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In this paper, we examine the channel estimation problem for one-way relay network(OWRN) under time-selective fading channel scenario. Our aim is to estimate the individual channels of each relay hop at the destination with unknown data from source. We utilize the relay's aided estimation function through superimposing pilots at relay, adopt the autoregressive (AR) model to characterize the time-varying...
In this paper, we examine the Bayesian Cramér-Rao lower bounds (BCRBs) for channel estimation in an amplify-and-forward (AF) one-way relay network (OWRN) under time selective flat fading scenario, where the superimposed training is adopted at relay node in order to achieve individual channel estimation. We formulate the nonlinear dynamic state space for individual channels and derive online/offline...
In this paper, the Bayesian Cramér-Rao lower bounds (BCRBs) on dynamic individual channel estimation is examined in an amplify-and-forward (AF) one-way relay network (OWRN) under time selective flat fading channel scenario, where the superimposed training framework is adopted. The target of our work is to formulate the nonlinear dynamic state-space equation for individual channels and derive the online/offline...
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