Joint Power and Admission Control via Linear Programming Deflation

被引:56
|
作者
Liu, Ya-Feng [1 ]
Dai, Yu-Hong [1 ]
Luo, Zhi-Quan [2 ]
机构
[1] Chinese Acad Sci, State Key Lab Sci & Engn Comp, Inst Computat Math & Sci Engn Comp, Acad Math & Syst Sci, Beijing 100190, Peoples R China
[2] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
基金
美国国家科学基金会;
关键词
Admission control; convex approximation; link removal; power control; sparse optimization; DISTRIBUTED POWER; CONTROL ALGORITHM; NETWORKS;
D O I
10.1109/TSP.2012.2236319
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
We consider the joint power and admission control problem for a wireless network consisting of multiple interfering links. The goal is to support a maximum number of links at their specified signal to interference plus noise ratio (SINR) targets while using a minimum total transmission power. In this work, we first reformulate this NP-hard problem as a sparse sic-minimization problem and then relax it to a linear program. Furthermore, we derive two easy-to-check necessary conditions for all links in the network to be simultaneously supported at their target SINR levels, and use them to iteratively remove strong interfering links ( deflation). An upper bound on the maximum number of supported links is also given. Numerical simulations show that the proposed approach compares favorably with the existing approaches in terms of the number of supported links, the total transmission power, and the execution time.
引用
收藏
页码:1327 / 1338
页数:12
相关论文
共 50 条
  • [41] Distributed method for joint power allocation and admission control based on ADMM framework
    Lin J.-R.
    Jiang C.-X.
    Li Q.
    Shao H.-Z.
    Li Y.-B.
    1600, Univ. of Electronic Science and Technology of China (45): : 726 - 731and743
  • [42] Joint power and admission control based on hybrid users in cognitive radio network
    Allahyari, Amir
    Jamshidi, Ali
    Derakhtian, Mostafa
    SIGNAL PROCESSING, 2019, 155 : 143 - 156
  • [43] Joint Admission and Power Control for Big Data Access Management using GAT
    Yang, Mengke
    Zhai, Daosen
    Zhang, Ruonan
    Cao, Haotong
    Cai, Lin
    Yu, F. Richard
    IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 4735 - 4740
  • [44] Regularized Multiple Criteria Linear Programming via Linear Programming
    Qi, Zhiquan
    Tian, Yingjie
    Shi, Yong
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2012, 2012, 9 : 1234 - 1239
  • [45] Joint Shape Segmentation with Linear Programming
    Huang, Qixing
    Koltun, Vladlen
    Guibas, Leonidas
    ACM TRANSACTIONS ON GRAPHICS, 2011, 30 (06):
  • [46] Assistive Power Buffer Control via Adaptive Dynamic Programming
    Massenio, Paolo Roberto
    Naso, David
    Lewis, Frank L.
    Davoudi, Ali
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 2020, 35 (03) : 1534 - 1546
  • [47] Power control for wireless cellular systems via DC programming
    Phan, Khoa T.
    Vorobyov, Sergiy A.
    Telambura, Chintha
    Le-Ngoc, Tho
    2007 IEEE/SP 14TH WORKSHOP ON STATISTICAL SIGNAL PROCESSING, VOLS 1 AND 2, 2007, : 507 - +
  • [48] Approximate dynamic programming via linear programming
    de Farias, DP
    Van Roy, B
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 14, VOLS 1 AND 2, 2002, 14 : 689 - 695
  • [49] Random Linear Packet Coding: Joint Power and Rate Control
    Ahmed, Rameez
    Stojanovic, Milica
    CONFERENCE RECORD OF THE 2014 FORTY-EIGHTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2014, : 328 - 332
  • [50] Joint multicast beamforming and admission control
    Matskani, E.
    Sidiropoulos, N. D.
    Luo, Z-Q.
    Tassiulas, L.
    2007 2ND IEEE INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING, 2007, : 17 - +