Unimodular Sequence Design Based on Alternating Direction Method of Multipliers

被引:133
|
作者
Liang, Junli [1 ]
So, Hing Cheung [2 ]
Li, Jian [3 ]
Farina, Alfonso [4 ]
机构
[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China
[2] City Univ Hong Kong, Dept Elect Engn, Kowloon Tong, Hong Kong, Peoples R China
[3] Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA
[4] IEEE AESS, I-00144 Rome, Italy
基金
中国国家自然科学基金;
关键词
Waveform design; unimodular waveform; low autocorrelation sidelobe; spectrally constrained waveform; alternating direction method of multipliers (ADMM); nonconvex optimization; active sensing; WAVE-FORM DESIGN; LOW AUTOCORRELATION; MATRIX CALCULATION; ALGORITHM; OPTIMIZATION; CONSTRAINTS; MODULUS; NETWORK;
D O I
10.1109/TSP.2016.2597123
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The topic of probing waveform design has received considerable attention due to its numerous applications in active sensing. Apart from having the desirable property of constant magnitude, it is also anticipated that the designed sequence possesses low sidelobe autocorrelation and/or specified spectral shape. In this paper, the alternating direction method of multipliers (ADMM), which is a powerful variant of the augmented Lagrangian scheme for dealing with separable objective functions, is applied for synthesizing the probing sequences. To achieve impulse-like autocorrelation, we formulate the design problem as minimizing a nonlinear least-squares cost function in the frequency domain subject to the constraint that all sequence elements are of unit modulus. Via introducing auxiliary variables, we are able to separate the objective into linear and quadratic functions where the unimodular constraint is only imposed on the former, which results in an ADMM-style iterative procedure. In particular, fast implementation for the most computationally demanding step is investigated and local convergence of the ADMM method is proved. To deal with the spectral shape requirement, we borrow the concept in frequency-selective filter design where passband and stopband magnitudes are bounded to formulate the corresponding optimization problem. In this ADMM algorithm development, unit-step functions are utilized to transform the multivariable optimization into a quadratic polynomial problem with a single variable. The effectiveness of the proposed approach is demonstrated via computer simulations.
引用
收藏
页码:5367 / 5381
页数:15
相关论文
共 50 条
  • [1] Alternating Direction Method of Multipliers for MIMO Radar Waveform Design
    Cheng, Ziyang
    He, Zishu
    Fang, Min
    Wang, Zhilei
    Zhang, Jichuan
    [J]. 2017 IEEE RADAR CONFERENCE (RADARCONF), 2017, : 367 - 371
  • [2] Discrete Phase Coded Sequence Set Design for Waveform-Agile Radar Based on Alternating Direction Method of Multipliers
    Zhang, Jindong
    Xu, Naiqing
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2020, 56 (06) : 4238 - 4252
  • [3] An Inertial Alternating Direction Method of Multipliers
    Bot, Radu Ioan
    Csetnek, Ernoe Robert
    [J]. MINIMAX THEORY AND ITS APPLICATIONS, 2016, 1 (01): : 29 - 49
  • [4] Parallel alternating direction method of multipliers
    Yan, Jiaqi
    Guo, Fanghong
    Wen, Changyun
    Li, Guoqi
    [J]. INFORMATION SCIENCES, 2020, 507 : 185 - 196
  • [5] Distributed Alternating Direction Method of Multipliers
    Wei, Ermin
    Ozdaglar, Asuman
    [J]. 2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2012, : 5445 - 5450
  • [6] Emulation Alternating Direction Method of Multipliers
    Routray, Chinmay
    Sahoo, Soumya Ranjan
    [J]. 2022 EIGHTH INDIAN CONTROL CONFERENCE, ICC, 2022, : 403 - 408
  • [7] Alternating Direction Method of Multipliers for Quantization
    Huang, Tianjian
    Singhania, Prajwal
    Sanjabi, Maziar
    Mitra, Pabitra
    Razaviyayn, Meisam
    [J]. 24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS), 2021, 130 : 208 - +
  • [8] An Adaptive Alternating Direction Method of Multipliers
    Bartz, Sedi
    Campoy, Ruben
    Phan, Hung M.
    [J]. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 2022, 195 (03) : 1019 - 1055
  • [9] Accelerated Alternating Direction Method of Multipliers
    Kadkhodaie, Mojtaba
    Christakopoulou, Konstantina
    Sanjabi, Maziar
    Banerjee, Arindam
    [J]. KDD'15: PROCEEDINGS OF THE 21ST ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2015, : 497 - 506
  • [10] Bregman Alternating Direction Method of Multipliers
    Wang, Huahua
    Banerjee, Arindam
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 27 (NIPS 2014), 2014, 27