Research On Energy Harvesting Distributed MIMO System Wireless Transmission Method

With the gradual application and development of the fifth generation?5G?mobile communication system and the increase of mobile users and equipment,the energy consumption problem of ICT industry will always exist and become increasingly serious.Green communication has attracted more and more attention and en-ergy efficiency?EE?indicators have become more and more important indicators to measure communication systems.On the one hand,energy harvesting is a promising technology for green communication by harvest-ing renewable energy from the environment.The main difference between renewable energy and traditional non-renewable energy is that its power is time-varying and limited in most cases.Therefore,it is necessary to re-examine the power management strategies in all existing wireless communication systems.On the other hand,distributed system with its high spectrum efficiency and energy efficiency is also a potential scheme for green communication.This paper mainly studies transmission strategies for three different distributed down-link wireless communication systems,namely,hybrid energy-supplied orthogonal frequency division access?OFDMA?downlink system,hybrid energy-supplied distributed downlink system with energy cooperation,and distributed multi-input single-output?MISO?system with simultaneous wireless information and power transfer?SWIPT?.Firstly,we introduce statical characteristics of wireless communication channel and the basic theory of MIMO and distributed antenna system?DAS?.Furthermore,we briefly describe energy harvesting technol-ogy.Then,the linear and non-linear models of the energy harvesting at the receiver are studied.A typical optimization of SWIPT systems is discussed and simulated to compare the linear and non-linear models.In addition,three precoding techniques are introduced as the basis for future research.Subsequently,a resource allocation scheme is proposed for distributed OFDMA system with hybrid power supply base station,where energy harvesting and non-renewable power sources are used complemen-tarily.A joint subcarrier and power allocation problem is formulated for minimizing the Joule-per-bit system with quality of service?QoS?and bit error rates constraints.The problem is a 0-1 mixed integer nonlinear programming problem due to the binary subcarrier allocation variable.To solve the problem we design an algorithm based on Lagrange relaxation method and fraction programming which optimizes the power allo-cation and subcarrier allocation iteratively in two nest.Simulation results show that the proposed algorithm converges in a small number of iterations and the scheme can improve EE of system greatly.Then,we investigates the joint power allocation and energy cooperation problem in a multiuser down-link DAS with hybrid energy supply.We focus on the energy efficiency maximization problem for three different types of precoding,zero-forcing?ZF?,general beamforming method and conjugate-beamforming.For ZF precoding with no user interference in achievable rate,we apply fractional programming and reform the optimization problem to a convex one.An iterative algorithm to deal with the fractional objective function is presented.Whereas the problem is non-convex for general beamforming with user interference,we take maximum ratio transmission?MRT?as an example and adopt a set of transformation and approximation based on difference of convex?DC?programming.Furthermore,for conjugate-beamforming we first transform the quadratic signal to interference plus noise power ratio?SINR?into a trackable form and then DC programming is applied.A two loops algorithm for the general beamforming and conjugate-beamforming is presented with fractional programming in the inner loop and DC programming in the outer loop.Simulation results show that the proposed algorithm improved EE significantly and indicate that energy cooperation can contribute to a higher EE.It also reveals that ZF achieves better EE with small noise variance while conjugate beamforming in high noise circumstance.Finally,we investigates the joint beamforming and power splitting factor optimization in distributed MISO systems with power-splitting SWIPT.Due to inefficiency of wireless energy transmission,we assume that all the user equipment?UE?perform data transmission whereas only UEs with sufficient large scale fad-ing,defined as SWIPT UEs,also conduct energy harvesting.System total power consumption minimization problem is formulated with per-UE QoS constraints and minimal harvesting power constraints for SWIPT UEs with the consideration of RAU selection.First,we classify the UEs into two groups according to the large scale fading criterion.Then for perfect channel state information?CSI?,the optimal problem is formulat-ed and approximated by transforming RAU mode indicator function into reweighted?₁-norm.Semi-definite relaxed?SDR?method is used and an iterative algorithm is proposed.Further,we consider the optimization with imperfect CSI and change the constraints to the worst case.To guarantee the rank-one constraint,an iterative function based on penalty function is proposed.Simulations show that the proposed algorithms with RAU selection can significantly reduce system total power consumption and also reveal that the RAU closest to SWIPT UEs tends to be active.