Efficient DFT of Zadoff-Chu Sequences using lmFH Pattern
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908473435881472 |
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| author | Du, Fanping |
| author_facet | Du, Fanping |
| contents | Having established that Zadoff-Chu (ZC) sequences are inherently linear micro-frequency hopping (lmFH) symbols, this paper first presents an intuitive and visual exposition of the computation of the DFT and IDFT of ZC sequences using the lmFH pattern. This yields interesting results. Subsequently, an alternative form for computing the cumulative sum of ZC sequences using the Generalized Quadratic Gauss Sum is introduced. Furthermore, building on the micro-frequency hopping (mFH) concept, this paper shows that the DFT of ZC sequences can be transformed into an lmFH symbol with frequency shift and phase offset. Therefore, the DFT of ZC sequences can be computed via cumulative frequency points, similar to the computation of normal mFH symbols. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_23200 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Efficient DFT of Zadoff-Chu Sequences using lmFH Pattern Du, Fanping Information Theory Signal Processing Having established that Zadoff-Chu (ZC) sequences are inherently linear micro-frequency hopping (lmFH) symbols, this paper first presents an intuitive and visual exposition of the computation of the DFT and IDFT of ZC sequences using the lmFH pattern. This yields interesting results. Subsequently, an alternative form for computing the cumulative sum of ZC sequences using the Generalized Quadratic Gauss Sum is introduced. Furthermore, building on the micro-frequency hopping (mFH) concept, this paper shows that the DFT of ZC sequences can be transformed into an lmFH symbol with frequency shift and phase offset. Therefore, the DFT of ZC sequences can be computed via cumulative frequency points, similar to the computation of normal mFH symbols. |
| title | Efficient DFT of Zadoff-Chu Sequences using lmFH Pattern |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2507.23200 |