Title :
Blind Multiple Frequency Offsets and Channel Estimation Using Particle Filter in Cooperative Transmission Wireless Networks
Author :
Li Anping ; Xia Nan
Author_Institution :
State Radio Monitoring Center, Beijing, China
Abstract :
Precise estimation of Carrier Frequency Offsets (CFO) and channel gains is significant for coherent receiver in cooperative transmission (CT) wireless networks. In this paper, we introduce an unknown parameters estimation approach using a preamble, which is based on Bayesian estimation framework and implemented via Sequential Monte Carlo Method (SMC) to estimate multiple CFOs between transmitters and receivers and the channel gains. The desired data can be subsequently detected based on the estimated parameters. We derive a particle filtering algorithm (PFA) for the parameters estimation of distributed frequency-shift keying (FSK) CT wireless networks. The computer simulations for our proposed approach indicate the particle filtering algorithm is accurate and superior for the parameters estimation compared to the existing algorithms.
Keywords :
Bayes methods; Monte Carlo methods; channel estimation; cooperative communication; frequency shift keying; particle filtering (numerical methods); Bayesian estimation framework; CFO; PFA; SMC; blind multiple frequency offset; carrier frequency offsets; channel estimation; channel gains; coherent receiver; cooperative transmission wireless networks; distributed FSK CT wireless networks; distributed frequency-shift keying CT wireless networks; particle filtering algorithm; sequential Monte Carlo method; unknown parameters estimation approach; Channel estimation; Estimation; Filtering; Frequency estimation; Frequency shift keying; Receivers; Wireless networks; Channel Estimation; Frequency Multiple Frequency Offsets; Particle Filter;
Conference_Titel :
Computer and Information Technology (CIT), 2014 IEEE International Conference on
Conference_Location :
Xi´an
DOI :
10.1109/CIT.2014.139
