Recent investigations have shown that with varying the amplitude of the external force, the deterministic ratchets exhibit multiple current reversals, which are undesirable in certain circumstances. To control the mul...Recent investigations have shown that with varying the amplitude of the external force, the deterministic ratchets exhibit multiple current reversals, which are undesirable in certain circumstances. To control the multiple reverse current to unidirectional current, an adaptive control law is presented inspired from the relation between multiple reversaJs current and the chaos-periodic/quasiperiodic transition of the transport velocity. The designed controller can stabilize the transport velocity of ratchets to steady state and suppress any chaos-periodic/quasiperiodic transition, namely, the stable transport in ratchets is achieved, which makes the current sign unchanged.展开更多
In order to support massive Machine Type Communication(mMTC) applications in future Fifth Generation(5G) systems,a key technical challenge is to design a highly effective multiple access protocol for massive connectio...In order to support massive Machine Type Communication(mMTC) applications in future Fifth Generation(5G) systems,a key technical challenge is to design a highly effective multiple access protocol for massive connection requests and huge traffic load from all kinds of smart devices,e.g.bike,watch,phone,ring,glasses,shoes,etc..To solve this hard problem in distributed scenarios with massive competing devices,this paper proposes and evaluates a Neighbor-Aware Multiple Access(NAMA) protocol,which is scalable and adaptive to different connectivity size and traffic load.By exploiting acknowledgement signals broadcasted from the neighboring devices with successful packet transmissions,NAMA is able to turn itself from a contention-based random access protocol to become a contention-free deterministic access protocol with particular transmission schedules for all neighboring devices after a short transition period.The performance of NAMA is fully evaluated from random state to deterministic state through extensive computer simulations under different network sizes and Contention Window(CW)settings.Compared with traditional IEEE802.11 Distributed Coordination Function(DCF),for a crowded network with 50 devices,NAMA can greatly improve system throughput and energy efficiency by more than 110%and210%,respectively,while reducing average access delay by 53%in the deterministic state.展开更多
In this paper, we study multiple shot noise process and its integral. We analyse these two processes systematically for their theoretical distributions, based on the piecewise deterministic Markov process theory devel...In this paper, we study multiple shot noise process and its integral. We analyse these two processes systematically for their theoretical distributions, based on the piecewise deterministic Markov process theory developed by Davis [1] and the martingale methodology used by Dassios and Jang [2]. The analytic expressions of the Laplace transforms of these two processes are presented. We also obtain the multivariate probability generating function for the number of jumps, for which we use a multivariate Cox process. To derive these, we assume that the Cox processes jumps, intensity jumps and primary event jumps are independent of each other. Using the Laplace transform of the integral of multiple shot noise process, we obtain the tail of multivariate distributions of the first jump times of the Cox processes, i.e. the multivariate survival functions. Their numerical calculations and other relevant joint distributions’ numerical values are also presented.展开更多
针对智能反射面(IRS, intelligent reflecting surface)辅助的多输入单输出(MISO, multiple input singleoutput)无线携能通信(SWIPT, simultaneous wireless information and power transfer)系统,考虑基站最大发射功率、IRS反射相移...针对智能反射面(IRS, intelligent reflecting surface)辅助的多输入单输出(MISO, multiple input singleoutput)无线携能通信(SWIPT, simultaneous wireless information and power transfer)系统,考虑基站最大发射功率、IRS反射相移矩阵的单位膜约束和能量接收器的最小能量约束,以最大化信息传输速率为目标,联合优化了基站处的波束成形向量和智能反射面的反射波束成形向量。为解决非凸优化问题,提出了一种基于深度强化学习的深度确定性策略梯度(DDPG, deep deterministic policy gradient)算法。仿真结果表明,DDPG算法的平均奖励与学习率有关,在选取合适的学习率的条件下,DDPG算法能获得与传统优化算法相近的平均互信息,但运行时间明显低于传统的非凸优化算法,即使增加天线数和反射单元数,DDPG算法依然可以在较短的时间内收敛。这说明DDPG算法能有效地提高计算效率,更适合实时性要求较高的通信业务。展开更多
利用认知无线电非正交多址接入(cognitive radio non-orthogonal multiple access,CR-NOMA)技术可缓解频谱资源短缺问题,提升传感设备的吞吐量。传感设备的能效问题一直制约着传感设备的应用。为此,针对CR-NOMA中的传感设备,提出基于深...利用认知无线电非正交多址接入(cognitive radio non-orthogonal multiple access,CR-NOMA)技术可缓解频谱资源短缺问题,提升传感设备的吞吐量。传感设备的能效问题一直制约着传感设备的应用。为此,针对CR-NOMA中的传感设备,提出基于深度确定策略梯度的能效优化(deep deterministic policy gradientbased energy efficiency optimization,DPEE)算法。DPEE算法通过联合优化传感设备的传输功率和时隙分裂系数,提升传感设备的能效。将能效优化问题建模成马尔可夫决策过程,再利用深度确定策略梯度法求解。最后,通过仿真分析了电路功耗、时隙时长和主设备数对传感能效的影响。仿真结果表明,能效随传感设备电路功耗的增加而下降。此外,相比于基准算法,提出的DPEE算法提升了能效。展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos. 10862001 and 10947011the Construction of Key Laboratories in Universities of Guangxi under Grant No. 200912
文摘Recent investigations have shown that with varying the amplitude of the external force, the deterministic ratchets exhibit multiple current reversals, which are undesirable in certain circumstances. To control the multiple reverse current to unidirectional current, an adaptive control law is presented inspired from the relation between multiple reversaJs current and the chaos-periodic/quasiperiodic transition of the transport velocity. The designed controller can stabilize the transport velocity of ratchets to steady state and suppress any chaos-periodic/quasiperiodic transition, namely, the stable transport in ratchets is achieved, which makes the current sign unchanged.
基金funded by the National Natural Science Foundation of China (Grant No.61231009)the National HighTech R&D Program of China(863)(Grant No.2014AA01A701)+5 种基金the National Science and Technology Major Project(Grant No. 2015ZX03001033-003)Ministry of Science and Technology International Cooperation Project(Grant No.2014DFE10160)the Science and Technology Commission of Shanghai Municipality(Grant No.14ZR1439600)the EU H2020 5G Wireless project(Grant No.641985)the EU FP7 QUICK project(Grant No. PIRSES-GA-2013-612652)the EPSRC TOUCAN project(Grant No.EP/L020009/1)
文摘In order to support massive Machine Type Communication(mMTC) applications in future Fifth Generation(5G) systems,a key technical challenge is to design a highly effective multiple access protocol for massive connection requests and huge traffic load from all kinds of smart devices,e.g.bike,watch,phone,ring,glasses,shoes,etc..To solve this hard problem in distributed scenarios with massive competing devices,this paper proposes and evaluates a Neighbor-Aware Multiple Access(NAMA) protocol,which is scalable and adaptive to different connectivity size and traffic load.By exploiting acknowledgement signals broadcasted from the neighboring devices with successful packet transmissions,NAMA is able to turn itself from a contention-based random access protocol to become a contention-free deterministic access protocol with particular transmission schedules for all neighboring devices after a short transition period.The performance of NAMA is fully evaluated from random state to deterministic state through extensive computer simulations under different network sizes and Contention Window(CW)settings.Compared with traditional IEEE802.11 Distributed Coordination Function(DCF),for a crowded network with 50 devices,NAMA can greatly improve system throughput and energy efficiency by more than 110%and210%,respectively,while reducing average access delay by 53%in the deterministic state.
文摘In this paper, we study multiple shot noise process and its integral. We analyse these two processes systematically for their theoretical distributions, based on the piecewise deterministic Markov process theory developed by Davis [1] and the martingale methodology used by Dassios and Jang [2]. The analytic expressions of the Laplace transforms of these two processes are presented. We also obtain the multivariate probability generating function for the number of jumps, for which we use a multivariate Cox process. To derive these, we assume that the Cox processes jumps, intensity jumps and primary event jumps are independent of each other. Using the Laplace transform of the integral of multiple shot noise process, we obtain the tail of multivariate distributions of the first jump times of the Cox processes, i.e. the multivariate survival functions. Their numerical calculations and other relevant joint distributions’ numerical values are also presented.
文摘针对智能反射面(IRS, intelligent reflecting surface)辅助的多输入单输出(MISO, multiple input singleoutput)无线携能通信(SWIPT, simultaneous wireless information and power transfer)系统,考虑基站最大发射功率、IRS反射相移矩阵的单位膜约束和能量接收器的最小能量约束,以最大化信息传输速率为目标,联合优化了基站处的波束成形向量和智能反射面的反射波束成形向量。为解决非凸优化问题,提出了一种基于深度强化学习的深度确定性策略梯度(DDPG, deep deterministic policy gradient)算法。仿真结果表明,DDPG算法的平均奖励与学习率有关,在选取合适的学习率的条件下,DDPG算法能获得与传统优化算法相近的平均互信息,但运行时间明显低于传统的非凸优化算法,即使增加天线数和反射单元数,DDPG算法依然可以在较短的时间内收敛。这说明DDPG算法能有效地提高计算效率,更适合实时性要求较高的通信业务。
