Joint parameter estimation and decoding in a distributed receiver

Summary This paper presents an algorithm for iterative joint channel parameter (carrier phase, Doppler shift, and Doppler rate) estimation and decoding of transmission over channels affected by Doppler shift and Doppler rate using a distributed receiver. This algorithm is derived by applying the sum...

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Bibliographic Details
Published in:International journal of satellite communications and networking Vol. 41; no. 1; pp. 59 - 81
Main Authors: Waqas, Ahsan, Nguyen, Khoa, Lechner, Gottfried, Chan, Terence
Format: Journal Article
Language:English
Published: Chichester Wiley Subscription Services, Inc 01.01.2023
Subjects:
Algorithms
Bit error rate
Cramer‐Rao bounds
Doppler effect
Doppler rate
Doppler shift
factor graphs (FGs)
Filtration
Graphical representations
Importance sampling
iterative detection and decoding
Iterative methods
Lower bounds
Mathematical models
Parameter estimation
particle filter
Phase shift
Polynomials
Random walk
sum‐product algorithm (SPA)
synchronization
Tracking
ISSN:1542-0973, 1542-0981
Online Access:Get full text
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Summary:Summary This paper presents an algorithm for iterative joint channel parameter (carrier phase, Doppler shift, and Doppler rate) estimation and decoding of transmission over channels affected by Doppler shift and Doppler rate using a distributed receiver. This algorithm is derived by applying the sum‐product algorithm (SPA) to a factor graph representing the joint a posteriori distribution of the information symbols and channel parameters given the channel output. In this paper, we present two methods for dealing with intractable messages of the SPA. In the first approach, we use particle filtering with sequential importance sampling for the estimation of the unknown parameters. We also propose a method for fine‐tuning of particles for improved convergence. In the second approach, we approximate our model with a random walk phase model, followed by a phase tracking algorithm and polynomial regression algorithm to estimate the unknown parameters. We derive the Weighted Bayesian Cramer‐Rao Bounds for joint carrier phase, Doppler shift, and Doppler rate estimation, which take into account the prior distribution of the estimation parameters and are accurate lower bounds for all considered signal‐to‐noise ratio values. Numerical results (of bit error rate and the mean‐square error of parameter estimation) suggest that phase tracking with the random walk model slightly outperforms particle filtering. However, particle filtering has a lower computational cost than the random walk model‐based method. This paper presents an algorithm for iterative joint channel parameter (carrier phase, Doppler shift, and Doppler rate) estimation and decoding of transmission over channels affected by Doppler shift and Doppler rate using a distributed receiver. We derive the Weighted Bayesian Cramer‐Rao Bounds for joint carrier phase, Doppler shift, and Doppler rate estimation, which take into account the prior distribution of the estimation parameters and are accurate lower bounds for all considered signal‐to‐noise ratio values.
Bibliography:Funding information
RTP scholarship by Government of Australia; SmartSat CRC
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ISSN:1542-0973
1542-0981
DOI:10.1002/sat.1460