control by interference prediction for broadba nd wireless packet networks. IEEE Transactions on Wireless ommunicatio ns, 1(2): 256-265.
[9]R. J. Fitzgerald, 1971. Divergence of the Kalman filter. I EEE Trans. Automat. Contr., 16: 736-747.
[10]F. Schweppe, 1973. Uncertain Dynamic Systems. Englewood Cliffs. NJ: Prentice-Hall.
[11]W. H. Kwon, P. S. Kim, S. H. Han, 2002. A receding horizon unbiased FIR filter for discrete-time state space models. Automatica , 38(3): 545-551.
[12]P. S. Kim, 2002. Maximum likelihood FIR filter for state space sign al models. IEICE Trans. Commun, E85-B(12): 1604-1607.
[13]P. S. Kim, M. E. Lee, 2007. A new FIR filter for state estimation a nd its application. Journal of Computer Science and Technology, 22(5): 779-784.
[14]C. K. Ahn, P. S. Kim, 2008. Fixed-lag maximum likelihood FIR smoot her for state-space models. IEICE Electronics Express, 5(1): 11-16.
[15]H. Kim, P. S. Kim, S. Lee. A delayed estimation filter using finite observation on delay interval. IEICE Trans. Fundamentals, E9 1-A(8): 2257-2262.
[full text view]
