A First-Order Primal-Dual Method for Saddle Point Optimization of PAPR Problem in MU-MIMO-OFDM Systems

被引:1
|
作者
Singh, Davinder [1 ]
Sarin, R. K. [1 ]
机构
[1] Dr BR Ambedkar Natl Inst Technol, Dept Elect & Commun Engn, Jalandhar 144011, Punjab, India
关键词
MIMO-OFDM; peak-to-average power ratio (PAPR) reduction; saddle point problem; convex optimization; proximity operator; REDUCTION; PERFORMANCE; SIGNALS;
D O I
10.13164/re.2018.0549
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
This paper investigates the use of a particular splitting-based optimization technique for constrained l(infinity)-norm based peak-to-average power ratio (PAPR) reduction problem in multiuser orthogonal frequency-division multiplexing (OFDM) based multiple-input multi-output (MIMO) systems. PAPR reduction and multi-user interference (MUI) cancelation are considered in a saddle-point formulation on the downlink of a multi-user MIMO-OFDM system and an efficient primal-dual hybrid gradient (PDHG) inspired algorithm with easy-to-evaluate proximal operators is developed. The proposed algorithm converges significantly faster to satisfactory solutions with much improved asymptotical convergence rate than existing methods. Numerical results illustrate the superior performance of the proposed algorithm over existing methods in terms of PAPR reduction for different MIMO configurations.
引用
收藏
页码:549 / 556
页数:8
相关论文
共 50 条
  • [21] A primal-dual algorithm framework for convex saddle-point optimization
    Zhang, Benxin
    Zhu, Zhibin
    JOURNAL OF INEQUALITIES AND APPLICATIONS, 2017,
  • [22] A primal-dual prediction-correction algorithm for saddle point optimization
    He, Hongjin
    Desai, Jitamitra
    Wang, Kai
    JOURNAL OF GLOBAL OPTIMIZATION, 2016, 66 (03) : 573 - 583
  • [23] A primal-dual algorithm framework for convex saddle-point optimization
    Benxin Zhang
    Zhibin Zhu
    Journal of Inequalities and Applications, 2017
  • [24] Bregman primal-dual first-order method and application to sparse semidefinite programming
    Jiang, Xin
    Vandenberghe, Lieven
    COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2022, 81 (01) : 127 - 159
  • [25] ACCELERATION AND GLOBAL CONVERGENCE OF A FIRST-ORDER PRIMAL-DUAL METHOD FOR NONCONVEX PROBLEMS
    Clason, Christian
    Mazurenko, Stanislav
    Valkonen, Tuomo
    SIAM JOURNAL ON OPTIMIZATION, 2019, 29 (01) : 933 - 963
  • [26] A RELAXED PARAMETER CONDITION FOR THE PRIMAL-DUAL HYBRID GRADIENT METHOD FOR SADDLE-POINT PROBLEM
    Zhang, Xiayang
    Kong, Yuqian
    Liu, Shanshan
    Shen, Yuan
    JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION, 2023, 19 (03) : 1595 - 1610
  • [27] Primal-dual first-order methods for a class of cone programming
    Lu, Zhaosong
    OPTIMIZATION METHODS & SOFTWARE, 2013, 28 (06): : 1262 - 1281
  • [28] A First-Order Stochastic Primal-Dual Algorithm with Correction Step
    Rosasco, Lorenzo
    Villa, Silvia
    Bang Cong Vu
    NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION, 2017, 38 (05) : 602 - 626
  • [29] Positive-contrast susceptibility imaging based on first-order primal-dual optimization
    Shi, Caiyun
    Cheng, Jing
    Xie, Guoxi
    Su, Shi
    Chang, Yuchou
    Chen, Hanwei
    Liu, Xin
    Wang, Haifeng
    Liang, Dong
    MAGNETIC RESONANCE IN MEDICINE, 2019, 82 (03) : 1120 - 1128
  • [30] On the ergodic convergence rates of a first-order primal-dual algorithm
    Chambolle, Antonin
    Pock, Thomas
    MATHEMATICAL PROGRAMMING, 2016, 159 (1-2) : 253 - 287