Wireless Communications Over Rapidly Time-Varying Channels 2011
DOI: 10.1016/b978-0-12-374483-8.00006-6
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Equalization of Time-Varying Channels

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Cited by 14 publications
(7 citation statements)
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References 131 publications
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“…From this we conclude that τ (ξ + j a , x + Finally, we investigate an important assumption made in wireless communications. To facilitate the inversion of the channel matrix in (1), it is commonly assumed that the channel matrix is a diagonal matrix [8,9,27,38]. Clearly, if the Gabor system G(g, Λ) is a (Riesz) basis for L 2 (R d ), then there is a bijection between operators and channel matrices, and thus there exist diagonal channel matrices.…”
Section: Uniqueness Resultsmentioning
confidence: 99%
“…From this we conclude that τ (ξ + j a , x + Finally, we investigate an important assumption made in wireless communications. To facilitate the inversion of the channel matrix in (1), it is commonly assumed that the channel matrix is a diagonal matrix [8,9,27,38]. Clearly, if the Gabor system G(g, Λ) is a (Riesz) basis for L 2 (R d ), then there is a bijection between operators and channel matrices, and thus there exist diagonal channel matrices.…”
Section: Uniqueness Resultsmentioning
confidence: 99%
“…And the data is modulated with QPSK of unit power. The maximal normalized Doppler shifts 1 for the first and third hop are set as 0.05 while that of the second hop is set as 0.15. Two relaying paths are considered (K= 2).…”
Section: Simulation Results and Discussionmentioning
confidence: 99%
“…One way to handle it is to iterate between data detection and channel estimation, e.g., through expectation-maximization (EM) algorithm [1], assuming knowledge of channel statistics and noise variance. When the noise variance is unknown, a solution based on variational inference was proposed in [2].…”
Section: Introductionmentioning
confidence: 99%
“…Since doubly selective or time-varying multipath channels caused by the propagation channel environment of IIoT will affect the robustness of the entire communication system [20]. In addition, since the channel state is varying and the equalizer must be constantly updated to match the channel changing, it is difficult to realize estimation and equalization simultaneously [28,29]. A low-complexity channel estimation scheme based on compressed sensing in IIoT environment is proposed in [20], and the simulations results show that the proposed method can effectively improve the robustness of the system.…”
Section: The Robust Communications In Iiotmentioning
confidence: 99%