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Semi-blind Channel Estimation and Decoding for Space-Time Block coded System
The paper addresses the problem of semi-blind channel estimation and decoding for space-time coded system over time-varying fading channel. We derive a state-space model that characterizes the space-time coded system. The channel estimation are performed using a kalman filtering method which operates in two modes: training mode and blind mode. Box-constrained ML algorithm is used to perform the decoding function under the previous state-space system model. The performance of channel estimation and decoding schemes are investigated by computer simulations.
Semi-blind Channel Estimation and Decoding for Space-Time Block coded System
The paper addresses the problem of semi-blind channel estimation and decoding for space-time coded system over time-varying fading channel. We derive a state-space model that characterizes the space-time coded system. The channel estimation are performed using a kalman filtering method which operates in two modes: training mode and blind mode. Box-constrained ML algorithm is used to perform the decoding function under the previous state-space system model. The performance of channel estimation and decoding schemes are investigated by computer simulations.
Semi-blind Channel Estimation and Decoding for Space-Time Block coded System
Jing, Xiaorong (Autor:in) / Xu, Zheng (Autor:in) / Dai, Shijin (Autor:in) / Zhou, Zhengzhong (Autor:in)
01.06.2006
4703850 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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