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In orthogonal frequency-division multiplexing systems, the temporal channel gains to estimate are much more than the observable data over highly mobile channels. The basis expansion model (BEM) has been employed to reduce the number of these channel parameters. In the absence of channel statistics, generalized complex-exponential BEM (GCE-BEM) is popular for its fast algebra operation and easy generation...
Channel estimation plays a vital role in coherent detection and demodulation in orthogonal frequency division multiplexing (OFDM) systems. However, the channel timevariation leads to tremendous unknown parameters to estimate and detrimental inter-carrier interference (ICI) for pilot-aided channel estimation, degrading the system performance significantly. This paper proposes a joint estimation of...
Time-varying channel gains are approximated by basis expansion model (BEM) to make the tremendous unknowns estimation feasible in orthogonal frequency division multiplexing (OFDM) systems. However, sparse dispersive channel requires overloaded subcarriers for pilot-aided estimation in the framework of BEM. This paper proposes a channel estimation scheme over time-varying and sparse dispersive channel...
In this paper, we propose a solution to the carrier frequency offset (CFO) estimation based on data dependent superimposed training scheme for Orthogonal Frequency Division Multiplexing (OFDM) systems. The proposed CFO estimation can improve the bandwidth efficiency compared with traditional pilot assistant scheme because it consumes no extra bandwidth for the training sequence is superimposed to...
This paper proposes a novel recursive approach for orthogonal frequency division multiplexing (OFDM) channel estimation over highly mobile channels without any priori channel statistics. The key idea is to decompose each objective channel into the known component and the rest for estimation. The known component is the output of the prior iteration except that the first one is attained in linear time-varying...
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