A New Algorithm for Searching Sequences with Low PAPR via Goal Attainment Method

This paper is focused on designing phase sequences with good peak-to-average power ratio (PAPR). The PAPR optimization problem is a min-max problem, which is generally difficult to solve with optimization theory. The goal attainment method (GAM) is one of the most prominent approach to solve the min-max problem, which has been used to optimize the peak sidelobe level of the sequence. Based on GAM, this paper proposes a new algorithm for searching sequences with low PAPR. The key feature of the proposed algorithm is to convert the main problem into multiple subproblems via coordinate-descent method and combine them with a traditional method to avoid the local optimum. The numerical results show that the proposed algorithm leads to sequences with lower PAPR compared with the well-known m-sequences, Zadoff-Chu sequences, and those generated by a previously proposed algorithm.