A Method for Energy Efficiency Optimization of Large-Scale MIMO System Based on Energy Harvesting

Abstract

The invention claims an energy efficiency optimization method of a large-scale MIMO system based on energy collection. The method comprises the following steps: initializing a maximum number of iterations, a maximum tolerance factor, an initial energy efficiency value, an energy tower emission power value and the number of iterations; determining whether the maximum number of iterations is satisfied according to the number of iterations, and if so, figuring out a sensor energy collection time; otherwise, directly substituting the maximum number of iterations to figure out the energy efficiency; in view of the figured out sensor energy collection time, judging whether a limit of the sensor energy collection time is met, if so, figuring out the transmitting power of an energy tower; otherwise, directly substituting the sensor energy collection time to figure out the energy efficiency; in view of the figured out transmitting power of the energy tower, judging whether the limiting condition of the transmitting power of the energy tower is met, if so, substituting the transmitting power of the energy tower into a target function for solving; and finally, judging whether the target function is within the maximum tolerance range, if so, figuring out the optimal energy efficiency, and updating the number of iterations; or otherwise, figuring out the energy efficiency value. The energyefficiency optimization method has the advantages of fast searching speed, practicability and strong feasibility.

Description

technical field [0001] The invention belongs to the technical field of MIMO, in particular to a method for optimizing energy efficiency of a massive MIMO system based on energy collection. Background technique [0002] In recent years, with the rapid development of human society and serious shortage of resources, Wireless Power Transfer (WPT) has attracted great attention in the field of wireless research. Different from traditional wired energy sources, sensor nodes collect energy from electromagnetic radiation , to prolong the lifetime of energy-constrained networks or devices. WPT can be used in many extreme conditions, such as underwater, desert and body area network. In medical treatment, devices implanted in the body can collect energy from the outside world through WPT technology, which is extremely convenient. In wireless sensor nodes for intelligent transportation, aircraft, and Internet of Things applications, the use of WPT extends battery life. Recently, when ...

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Problems solved by technology

The proposed method adopts Zero Forcing (ZF) reception, and maximizes the system energy efficiency as the criterion, and optimizes the energy efficiency function by jointly adjusting the number of transmitting antennas at the base station and the user data rate, but ignores the impact of large-scale fading on system energy efficiency. influences

[0007] In "Energy and Spectral Efficiency of Very Large MultiuserMIMO Systems, apr.2013, vol.61, no.4, pp.1436-1449", Ngo H Q et al. deduced that the uplink of a large-scale MIMO multiuser system uses The maximum ratio combining, ZF and the capacity lower bound of the minimum mean square error detection, and the trade-off relationship between energy efficiency and spectral efficiency are studied, but the circuit power consumption is not considered in the power consumption of the system

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