메뉴 건너뛰기




Volumn 55, Issue 2, 2007, Pages 437-450

Batch and Sequential Bayesian Estimators of the Number of Active Terminals in an IEEE 802.11 Network

Author keywords

Gibbs sampler; hidden Markov model (HMM); IEEE 802.11 wireless networks; sequential Monte Carlo; unknown transition matrix

Indexed keywords


EID: 85008537091     PISSN: 1053587X     EISSN: 19410476     Source Type: Journal    
DOI: 10.1109/TSP.2006.885723     Document Type: Article
Times cited : (48)

References (34)
  • 1
    • 0031237594 scopus 로고    scopus 로고
    • IEEE 802.11 wireless local area networks
    • Sep.
    • B. P. Crow, I. Widjaja, J. G. Kim, and P. T. Sakai, “IEEE 802.11 wireless local area networks,” IEEE Commun. Mag., vol. 35, no. 9, pp. 116–126, Sep. 1998.
    • (1998) IEEE Commun. Mag. , vol.35 , Issue.9 , pp. 116-126
    • Crow, B.P.1    Widjaja, I.2    Kim, J.G.3    Sakai, P.T.4
  • 2
    • 0033749075 scopus 로고    scopus 로고
    • Performance analysis of the IEEE 802.11 distributed coordination function
    • Mar.
    • G. Bianchi, “Performance analysis of the IEEE 802.11 distributed coordination function,” IEEE J. Sel. Areas Commun., vol. 18, pp. 535–547, Mar. 2000.
    • (2000) IEEE J. Sel. Areas Commun. , vol.18 , pp. 535-547
    • Bianchi, G.1
  • 3
    • 0041438376 scopus 로고    scopus 로고
    • Kalman fitler estimation of the number of competing termnals in an IEEE 802.11 network
    • San Francisco, CA, Mar.
    • G. Bianchi and I. Tinnirello, “Kalman fitler estimation of the number of competing termnals in an IEEE 802.11 network,” in Proc. Infocom 2003, San Francisco, CA, Mar. 2003, vol. 2, pp. 844–852.
    • (2003) Proc. Infocom , vol.2 , pp. 844-852
    • Bianchi, G.1    Tinnirello, I.2
  • 4
    • 0003860037 scopus 로고    scopus 로고
    • Markov Chain Monte Carlo in Practice
    • London, U.K.: Chapman and Hall
    • W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, Markov Chain Monte Carlo in Practice. London, U.K.: Chapman and Hall, 1996.
    • (1996)
    • Gilks, W.R.1    Richardson, S.2    Spiegelhalter, D.J.3
  • 5
    • 0003665481 scopus 로고    scopus 로고
    • Sequential Monte Carlo Methods in Practice
    • New York: Springer-Verlag
    • A. Doucet, N. de Freitas, and N. Gordon, Eds., Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag, 2001.
    • (2001)
    • Doucet, A.1    de Freitas, N.2    Gordon, N.3
  • 6
    • 0032359151 scopus 로고    scopus 로고
    • Sequential Monte Carlo methods for dynamic systems
    • J. S. Liu and R. Chen, “Sequential Monte Carlo methods for dynamic systems,” J. Amer. Statist. Assoc., vol. 93, no. 443, pp. 1032–1044, 1998.
    • (1998) J. Amer. Statist. Assoc. , vol.93 , Issue.443 , pp. 1032-1044
    • Liu, J.S.1    Chen, R.2
  • 7
    • 0036125627 scopus 로고    scopus 로고
    • Monte Carlo signal processing for wireless communications
    • Jan./Mar.
    • X. Wang, R. Chen, and J. S. Liu, “Monte Carlo signal processing for wireless communications,” J. VLSI Signal Process., vol. 30, no. 1–3, pp. 89–105, Jan./Mar. 2002.
    • (2002) J. VLSI Signal Process. , vol.30 , pp. 1-3
    • Wang, X.1    Chen, R.2    Liu, J.S.3
  • 8
    • 0036475891 scopus 로고    scopus 로고
    • Particle filters for state-space models with the presence of unknown static parameters
    • Feb.
    • G. Storvik, “Particle filters for state-space models with the presence of unknown static parameters,” IEEE Trans. Signal Process., vol. 50, pp. 281–289, Feb. 2002.
    • (2002) IEEE Trans. Signal Process. , vol.50 , pp. 281-289
    • Storvik, G.1
  • 9
    • 11844249571 scopus 로고    scopus 로고
    • Sequential Monte Carlo methods for digital communications
    • Ph. D, Univ. Cambridge, Cambridge, U.K.
    • E. Punskaya, “Sequential Monte Carlo methods for digital communications,” Ph.D, Univ. Cambridge, Cambridge, U.K., 2003.
    • (2003)
    • Punskaya, E.1
  • 10
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected application in speech recognition
    • Feb.
    • L. R. Rabiner, “A tutorial on hidden Markov models and selected application in speech recognition,” Proc. IEEE, vol. 77, pp. 257–285, Feb. 1989.
    • (1989) Proc. IEEE , vol.77 , pp. 257-285
    • Rabiner, L.R.1
  • 11
    • 0036489069 scopus 로고    scopus 로고
    • Bayesian methods for hidden Markov models: Recursive computing in the 21st century
    • S. L. Scott, “Bayesian methods for hidden Markov models: Recursive computing in the 21st century,” J. Amer. Statist. Assoc., vol. 97, no. 457, pp. 337–351, 2002.
    • (2002) J. Amer. Statist. Assoc. , vol.97 , Issue.457 , pp. 337-351
    • Scott, S.L.1
  • 12
    • 0027797470 scopus 로고
    • Online estimation of hidden Markov model parameters based on the Kullback-Leibler information measure
    • Aug.
    • V. Krishnamurthy and J. B. Moore, “Online estimation of hidden Markov model parameters based on the Kullback-Leibler information measure,” IEEE Trans. Signal Process., vol. 41, pp. 2557–2573, Aug. 1993.
    • (1993) IEEE Trans. Signal Process. , vol.41 , pp. 2557-2573
    • Krishnamurthy, V.1    Moore, J.B.2
  • 13
    • 0036477062 scopus 로고    scopus 로고
    • Recursive algorithms for estimation of hidden Markov models and autoregressive models with Markov regime
    • Feb.
    • V. Krishnamurthy and G. G. Yin, “Recursive algorithms for estimation of hidden Markov models and autoregressive models with Markov regime,” IEEE Trans. Inf. Theory, vol. 48, pp. 458–476, Feb. 2002.
    • (2002) IEEE Trans. Inf. Theory , vol.48 , pp. 458-476
    • Krishnamurthy, V.1    Yin, G.G.2
  • 14
    • 0032075655 scopus 로고    scopus 로고
    • Adaptive estimation of HMM transition probabilities
    • May
    • J. J. Ford and J. B. Moore, “Adaptive estimation of HMM transition probabilities,” IEEE Trans. Signal Process., vol. 46, pp. 1374–1385, May 1998.
    • (1998) IEEE Trans. Signal Process. , vol.46 , pp. 1374-1385
    • Ford, J.J.1    Moore, J.B.2
  • 15
    • 0031341716 scopus 로고    scopus 로고
    • Recursive estimation in hidden Markov models
    • F. LeGland and L. Mevel, “Recursive estimation in hidden Markov models,” in Proc. Conf. Decision Contr., 1997, vol. 4.
    • (1997) Proc. Conf. Decision Contr. , vol.4
    • LeGland, F.1    Mevel, L.2
  • 16
    • 0031065861 scopus 로고    scopus 로고
    • On recursive estimation for hidden Markov models
    • T. Ryden, “On recursive estimation for hidden Markov models,” Stoch. Proc. Applicat., vol. 66, pp. 79–96, 1997.
    • (1997) Stoch. Proc. Applicat. , vol.66 , pp. 79-96
    • Ryden, T.1
  • 17
    • 0021518209 scopus 로고
    • Stochastic relaxation, Gibbs distribution and the Beyesian restoration of images
    • Nov.
    • S. Geman and D. Geman, “Stochastic relaxation, Gibbs distribution and the Beyesian restoration of images,” IEEE Trans. Pattern Anal. Mach. lntell, vol. 6, pp. 721–741, Nov. 1984.
    • (1984) IEEE Trans. Pattern Anal. Mach. lntell , vol.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 18
    • 21144460710 scopus 로고
    • Asymptotic behavior of the Gibbs sampler
    • K. S. Chan, “Asymptotic behavior of the Gibbs sampler,” J. Amer. Statist. Assoc., vol. 88, pp. 320–326, 1993.
    • (1993) J. Amer. Statist. Assoc. , vol.88 , pp. 320-326
    • Chan, K.S.1
  • 19
    • 0000854270 scopus 로고
    • Covariance structure and convergence rate of the Gibbs sampler with various scan
    • J. S. Liu, W. H. Wong, and A. Hong, “Covariance structure and convergence rate of the Gibbs sampler with various scan,” J. R. Statist. Soc. (B), vol. 57, pp. 157–169, 1995.
    • (1995) J. R. Statist. Soc. (B) , vol.57 , pp. 157-169
    • Liu, J.S.1    Wong, W.H.2    Hong, A.3
  • 20
    • 0003919677 scopus 로고    scopus 로고
    • Monte Carlo Statistical Methods
    • New York: Springer-Verlag
    • C. P. Robert and G. Casella, Monte Carlo Statistical Methods. New York: Springer-Verlag, 1999.
    • (1999)
    • Robert, C.P.1    Casella, G.2
  • 21
    • 84981748011 scopus 로고
    • Bayesian Theory
    • New York: Wiley
    • J. M. Bernardo and A. F. M. Smith, Bayesian Theory. New York: Wiley, 1994.
    • (1994)
    • Bernardo, J.M.1    Smith, A.F.M.2
  • 22
    • 0003924729 scopus 로고    scopus 로고
    • Convergenge of sequential Monte Carlo methods
    • Tech. Rep. 381
    • D. Crisan and A. Doucet, “Convergenge of sequential Monte Carlo methods,” CUED-F-INFENG, 2000, Tech. Rep. 381.
    • (2000) CUED-F-INFENG
    • Crisan, D.1    Doucet, A.2
  • 23
    • 0036475447 scopus 로고    scopus 로고
    • A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking
    • Feb.
    • S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process., vol. 50, pp. 174–188, Feb. 2002.
    • (2002) IEEE Trans. Signal Process. , vol.50 , pp. 174-188
    • Arulampalam, S.1    Maskell, S.2    Gordon, N.3    Clapp, T.4
  • 24
    • 0141854970 scopus 로고    scopus 로고
    • Online expectation-maximization type algorithms for parameter estimation in general state space models
    • Apr.
    • C. Andrieu and A. Doucet, “Online expectation-maximization type algorithms for parameter estimation in general state space models,” in Proc. Acoust., Speech, Signal Process., ICASSP'03, vol. 6, pp. 69–72, Apr. 2003.
    • (2003) Proc. Acoust., Speech, Signal Process., ICASSP'03 , vol.6 , pp. 69-72
    • Andrieu, C.1    Doucet, A.2
  • 25
    • 0001225908 scopus 로고    scopus 로고
    • Combined parameter and state estimation in simulation-based filtering
    • Doucet, N. de Freitas, and N. Gordon, Eds. New York: Springer-Verlag
    • J. Liu and M. West, “Combined parameter and state estimation in simulation-based filtering,” in Sequential Monte Carlo Methods in Practice, A. Doucet, N. de Freitas, and N. Gordon, Eds. New York: Springer-Verlag, 2001.
    • (2001) Sequential Monte Carlo Methods in Practice, A.
    • Liu, J.1    West, M.2
  • 26
    • 0035648076 scopus 로고    scopus 로고
    • Following a moving target - Monte Carlo inference for dynamic Bayesian models
    • W. R. Gilks and C. Berzuini, “Following a moving target - Monte Carlo inference for dynamic Bayesian models,” J. R. Statist. Soc. (B), vol. 63, no. 1, pp. 127–146, 2001.
    • (2001) J. R. Statist. Soc. (B) , vol.63 , Issue.1 , pp. 127-146
    • Gilks, W.R.1    Berzuini, C.2
  • 27
    • 0036929961 scopus 로고    scopus 로고
    • MCMC, sufficient statistics and particle filters
    • P. Fearnhead, “MCMC, sufficient statistics and particle filters,” J. Computat. Graph. Statist., vol. 11, pp. 848–862, 2002.
    • (2002) J. Computat. Graph. Statist. , vol.11 , pp. 848-862
    • Fearnhead, P.1
  • 28
    • 0001460136 scopus 로고    scopus 로고
    • On sequential Monte Carlo sampling methods for Bayesian filtering
    • A. Doucet, S. J. Godsill, and C. Andrieu, “On sequential Monte Carlo sampling methods for Bayesian filtering,” Statist. Comput., vol. 10, no. 3, pp. 197–208, 2000.
    • (2000) Statist. Comput. , vol.10 , Issue.3 , pp. 197-208
    • Doucet, A.1    Godsill, S.J.2    Andrieu, C.3
  • 29
    • 1542427941 scopus 로고    scopus 로고
    • Filtering via simulation: Auxiliary particle filters
    • M. K. Pitt and N. Shephard, “Filtering via simulation: Auxiliary particle filters,” J. Amer. Statist. Assoc., vol. 94, no. 446, pp. 590–599, 1999.
    • (1999) J. Amer. Statist. Assoc. , vol.94 , Issue.446 , pp. 590-599
    • Pitt, M.K.1    Shephard, N.2
  • 30
    • 0018494990 scopus 로고
    • A detection-estimation scheme for state estimation in switching environment
    • J. Tugnait and A. Haddad, “A detection-estimation scheme for state estimation in switching environment,” Automatica, vol. 15, pp. 477–481, 1979.
    • (1979) Automatica , vol.15 , pp. 477-481
    • Tugnait, J.1    Haddad, A.2
  • 32
    • 0242550819 scopus 로고    scopus 로고
    • On-line inference for hidden Markov models via particle filters
    • P. Fearnhead and P. Clifford, “On-line inference for hidden Markov models via particle filters,” J. R. Statist. Soc. (B), vol. 65, no. 4, pp. 887–899, 2003.
    • (2003) J. R. Statist. Soc. (B) , vol.65 , Issue.4 , pp. 887-899
    • Fearnhead, P.1    Clifford, P.2
  • 34
    • 85008570250 scopus 로고    scopus 로고
    • [Online]
    • N. Simulator 2, [Online]
    • N. Simulator , vol.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.