Transmission Theory And Key Technologies For Energy Harvesting Wireless Communication Systems

With the rapid development of wireless communication technology,the load capacity and coverage scale of wireless communication system have been improved.Meanwhile,there has seen an explosive increase in the number of wireless terminal and data traffic.As a result,the whole wireless communication industry becomes a “huge household” for consuming the energy.On the other hand,as the rise of mobile Internet,Internet of things and multimedia technology,higher requirements have been posed to wireless equipment by diversified services.The energy-limited characteristic of traditional wireless devices will be the “bottleneck” for user experience at the terminal side.As such,how to improve the spectral efficiency as well as reducing the energy consumption has emerged as a key issue for designing next generation wireless communications.The concept of energy harvesting(EH),once introduced,casts dawn light on the horizon of wireless communications,as it powers wireless devices by scavenging energy from the ambient environment.An EH based wireless communication system introduces several transformative changes which solve the energy consumption problem brought by the development of wireless communications.However,the time/space domain ‘distribution' and the random/intermittent characteristics of harvesting energy interact in a new challenge on the design of transmission and energy management schemes.The goal of this thesis is to bring forth promising solutions that address transmission strategies and performance optimization of EH wireless communication systems,including EH model,storage imperfection,resource allocation as well as joint wireless information and energy transfer.The main contributions are summarized as follows:1)Optimal throughput scheme design and analysis for energy harvesting wireless communication systems.This work studies the optimal energy management and transmission polices on static and flat-block fading channels under the criterion of throughput maximization.Different from the commonly used harvest-store-use(HSU)scheme,a noval storage management policy is proposed in this work,i.e.,harvest-use-store(HUS)scheme,to coordinate the randomness of harvesting energy and the imperfection of storage,where the harvested energy is prioritized for use in data transmission while its balance/debt is stored in or extracted from the storage device.The optimization is done in the Lagrangian framework,uncovering the special structure of the optimal power pattern and obtaining a closed-form solution conditioned on the knowledge of the block locations for zero battery level.A dynamic programming(DP)based algorithm is developed for locating such blocks in the optimal power patterns.Numerical results are presented to demonstrate the properties of the proposed HUS architecture and its superior performance over the existing schemes.2)Offline and online transmission policy design for energy harvesting wireless systems in frequency-selective fading channels.This work focuses on the EH optimal transmission problem under the quasi-static frequency-selective fading channel,which analyzes the problem of maximizing the data transmission for the point-to-point(P2P)wireless communication systems from two perspectives: offline or deterministic(for non-causal),and online or stochastic(for causal)energy harvesting profiles.To balance the energy stored in or extracted from the battery for maximization throughput with the randomly arrival harvesting energy constraint,we first characterize the amazing properties of our optimal offline policy,implying a double-threshold structure of the solution,then investigate a dynamic programming(DP)-based double-layer optimal waterfilling allocation policy to solve the double-domain waterfilling problem(time and frequency domain).Further,the work tends to analyze the online solution.We first provide the optimal policy based on the continuous time stochastic dynamic programming.Then,two heuristic online policies are proposed building on the intuition from the optimal offline policy(i.e.,double-threshold structure),which are simple to be implemented.Numerical results are presented to validate the theoretical analysis and show that the proposed online policies track well to the optimal solution.3)Optimal energy efficiency design for delay-constrained energy harvesting wireless communications.This work considers the minimization transmission energy problem,which is equal to keep the final energy storage maximized in order to achieve reliable and efficient energy scheduling for the next scheduling period.Therefore,we first prove that the optimal transmission is a non-idling transmission,which means that the transmission lasts all the blocks without any break.Based on this,a prescribed data threshold and battery residual energy(PDTBRE)region is proposed to characterize all the possible pairs for wireless information bits and energy efficiency.In order to obtain the boundary point of the region(i.e.,the corresponding optimal power allocation solution of the maximum energy efficiency),a double-threshold structure is characterized,which illustrates that the power allocated is related to the battery mode and is monotonic.For the block fading case,it is found that the optimal solution has a waterfilling interpretation with double thresholds.Rather than having a single water level,there are multiple water levels that are nondecreasing over time.Numerical results are provided to validate the theoretical analysis and to compare the optimal solutions with existing schemes.4)Simultaneous wireless information and power transfer design for energy cooperation distributed antenna systems(DAS).This work studies simultaneous wireless information and power transfer(SWIPT)for a multiple-input single-output(MISO)DAS in the downlink which consists of arbitrarily distributed remote antenna units(RAUs).In order to save the energy cost,we adopt energy cooperation of energy harvesting(EH)and two-way energy flows to let the RAUs trade their harvested energy through the smart grid network.To supply maximum wireless information transfer(WIT)with a minimum WET constraint for a receiver adopting power splitting(PS),a power management strategy is investigated to determine how to utilize the stochastically spatially distributed harvested energy at the RAUs and how to trade the energy with the smart grid simultaneously.We realize the above objective without any usage of non green energy,considering both the smart grid profitable and smart grid neutral cases.For the grid-profitable case,the most promising solution is the optimal full power strategy.Based on this,we provide a closed-form result to see under what condition this strategy is used.On the other hand,for the grid-neutral case,it is illustrated that the optimal power policy has three special properties.Building on the double-threshold structure,this work proposes a more efficient algorithm to obtain the optimal allocation strategy.Simulation results are provided to show the SWIPT performance under various settings.