Journal on Communications ›› 2015, Vol. 36 ›› Issue (1): 68-74.doi: 10.11959/j.issn.1000-436x.2015008

• Academic paper • Previous Articles     Next Articles

Energy-efficient optimal algorithm based on uplink multi-user very large MIMO system

UYing H1,2,IBao-feng J3,UANGYong-ming H1,UFei Y1,ANGLV-xi Y1   

  1. 1 School of Information Science and Engineering,Southeast University,Nanjing 210096,China
    2 Institute of Electronics and Information,Jiangsu University of Science and Technology,Zhenjiang 212003,China
    3 College of Information Engineering,Henan University of Science and Technology,Luoyang 471023,China
  • Online:2015-01-25 Published:2017-06-21
  • Supported by:
    The National Science and Terchnology Major Project of China;The National Science and Terchnology Major Project of China;The National Science and Terchnology Major Project of China;The National Science and Terchnology Major Project of China;The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Natural Science Foundation of China;Research Project of Jiangsu Province;Research Project of Jiangsu Province;PhD Programs Foundation of Ministry of Education of China

Abstract:

Using the energy efficiency lower bound as the optimization criterion,a resource allocation algorithm was investigated under uplink multi-user very large MIMO systems.Specifically,both the number of antenna arrays at the BS and the transmit data rate at the user are adjusted to maximize the energy efficiency,in which the power consumption accounts for both transmit power and circuit power,meanwhile the BS uses a zero forcing(ZF) receiver.The existence of a unique globally optimal resource allocation solution was demonstrated by exploiting the properties of objective function.Furthermore,by transforming the originally fractional optimization problem into an equivalent subtractive form using the properties of fractional programming,an iterative resource allocation algorithm was developed to achieve the optimum was developed.Simulation results show that the algorithm converge to a near optimal solution only with a small number of iterations.

Key words: wireless communication, MIMO, resource allocation, uplink system, energy-efficient

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