Blind Sequential Monte Carlo Joint Tracking of Channel State and Frequency Offset in OFDM Systems

Authors:
Alex P. Palamides;Andreas M. Maras
Affiliations:
Department of Electronic Computer Systems Engineering, Technological Educational Institute of Piraeus, Aigaleo, Athens, Greece 12244;Department of Telecommunications Science and Technology, University of Peloponnese, Tripolis, Greece 22100
Venue:
Wireless Personal Communications: An International Journal
Year:
2010

Citing 6
Cited 1

New blind frequency offset estimator for OFDM systems over frequency selective fading channels

Signal Processing
Fast communication: State-space approach to spatially correlated MIMO OFDM channel estimation

Signal Processing
A novel simplified channel tracking method for MIMO-OFDM systems with null sub-carriers

Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking

IEEE Transactions on Signal Processing
Joint estimation of channel response, frequency offset, and phase noise in OFDM

IEEE Transactions on Signal Processing
Joint Frequency Offset and Channel Estimation for OFDM Systems Using Pilot Symbols and Virtual Carriers

IEEE Transactions on Wireless Communications

Full length article: Blind tracking of channel state and multiple frequency offsets in MIMO-OFDM systems

Physical Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

Orthogonal frequency division multiplexing (OFDM) is a multi-carrier modulation scheme, which has been adopted for several wireless standards. In order to fully exploit the benefits of an OFDM system, estimation of the channel state information must be performed. Moreover a well-known problem of OFDM is its sensitivity to frequency offset between the transmitted and received carrier frequencies. This frequency offset introduces inter-carrier interference in the OFDM signal. In this paper we address the problem of jointly tracking the channel and frequency offset based on a Sequential Monte Carlo filtering approach. The proposed algorithm works in a decision-directed way, thus does not require the use of pilot symbols, providing a worth-mentioned increase in the useful data rate. Through simulations we demonstrate the efficiency of this approach against a similar approach where the Extended Kalman Filter is used. Moreover our method is compared with two recently proposed pilot-based methods.