Title | ||
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Temporally Correlated Sparsity Based Compressed Sensing of Doubly Selective Sky Wave Channel for High-Frequency OFDM Systems |
Abstract | ||
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In order to reduce the pilots overhead and improve the estimation accuracy of doubly selective sky wave channel estimation based on compressed sensing (CS), a new compressed sensing estimation scheme is proposed by exploiting the temporally correlated sparsity of channel coefficient in this paper. Combining with the transmission model of High-frequency (HF) orthogonal frequency division multiplexing (OFDM) system and the sparsity of sky wave channel in transformed domain, the channel estimation problem is formulated under the framework of compressed sensing. On this basis, the temporal correlation of channel coefficient sparsity is theoretically verified by proving that the channel coefficients in several successive OFDM symbols share the common support set. Since the temporal correlation enhances the sparsity of channel coefficients in time dimension, then higher reconstruction accuracy of compressed sensing and the reducuction of pilot overhead can be expected. Simulation results verify the effectiveness of the proposed scheme. |
Year | DOI | Venue |
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2020 | 10.1109/ICCT50939.2020.9295820 | 2020 IEEE 20th International Conference on Communication Technology (ICCT) |
Keywords | DocType | ISSN |
high-frequency,OFDM,sky wave channel,compressed sensing,sparsity | Conference | 2576-7844 |
ISBN | Citations | PageRank |
978-1-7281-8142-4 | 0 | 0.34 |
References | Authors | |
3 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Kai Wang | 1 | 1734 | 195.03 |
Xu Shun | 2 | 0 | 0.34 |
Chen Shaorong | 3 | 0 | 0.34 |
Bo Zhang | 4 | 4 | 19.80 |