PROJECT TITLE :

Constructing Binary Sequences With Good Correlation Properties: An Efficient Analytical-Computational Interplay - 2018

ABSTRACT:

Binary sequence sets with asymptotically optimal auto/cross correlation peak sidelobe level (PSL) growth are known within the literature for a while, and their construction has been studied each analytically and numerically. In contrast, it has been an extended-standing downside whether we have a tendency to will construct a family of binary sequences whose auto-correlation PSL grows in an optimal manner. During this Project, we tend to devise a construction methodology of binary sequences with asymptotically optimal PSL growth from the sequence sets with sensible correlation properties. A key component of the look follows from the observation that if the PSL of the sequence set grows optimally or nearly optimally, then the PSL of the made binary sequence can expertise the same growth as a consequence. The proposed construction is straightforward-to-implement, and is shown to be accomplished in polynomial time. With such a construction, we tend to not solely bridge the gap between analytical construction and computational search, but conjointly pave the way to settle the long-standing design downside of binary sequences with an optimal growth of the auto-correlation PSL.