A sequential Monte Carlo method for blind phase noise estimation and data detection
Yükleniyor...
Dosyalar
Tarih
2005
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, a computationally efficient algorithm is presented for blind phase noise estimation and data detection jointly, based on a sequential Monte Carlo method. The basic idea is to treat the transmitted symbols as " missing data" and draw samples sequentially of them based on the observed signal samples up to time t. This way, the Bayesian estimates of the phase noise and the incoming data are obtained through these samples, sequentially drawn, together with their importance weights. The proposed receiver structure is seen to be ideally suited for high-speed parallel implementation using VLSI technology.
Açıklama
Anahtar Kelimeler
High-speed parallel implementation, Bayesian estimation, Signal sample observation, Missing data, Transmitted symbols, Computationally efficient algorithm, Data detection, Blind phase noise estimation, Sequential Monte Carlo method, Sequential estimation, Object detection, Joints, Bayes methods, Bit error rate, Estimation, Phase noise, Signal processing, Monte Carlo methods, Bayesian networks, Algorithms, VLSI technology, Signal samples, Sequential Monte Carlo methods, Receiver structure, Parallel implementations, Noise estimation, Missing data, Importance weights, High-speed, Data detection, Computationally efficient, Bayesian estimate, Filter CKF, Target tracking, Kalman filters
Kaynak
13th European Signal Processing Conference, EUSIPCO 2005
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Panayırcı, E., Çırpan, H. A. & Moeneclaey, M. (2005). A sequential monte carlo method for blind phase noise estimation and data detection. Paper presented at the 13th European Signal Processing Conference, EUSIPCO 2005, 1942-1946.