Transmission Power and Antenna Allocation for Energy-Efficient RF Energy Harvesting Networks with Massive MIMO

Abstract

The optimum transmission strategy for maximizing energy efficiency (EE) of a multi-user massive multiple-input multiple-output (MIMO) system in radio frequency energy harvesting networks is investigated. We focus on dynamic time-switching (TS) antennas, to avoid the practical problems of power-splitting antennas, such as complex architectures, power loss and signal distortion when splitting the power of the received signal into power for information decoding (ID) and energy harvesting (EH). However, since a single TS antenna cannot serve ID and EH simultaneously, the MIMO system is considered in this paper. We thus formulate an EE optimization problem and propose an iterative algorithm as a tractable solution, including an antenna selection strategy to optimally switch each TS antenna between ID mode and EH mode using nonlinear fractional programming and the Lagrange dual method. Further, the problem is solved under practical constraints of maximum transmission power and outage probabilities for a minimum amount of harvested power and rate capacity for each user. Simulation results show that the proposed algorithm is more energy-efficient than that of baseline schemes, and demonstrates the trade-off between the required amount of harvested power and energy efficiency.

Keywords

• radio frequency-energy harvesting
• massive MIMO
• energy efficiency (EE)
• resource allocation
• time-switching (TS) antenna
• Lagrange dual method