Research On SWIPT For Multi-user Interference Channels

In energy-constrained wireless networks,especially in the context of promoting green communications,it is very important to design energy-saving systems.An effective way to reduce energy consumption and achieve green communications is to harvest energy from the environment.Environment-independent ambient radio frequency signals,which can carry both energy and information,can be a viable new source for energy harvesting.Hence,it is meaningful for prolonging the lifetime of the wireless device's built-in battery to harvest the RF energy.On the other hand,with the development of wireless communication technology,the traditional point-to-point communication system is gradually replaced by the multi-user multi-antenna system,which has a higher utilization of spectrum resources.Therefore,this thesis studies the simultaneous wireless information and power transfer(SWIPT)technology that integrates RF signal energy harvesting and traditional wireless information transmission in multi-user interference channels.The main contributions of this work are summarized as follows:Firstly,for the energy efficiency optimization problem in K-user MIMO interference channel,we jointly investigate SWIPT and interference alignment.The Max-SINR algorithm is used to eliminate the interference among users for information decoding while harvest the interference energy for energy harvesting.Taking the SINR and harvested power constraints into consideration,we then establish an energy efficiency optimal model.By analyzing the characteristics of the objective function of the optimization problem,the fractional programming theory is used to transform the non-convex optimization problem into K convex problems.Lastly,an EE-Max algorithm coupled with the Max-SINR,nonlinear fraction programming and one dimension searching is proposed to solve the reformulated problem,which can improve the energy efficiency of the system greatly,compared with the existing TZF method.Secondly,for the data transmission requirements of the downlink and uplink in K-user MISO interference channels,the data rate mathematical models of downlink and uplink are firstly established.Then,a weighted sum rate optimization model which considers the transmit power constraint of the access point is established.The access point transmits power and information by SWIPT in the downlink and the users transmit information by time division multiple access in the uplink.After the precoding vectors and the received filter vectors being obtained by transmit zero forcing method and the maximum ratio-combining algorithm,respectively,the non-convex optimization problem is then transformed into K convex problems.At the same time,by analyzing the characteristics of the objective function of the optimization problem,a weighted sum-rate optimization algorithm is proposed coupled with the golden section method,dichotomy and optimization theory,the effectiveness of which has been verified by simulations.Lastly,for the variable power splitting ratio of the weighted sum-rate optimization problem in K-user MISO interference channel,we first established a weighted sum-rate optimization model with the power splitting ratio and time division ratio as optimization variables.Then,a weighted sum-rate optimization algorithm is proposed based on the variable powersplitting ratio coupled with golden section method and one dimension searching,which can achieve better system performance than the algorithm with power splitting ratio as a fixed value.