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Recently, a switch-based hybrid massive MIMO structure that aims to reduce the hardware complexity and power consumption has been proposed as a potential candidate for millimeter wave (mmWave) communications. In this paper, we investigate a matrix completion (MC)-based low-complexity channel estimator for such systems, which is compatible with the switch-based hybrid structure. We conduct a thorough...
This paper studies the channel estimation and equalisation of orthogonal frequency-division multiplexing (OFDM) systems over doubly selective channels. We consider practical channel estimation schemes based on basis expansion model (BEM) and clustered pilots. We investigate the influence of the parameters of the channel estimation scheme, including the dimensionality of the BEM basis and bandwidth...
This paper proposes a new approach to joint Doppler spread and channel estimation over Rayleigh fading channels through an iterative process between a Doppler spread estimator and a channel estimator. Our proposed Doppler spread estimator is based on the autocorrelation function (ACF) of the estimated channel coefficients, where we devise an ACF lag selection mechanism to maximize the performance...
Signal estimation in MIMO communications typically suffers from performance degradations due to imperfect channel state information (CSI). Traditional robustification schemes rely on assumptions about the model uncertainty and may result in conservative performance. We introduce a rank-reduction approach that enhances the performance in training-based applications. A sequence of reduced-rank channel...
This letter introduces condition number-constrained approximation to matrices used for signal estimation and detection. Under a Frobenius norm criterion, the closed-form solution to the optimal approximation is derived, which can be found efficiently for arbitrary condition number constraints. The resulting approximation techniques are applied to the imperfectly estimated covariance and channel matrices...
Linear equalization can be applied to combat intersymbol interference (ISI) and cross-antenna interference (CAI) for communication systems over multipath channels. If the channel estimation is imperfect, the receiver uses a mismatched model of the system. Regularized equalization based on Krylov subspace expansion can be applied to improve robustness and reduce complexity for large systems. In this...
This paper deals with different techniques for linear equalization of multipath channels with imperfect channel estimation (CE). We develop a unified framework based on Krylov subspace expansion, which allows us to compare the performance of the conjugate gradient (CG) method, diagonal loading (DL), and a hybrid scheme. Our analysis shows that the DL method generally outperforms its alternatives,...
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