Distributed Joint Optimization of Beamforming and Power Allocation for Maximizing the Energy Efficiency of Cognitive Heterogeneous Networks

Abstract

This paper investigated an energy-efficient beamforming and power allocation strategy for cognitive heterogeneous networks with multiple-input-single-output interference channels. To maximize 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 iteratively 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.

Distributed Transmit Power Control for Energy-Efficient Wireless-Powered Secure Communications

“…This may cause inconvenience to users as the battery may need to be recharged or replaced more often to extend the lifetime of the network. Accordingly, several methods, such as energy-efficient protocols [ 3 ], resource allocation [ 4 , 5 ], and multi-antenna techniques [ 6 , 7 ], have been proposed to improve the energy efficiencies of networks.…”

“…Unlike the aforementioned studies that focus only on energy efficiency [ 3 , 4 , 5 , 6 , 7 , 13 , 14 , 15 , 16 , 17 ] or PLS [ 18 , 19 , 20 , 21 , 22 , 23 , 24 ], secrecy energy efficiency (SEE), which is defined as the ratio of the secrecy rate to dissipated power, was suggested to achieve a balance between energy efficiency and secure communication [ 25 , 26 , 27 , 28 , 29 , 30 ]. For example, resource allocations including transmit power and beamforming vectors were optimized to maximize the SEE in CRNs [ 25 , 27 ] and multi-antenna systems [ 26 , 28 ], respectively.…”