Distributed joint optimization of beamforming and power allocation for maximizing the energy efficiency of cognitive heterogeneous networks

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Abstract

This paper investigated an energy-efficient beamforming and power allocation strategy for cognitive heterogeneous networks with multiple-input-single-output interference channels. To maxi-mize the sum energy efficiency of secondary users (SUs) while keeping the interference to primary networks under a predetermined threshold, I propose a distributed resource allocation algorithm using dual methods, in which each SU updates its beamforming vector and transmit power itera-tively without any information sharing until convergence. The simulation results verify that the performance of the proposed scheme is comparable to that of the optimal scheme but with a much shorter computation time.

Original languageEnglish
Article number3186
JournalSensors
Volume21
Issue number9
DOIs
StatePublished - 1 May 2021

Keywords

  • Cognitive heterogeneous networks
  • Distributed algorithm
  • Energy efficiency
  • Joint optimization
  • MISO interference channel

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