Research On Key Technologies Of Sustainable Wireless Communication For Internet Of Things

With the recent rapid development of communication technology,the Internet of Things(Io T)has become an important application of new generation communication technology.However,sustainable wireless communication for the Io T faces serious energy supply and energy-saving requirements.Firstly,the wireless communication network has occupied a lot of spectrum resources,resulting in the spectrum scarcity issue for efficient wireless power transfer(WPT).Secondly,as most wireless devices have very limited energy,we need to improve their energy efficiency to save energy.At last,the efficiency of WPT is low,resulting in a small coverage area of energy supply and very limited application deployment.This thesis aims to solve the above problems of sustainable wireless communication from both energy supply and demand perspectives.In particular,this thesis investigates the cognitive WPT system based on cognitive radio(CR)spectrum sharing technology,the unmanned aerial vehicle(UAV)-enable data collection system with distributed beamforming,and the UAV-enable wireless powered communication network(WPCN).The main results are as follows.First,from a WPT perspective,this thesis studies a cognitive or secondary multi-antenna WPT system over a multi-carrier channel to improve spectral efficiency,which shares the same spectrum with a primary wireless information transfer(WIT)system.By controlling the transmit energy beamforming over sub-carriers(SCs),the secondary energy transmitter(S-ET)can directly charge the secondary energy receiver(S-ER),even purposely interfere with the primary WIT system,such that the primary information transmitter(P-IT)can reactively adjust its power allocation(based on waterfilling)to facilitate the S-ER's energy harvesting.We investigate how the secondary WPT system can exploit the primary WIT system's reactive power allocation,for improving the wireless energy harvesting performance.In particular,our objective is to maximize the total energy received at the S-ER from both the S-ET and the PIT,by optimizing the S-ET's energy beamforming over SCs,subject to its maximum transmit power constraint,and the maximum interference power constraint imposed at the primary information receiver(P-IR)to protect the primary WIT.Although the formulated problem is non-convex and difficult to be optimally solved in general,we propose an efficient algorithm to obtain a high-quality solution by employing the Lagrange dual method together with a onedimensional search.We also present two benchmark energy beamforming designs based on the zero-forcing and maximum-ratio-transmission principles,respectively,as well as the conventional design without considering the primary WIT system's reaction.Numerical results show that our proposed design leads to significantly improved the total energy received at the S-ER from both the S-ET and the P-IT,as compared to these benchmark schemes.Therefore,this design can power the network equipment better and enhance the sustainability of wireless communications.Second,an energy-efficient data collection system is studied from the point of view of improving energy utilization efficiency for Io T devices at the demand side.This thesis studies a new UAV-enabled wireless sensor network,in which one UAV flies in the sky to collect the data transmitted from a set of ground nodes(GNs)via distributed beamforming.We consider two scenarios with delay-tolerant and delay-sensitive applications,in which the GNs send the common/shared messages to the UAV via adaptive-rate and fixed-rate transmissions,respectively.For the two scenarios,we aim to maximize the average data-rate throughput and minimize the transmission outage probability,respectively,by jointly optimizing the UAV's trajectory design and the GNs' transmit power allocation over time,subject to the UAV's flight speed constraints and the GNs' individual average power constraints.However,the two formulated problems are both non-convex and thus generally difficult to be optimally solved.To tackle this issue,we first consider the relaxed problems in the ideal case with the UAV's flight speed constraints ignored,for which the well-structured optimal solutions are obtained to reveal the fundamental performance upper bounds.It is shown that for the two approximate problems,the optimal trajectory solutions have the same multi-location-hovering structure,but with different optimal power allocation strategies.Next,for the general problems with the UAV's flight speed constraints considered,we propose efficient algorithms to obtain highquality solutions by using the techniques from convex optimization and approximation.Finally,numerical results show that our proposed designs significantly outperform other benchmark schemes,in terms of the achieved data-rate throughput and outage probability under the two scenarios.It is also observed that when the mission period becomes sufficiently long,our proposed designs approach the performance upper bounds when the UAV's flight speed constraints are ignored.Therefore,this design can improve the energy efficiency of the GNs and enhance the sustainability of wireless communication.Finally,by considering both supply and demand sides,this thesis studies a UAV-enable wireless powered communication network(WPCN)with distributed beamforming.In this network,the UAV powers multiple clusters of GNs,and the GNs in each cluster send the common data to the UAV by using distributed beamforming with the received energy.For the scenario of delay-tolerant applications,the objective is to maximize the common average datarate throughput,by jointly optimizing UAV's trajectory design and GNs' resource allocation over time,subject to UAV's flight speed constraints and GNs' energy neutrality constraints.Although the problem is non-convex and difficult to be optimally solved in general,we propose an efficient algorithm to obtain the performance upper bound and a high-quality solution by using the techniques from convex optimization and approximation.We also present three intuitive designs that can be used as initial points for the algorithm.Numerical results show that our proposed design leads to much better common average data-rate throughput,as compared to these initial points.Therefore,the design can not only efficiently supply energy to the GNs,but also improve the energy efficiency of the GNs and enhance the sustainability of wireless communications.In summary,in order to achieve sustainable wireless communication,this thesis proposes effective approaches in terms of both WPT and energy saving for the Io T.It is expected that the research results in this thesis can provide useful solutions to support the sustainable operation of Io T in a wider range.