On Resource Optimal Control Technology For Wireless Communications

The growth of mobile traffic by a magnitude of thousands in the future,together with the amazing number of wireless devices that are accessing mobile networks,promotes a new wave of upgrades and a revolution in mobile communications technologies and the industry as a whole.However,the development of this prospective revolution is encountered with bottleneck,i.e.,radio frequency(RF)spectrum scarcity,mainly due to the RF spectrum is fixed and limited.Solutions to the RF spectrum scarcity problem are generally based on two directions.One direction is to improve spectrum efficiency by using cognitive radio(CR),which allows unlicensed users(or,secondary users)to access the same RF spectrum originally assigned to the licensed users(or,primary users)and controls the harmful interference under an acceptable threshold.Another direction is developing new wireless communications that capitalizes on higher frequencies,including millimeter wave(mm Wave)communications and free space optical(FSO)communications.In wireless networks,one crucial task is to design resource optimal control policies that can efficiently manage network resources for realizing the optimal system performance,while guaranteeing the required Quality of Service(Qo S).As a result,we investigate the resource optimal control policy in network scenarios related to solutions of RF spectrum scarcity.Specifically,we obtain the resource optimal control policies under different network scenarios,in which users aim to optimize system operating parameters,such as transmit power,spectrum access policy or beamwidth,to meet objectives such as maximal throughput,minimal energy consumption or maximal energy efficiency with limitations of power,spectrum and Qo S constraints.The main contents and contributions are summarized as follows.(1)We investigate the transmission strategy for cognitive radios(CR),which opportunistically operate on various primary users’(PUs’)channels with the aid of proactive spectrum handoff.Specifically,a secondary user(SU)in the CR network proactively predicts the future spectrum status and decides whether to keep idle,or stay in the current channel,or switch to a new channel to resume its transmission.A problem of completing a target data packet size of V bits within a predefined deadline D time slots is formulated as a discretetime Markov Decision Process(MDP),in which the SU aims at minimizing its expected total cost,i.e.,transmission cost,handoff cost and overtime penalty.We solve the problem using dynamic programming,and propose a general optimal transmission with proactive spectrum handoff(OTPH)algorithm whose complexity is 2 × |V| × D.Furthermore,we prove that for a convex penalty function,the optimal handoff aided transmission(OHT)exhibits a threshold structure.A monotone OTPH algorithm with a complexity of max(|V|,D)is used in this case.Simulation results verify that our proposed scheme achieves both the minimal total cost and the highest data transmission efficiency as compared with the traditional always staying and always changing schemes.(2)We investigate the optimal energy harvesting-ratio and beamwidth selection in millimeter wave(mm Wave)communications.Specifically,users in mm Wave communications operate in slotted mode,where each frame consists of three continuous segments – energy harvesting,beam-searching and data transmissions.In this sense,we propose a joint optimal energy harvesting-ratio and beamwidth selection scheme by maximizing the achievable throughput and energy efficiency,respectively.By using optimal theory,we solved these problems,and proposed implementation algorithms correspondingly.Simulation results validate the performance superiority of the proposed scheme.(3)We study transmission strategies for hybrid free space optical(FSO)/radio frequency(RF)systems by jointly considering link selection,power allocation,and reliability guarantees.Specifically,under an explicit long-term average reliability requirement,the transmitter in the hybrid FSO/RF system makes decisions about which links should be selected and how much power should be allocated to the corresponding active link.The problem of minimizing the power consumption cost while guaranteeing packet success-probability requirements and peak and average power constraints is considered and formulated as a stochastic optimal problem.Using the Lyapunov optimization techniques,we solve this problem and derive closed-form power allocation solutions for different link selection modes.Furthermore,we design a dynamic link selection and power allocation(DLSPA)algorithm that can arbitrarily push the consumed power approach to the optimum at the expense of a tradeoff over reliability.Simulation results verify the theoretical analysis and validate the performance superiority of our proposed scheme.