Sequence Design for Spectral Shaping via Minimization of Regularized Spectral Level Ratio

The topic of sequence design has received considerable attention due to its wide applications in active sensing. One important desired property for the design sequence is the spectral shape. In this paper, the sequence design problem is formulated by minimizing the regularized spectral level ratio s...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE transactions on signal processing Ročník 67; číslo 18; s. 4683 - 4695
Hlavní autoři: Wu, Linlong, Palomar, Daniel P.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 15.09.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Dinkelbach's algorithm
Interference
Linear programming
majorization-minimization
Mathematical programming
Measurement
Optimization
PAR constraint
Peak to average power ratio
Radar
sequence design
Signal processing algorithms
Spectra
spectral level ratio
Spectral shaping
ISSN:1053-587X, 1941-0476
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The topic of sequence design has received considerable attention due to its wide applications in active sensing. One important desired property for the design sequence is the spectral shape. In this paper, the sequence design problem is formulated by minimizing the regularized spectral level ratio subject to a peak-to-average power ratio constraint. Then, two algorithms are proposed by combining both the Dinkelbach's algorithm and the majorization-minimzation (MM) method organically. Specifically, by using the Dinkelbach's algorithm, the challenging fractional programming problem can be handled by solving a series of subproblems, which are further solved via the MM method. The numerical experiments verify the effectiveness of the optimization metric and demonstrate the performance of the proposed algorithms compared with the benchmark.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2019.2929468