Multiuser detection in the presence of strong phase noise for DVB-RCS systems.
DOI: 10.1109/WCNC.2011.5779352 Conference: 2011 IEEE Wireless Communications and Networking Conference, WCNC 2011, Proceedings, Cancun, Mexico, 28-31 March, 2011
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ABSTRACT: In satellite communications, the space segment is a large slice of the operating costs. Therefore every effort should be made to increase the spectral efficiency, thereby reducing the space segment costs. In order to optimize spectral efficiency, channel spacing (CS) should be reduced. Unfortunately, this introduces spectrally overlapping transmissions, thereby creating adjacent channel interference (ACI), which impairs the performance of satellite communication systems. To overcome this problem, intelligent interference mitigation schemes should be considered. This paper considers the problem of multi-channel synchronization of several spectrally overlapping transmissions in a satellite TDMA/frequency division multiple access burst system. The synchronization aims to estimate carrier frequency, carrier phase and symbol timing in the presence of ACI. The potential performance gain of multi-channel processing over conventional single channel processing is shown. Two types of low-complexity algorithms are proposed: ‘channelized’ expectation maximization and ‘channelized’ interference cancellation. Both of these algorithms attain this performance gain. Computer simulations show a 78% improvement in spectral efficiency for a wide range of carrier-imbalance values. This translates into a large potential saving in space segment costs compared to conventional CS. Copyright © 2006 John Wiley & Sons, Ltd.International Journal of Satellite Communications and Networking 02/2006; 24(1):1 - 22. · 0.54 Impact Factor
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ABSTRACT: Algorithms that must deal with complicated global functions of many variables often exploit the manner in which the given functions factor as a product of “local” functions, each of which depends on a subset of the variables. Such a factorization can be visualized with a bipartite graph that we call a factor graph, In this tutorial paper, we present a generic message-passing algorithm, the sum-product algorithm, that operates in a factor graph. Following a single, simple computational rule, the sum-product algorithm computes-either exactly or approximately-various marginal functions derived from the global function. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can be derived as specific instances of the sum-product algorithm, including the forward/backward algorithm, the Viterbi algorithm, the iterative “turbo” decoding algorithm, Pearl's (1988) belief propagation algorithm for Bayesian networks, the Kalman filter, and certain fast Fourier transform (FFT) algorithmsIEEE Transactions on Information Theory 03/2001; · 2.65 Impact Factor
- Vehicular Technology Conference, 2005. VTC-2005-Fall. 2005 IEEE 62nd; 10/2005
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