Abstract
This paper concerns channel tracking in a multiantenna context for correlated flat-fading channels obeying a Gauss-Markov model. It is known that data-aided tracking of fast-fading channels requires a lot of pilot symbols in order to achieve sufficient accuracy, and hence decreases the spectral efficiency. To overcome this problem, we design a code-aided estimation scheme which exploits information from both the pilot symbols and the unknown coded data symbols. The algorithm is derived based on a factor graph representation of the system and application of the sum-product algorithm. The sum-product algorithm reveals how soft information from the decoder should be exploited for the purpose of estimation and how the information bits can be detected. Simulation results illustrate the effectiveness of our approach.
Highlights
Communication over time-varying fading channels has been studied intensively during the last decade [1,2,3]
We present simulation results for a multiple-input multiple-output (MIMO) bit-interleaved coded modulation (BICM) scheme [24, 30] with NT = 2 transmit antennas and NR = 2 receive antennas
Frames consists of 1440 coded information bits, and a number of pilot symbols are periodically
Summary
Communication over time-varying fading channels has been studied intensively during the last decade [1,2,3]. The Kalman filter/smoother [12] is a powerful tool to obtain the minimum mean-squared error (MMSE) estimate of a parameter varying according to a discrete-time linear model. This technique is convenient for pilotassisted estimation of a time-varying channel [7,8,9]. Estimating a time-varying channel in the presence of unknown data symbols is not possible by straightforward Kalman filtering/smoothing. This is followed by a factor graph representation of the receiver and derivation of the SP algorithm on this graph.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
