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A Review Study of Prime Period Perfect Gaussian Integer Sequences
Version 1
: Received: 16 January 2024 / Approved: 16 January 2024 / Online: 16 January 2024 (12:28:06 CET)
A peer-reviewed article of this Preprint also exists.
Chang, H.-H.; Guan, S.; Zeng, M.; Chen, P. A Review Study of Prime Period Perfect Gaussian Integer Sequences. Axioms 2024, 13, 159. Chang, H.-H.; Guan, S.; Zeng, M.; Chen, P. A Review Study of Prime Period Perfect Gaussian Integer Sequences. Axioms 2024, 13, 159.
Abstract
Prime period sequences can serve as the fundamental tool to construct arbitrary composite period sequences. This is a review study of prime period perfect Gaussian integer sequence (PGIS). When cyclic group {1,2,…,N−1} can be partitioned into k cosets, where N=kf+1 is an odd prime number, the construction of a degree-(k+1) PGIS can be derived from either matching the flat magnitude spectrum criterion or making the sequence with ideal periodic autocorrelation function (PACF). This is a systematic approach of prime period N=kf+1 PGIS construction, and is applied to construct PGISs with degrees 1, 2, 3 and 5. However, for degrees larger than 3, matching either the flat magnitude spectrum or achieving the ideal PACF encounters a great challenge of solving a system of nonlinear constraint equations. To deal with this problem, the correlation and convolution operations can be applied upon PGIS of lower degrees to generate new PGIS with degree-4 and other higher degrees, e.g., 6, 7, 10, 11, 12, 14, 20 and 21 in this paper. In this convolution based scheme, both degree and pattern of a PGIS vary and can be indeterminant, which is rather nonsystematic compared with the systematic approach. The combination of systematic and nonsystematic schemes contributes the great efficiency for constructing abundant PGISs with various degrees and patterns for the associated applications.
Keywords
correlation function; degree; perfect sequence; PGIS
Subject
Computer Science and Mathematics, Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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