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Register a new userOn the Cramer-Rao Lower Bound for Spatial Correlation Matrices of Doubly Selective Fading Channels for MIMO OFDM Systems
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Xiaochuan Zhao
Publication date
2008
fields
Informatics Engineering
and research's language is
English
Authors
Xiaochuan Zhao
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The analytic expression of CRLB and the maximum likelihood estimator for spatial correlation matrices in time-varying multipath fading channels for MIMO OFDM systems are reported in this paper. The analytical and numerical results reveal that the amount of samples and the order of frequency selectivity have dominant impact on the CRLB. Moreover, the number of pilot tones, SNR as well as the normalized maximum Doppler spread together influence the effective order of frequency selectivity.
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The analytic expression of CRLB and the maximum likelihood estimator for the sample frequency correlation matrices in doubly selective fading channels for OFDM systems are reported in this paper. According to the analytical and numerical results, the amount of samples affects the average mean square error dominantly while the SNR and the Doppler spread do negligibly.
This paper derives the analytic expression of the sample auto-correlation matrix from the least-squared channel estimation of doubly selective fading channels for OFDM systems. According to the expression, the sample auto-correlation matrix reveals the bias property which would cause the model mismatch and therefore deteriorate the performance of channel estimation. Numerical results demonstrate the bias property and corresponding analysis.
A novel maximum Doppler spread estimation algorithm for OFDM systems with comb-type pilot pattern is presented in this paper. By tracking the drifting delay subspace of time-varying multipath channels, a Doppler dependent parameter can be accurately measured and further expanded and transformed into a non-linear high-order polynomial equation, from which the maximum Doppler spread is readily solved by resorting to the Newtons method. Its performance is demonstrated by simulations.
This letter presents and analyzes orthogonal frequency-division multiplexing (OFDM)-based multi-carrier transmission for cell-free massive multi-input multi-output (CFmMIMO) over frequency-selective fading channels. Frequency-domain conjugate beamforming, pilot assignment, and user-specific resource allocation are proposed. CFmMIMO-OFDM is scalable to serve a massive number of users and is flexible to offer diverse data rates for heterogeneous applications.
To achieve the joint active and passive beamforming gains in the reconfigurable intelligent surface assisted millimeter wave system, the reflected cascade channel needs to be accurately estimated. Many strategies have been proposed in the literature to solve this issue. However, whether the Cramer-Rao lower bound (CRLB) of such estimation is achievable still remains uncertain. To fill this gap, we first convert the channel estimation problem into a sparse signal recovery problem by utilizing the properties of discrete Fourier transform matrix and Kronecker product. Then, a joint typicality based estimator is utilized to carry out the signal recovery task. We show that, through both mathematical proofs and numerical simulations, the solution proposed in this letter can in fact asymptotically achieve the CRLB.
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