Research On Joint Wireless Information And Energy Transfer

Since radio frequency(RF)signals can be transformed into energy through RF to direct current(RF/DC)circuits,RF wireless energy transfer(WET)can continuously and wirelessly charge low-energy-cost wireless devices,tackling the lifetime bottleneck of energy limited devices caused by energy shortage.This paper focuses on the research on jointly wireless information and energy transfer methods,which can be classified into two promising researching fields,i.e.,simultaneous wireless information and power transfer(SWIPT),and wireless powered communications(WPC).Based on dual purposes of RF signals,SWIPT splits the received signal into two parts at the receiver.One part is used to information decoding(ID)and the other part is used to energy harvesting(EH).WPC adopts the harvestthen-transmit protocol,where the user equipment(UE)stores the received energy into their batteries,and then allocates these energy for the uplink information transmission.This paper puts emphasis on the joint design of wireless information and energy transfer through resource allocation,for both SWIPT and WPC.We focus on the following problems in this paper.Firstly,in SWIPT,spectral efficiency and received energy cannot achieve optimal value at the same time,because the received signal has to be split to ID and EH,respectively.The trade-off between ID and EH should be carefully designed through resource allocation,based on specific quality of service requirements of communication scenarios.Considering that one of the key features of the next generation of mobile networks is network densification,we introduce SWIPT in the coordinated multi-point(CoMP)downlink transmission(which is called SWIPT-CoMP downlink transmission),to enhance received signals and to reduce interference.Secondly,the limited backaul capacity can directly affect the performance of SWIPT-CoMP systems.EH is independent with EH data.The traditional power splitting method cannot split EH and ID signals at the transmitter,and therefore EH data has to be transmitted through backhaul,wasting the backaul capacity.Thirdly,for WPC systems,limited battery capacity and energy sensitivity of(i.e.,the minimum input signal power)RF/DC circuits will impact complexity of algorithm design and the system performance.However,up to now,no literature has taken these two constaints into consideration.Based on these three problems,the main content and contributions are summarized as follows.1.This paper proposes a fair power splitting algorithm for SWIPT-CoMP downlink transmissions.Based on beamforming design at the transmitter and the receiver,and the optimal power splitting factor of the receiver,optimal spectral efficiency is achieved.We formulate this problem as a max-min problem,which maximizes the minimum spectral efficiency among all the users with satisfying the harvested energy constraint and the per-base station(BS)transmission power constraint.This problem is a non-convex problem,which can be solved by a combination of mathematical methods,including introducing the slack variable,transforming spectral efficiency expression based on the minimum mean square error(MMSE)signal detector,addressing the reverse convex received energy constraint by successive convex approximation(SCA),and finally solving the original problem through alternating convex optimization(ACO).Therefore,the original optimization problem is recast as a second order cone programming(SOCP)problem.Compared with traditional semidefinite programming(SDP),SOCP has the high convergent speed,and avoids the rank one problem of SDP,where the rank of beamformer's covariance matrix should be one.2.This paper proposes a dual polarized-antenna based double side signal splitting method for SWIPT-CoMP transmission with limited backhaul capacity.This method takes the use of polarization diversity to split ID and EH signals at the RF domain.Compared with the conventional power splitting method,the advantages of the proposed algorithm are multiple folds.First,the splitting of ID and EH signals at the RF domain makes that there is no needs to transmit energy data from the central unit(CU)to remote radio units through backhaul links,because EH is independent with energy data of the received signal and EH data can be created at RRUs.This practice can avoid consumption of energy harvesting signals on backhaul capacity resources.Second,based on signal splitting at the RF domain of the receiver,few ID signals leak to the EH due to the cross polarization,improving the utilization of backhaul capacity.Third,the proposed method reduces computational complexity because solving the power splitting factor by the iteration method is avoided.This paper also adopts the rate splitting method to adaptively use CoMP transmission model(i.e.,CoMP joint processing(JP)and CoMP coordinated beamforming(CB)),which further splits user data into common and private parts.The common part adopts CoMP-JP transmission model,which needs transmitting common data from CU to all RRUs.The private part adopts CoMP-CB transmission model,where the private data is transmitted to the serving RRU of the data's user.The problem is formulated to maximize sum spectral efficiency while satisfying peruser harvested energy constraints,per-base station transmission power constraints,and per backhaul link capacity constraints.3.For the RF wireless powered multiple input multiple output(MIMO)uplink transmission,we put emphasis on limited capacity batteries and energy receiving sensitivity(i.e.,minimum required input power of the RF/DC circuit).We focus on optimal problem among multiple slots due to the limited capacity battery constraint which leads to independent between each slot.Multiple slot optimization has a better performance but suffers from more complex problem than existing single slot optimization.This paper forms a Bernoulli process with parameter p for the downlink WET.Before downlink WET,the BS estimates the received power at the receiver and performs WET only if the estimated power is larger than the energy receiving sensitivity,reducing the energy waste of the BS.We adopt energy beamforming during WET,based on which the WET probability p is calculated.The optimal problem is formulated as maximizing the average spectral efficiency among multiple slots while satisfying the energy battery capacity constraint(i.e.,the maximum energy can be stored in the battery),and the energy causality constraint(i.e.,the UL transmission can only use the energy harvested at the current and previous slots).To solve this non-convex problem,this paper provides joint time and power allocation algorithm.During the power allocation,p fraction of the available energy in the battery is allocated for the current slot uplink transmission,then water filling algorithm is adopted to allocate power for each antenna.Meanwhile,the time allocation is demonstrated as a convex problem and can be solved by one-dimensional search.Compared with existing methods,the proposed algorithm has the advantages of low computational complexity and high spectral efficiency performance.Furthermore,this paper has expanded the proposed algorithm into the multiple user scenario.