An Improved Random Access Scheme for M2M Communications

In this study, an improved random access(RA) scheme for Machine-to-Machine(M2M) communications is proposed. The improved RA scheme is realized by two steps. First, the improved RA scheme achieves a reasonable resource tradeoff between physical random access channel(PRACH) and physical uplink shared channel(PUSCH). To realize a low-complexity resource allocation between PRACH and PUSCH, a boundary of traffic load is derived to divide the number of active M2 M users(UEs) into multiple intervals. The corresponding resource allocation for these intervals is determined by e NB. Then the resource allocation for other number of UEs can be obtained from the allocation of these intervals with less computation. Second, the access barring on arrival rate of new UEs is introduced in the improved RA scheme to reduce the expected delay. Numerical results show that the proposed improved RA scheme can realize a low-complexity resource allocation between PRACH and PUSCH. Meanwhile, the expected delay can be effectively reduced by access barring on arriving rate of new M2 M UEs.

Random Access and Resource Allocation for the Coexistence of NOMA-Based and OMA-Based M2M Communications

In the future fifth generation(5G) systems,non-orthogonal multiple access(NOMA) is a promising technology that can greatly enhance the network capacity compared to orthogonal multiple access(OMA) .In this paper,we propose a novel random access(RA) and resource allocation scheme for the coexistence of NOMA-based and OMAbased machine-to-machine(M2M) communications,which aims at improving the number of successful data packet transmissions and guaranteeing the quality of service(Qo S) (e.g.,the minimum data rate requirement) for M2 M communications.The algorithm of joint user equipment(UE) paring and power allocation is proposed for the coexisting RA(i.e.,the coexistence of NOMA-based RA and OMA-based RA) .The resource allocation for the coexisting RA is investigated,thus improving the number of successful data packet transmissions by more efficiently using the radio resources.Simulation results demonstrate that the proposed RA and resource allocation scheme outperforms the conventional RA in terms of the number of successful data packet transmissions,thus is a promising technology in future M2 M communications.

Unsourced Multiple Access for 6G Massive Machine Type Communications

Unsourced multiple access(UMA)is a multi-access technology for massive,low-power,uncoordinated,and unsourced Machine Type Communication(MTC)networks.It ensures transmission reliability under the premise of high energy efficiency.Based on the analysis of the 6G MTC key performance indicators(KPIs)and scenario characteristics,this paper summarizes its requirements for radio access networks.Following this,the existing multiple access models are analyzed under these standards to determine UMA's advantages for 6G MTC according to its design characteristics.The critical technology of UMA is the design of its multiple-access coding scheme.Therefore,the existing UMA coding schemes from different coding paradigms are further summarized and compared.In particular,this paper comprehensively considers the energy efficiency and computational complexity of these schemes,studies the changes of the above two indexes with the increase of access scale,and considers the trade-off between the two.It is revealed by the above analysis that some guiding rules of UMA coding design.Finally,the open problems and potentials in this field are given for future research.

Finite family trees of continuous time birth and death processes for evaluating the transmitting speed of information on communication networks

A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are the living particles, and directed edges go from mothers to daughters. The size of the communication network was studied. Furthermore, the probability of successfully connecting senders with receivers and the transmitting speed of information were obtained.

Optimal chunk caching in network coding-based qualitative communication

Network processing in the current Internet is at the entirety of the data packet,which is problematic when encountering network congestion.The newly proposed Internet service named Qualitative Communication changes the network processing paradigm to an even finer granularity,namely chunk level,which obsoletes many existing networking policies and schemes,especially the caching algorithms and cache replacement policies that have been extensively explored in Web Caching,Content Delivery Networks(CDN)or Information-Centric Networks(ICN).This paper outlines all the new factors that are brought by random linear network coding-based Qualitative Communication and proves the importance and necessity of considering them.A novel metric is proposed by taking these new factors into consideration.An optimization problem is formulated to maximize the metric value of all retained chunks in the local storage of network nodes under the constraint of storage limit.A cache replacement scheme that obtains the optimal result in a recursive manner is proposed correspondingly.With the help of the introduced intelligent cache replacement algorithm,the performance evaluations show remarkably reduced end-to-end latency compared to the existing schemes in various network scenarios.

Distributed Hybrid Model Predictive Secondary Control of DC Microgrids with Random Communication Disorders

A reliable and robust communication network is essential to exchange information between distributed generators(DGs)and accurately calculate their control actions in microgrids(MGs).However,the integration of the communication network and MGs poses challenges related to the flexibility,availability,and reliability of the system.Furthermore,random communication disorders such as time delays and packet loss can negatively impact the system performance.Therefore,it is essential to design a suitable secondary controller(SC)with a fast dynamic response to restore voltage and appropriate powersharing,while ensuring that the effects of random communication disorders are eliminated.In this regard,an optimal distributed hybrid model predictive secondary control method is presented in this paper.Realistic simulations are carried out in a mixed simulation environment based on MATLAB and OMNET++,by considering IEEE 802.11(Wi Fi)using the recently developed Internet networking(INET)framework.In the implemented application layer,the recovery Unit is responsible for reducing the impact of random communication disorders.The effectiveness and performance of the proposed method in comparison with a conventional model predictive control are verified by simulation results.

Time-delayed feedback control optimization for quasi linear systems under random excitations

A strategy for time-delayed feedback control optimization of quasi linear systems with random excitation is proposed. First, the stochastic averaging method is used to reduce the dimension of the state space and to derive the stationary response of the system. Secondly, the control law is assumed to be velocity feedback control with time delay and the unknown control gains are determined by the performance indices. The response of the controlled system is predicted through solving the Fokker-Plank-Kolmogorov equation associated with the averaged Ito equation. Finally, numerical examples are used to illustrate the proposed control method, and the numerical results are confirmed by Monte Carlo simulation .

Random-injection-based two-channel chaos with enhanced bandwidth and suppressed time-delay signature by mutually coupled lasers: Proposal and numerical analysis

Simultaneous bandwidth(BW) enhancement and time-delay signature(TDS) suppression of chaotic lasing over a wide range of parameters by mutually coupled semiconductor lasers(MCSLs) with random optical injection are proposed and numerically investigated. The influences of system parameters on TDS suppression(characterized by autocorrelation function(ACF) and permutation entropy(PE) around characteristic time) and chaos BW are investigated. The results show that, with the increasing bias current, the ranges of parameters(detuning and injection strength) for the larger BW(> 20 GHz) are broadened considerably, while the parameter range for optimized TDS(< 0.1) is not shrunk obviously.Under optimized parameters, the system can simultaneously achieve two chaos outputs with enhanced BW(> 20 GHz)and perfect TDS suppression. In addition, the system can generate two-channel high-speed truly physical random number sequences at 200 Gbits/s for each channel.

Delay-Optimal Random Access in Large-Scale Energy Harvesting IoT Networks Based on Mean Field Game

With energy harvesting capability, the Internet of things(IoT) devices transmit data depending on their available energy, which leads to a more complicated coupling and brings new technical challenges to delay optimization. In this paper,we study the delay-optimal random access(RA) in large-scale energy harvesting IoT networks. We model a two-dimensional Markov decision process(MDP)to address the coupling between the data and energy queues, and adopt the mean field game(MFG) theory to reveal the coupling among the devices by utilizing the large-scale property. Specifically, to obtain the optimal access strategy for each device, we derive the Hamilton-Jacobi-Bellman(HJB) equation which requires the statistical information of other devices.Moreover, to model the evolution of the states distribution in the system, we derive the Fokker-PlanckKolmogorov(FPK) equation based on the access strategy of devices. By solving the two coupled equations,we obtain the delay-optimal random access solution in an iterative manner with Lax-Friedrichs method. Finally, the simulation results show that the proposed scheme achieves significant performance gain compared with the conventional schemes.

Markov Chain Induced by Random Dynamical System on Graph

In this paper, we define a model of random dynamical systems（RDS） on graphs and prove that they are actually homogeneous discrete-time Markov chains. Moreover, a necessary and sufficient condition is obtained for that two state vectors can communicate with each other in a random dynamical system（tLDS）.

Enhancement of MTC Performance in LTE Networks by Maximizing Random Access Procedure Throughput

A fundamental requirement for any cellular system is the possibility for the device to request a connection setup, commonly referred to as random access procedure. In LTE （long term evolution） networks, the distribution of a limited number of radio resources among H2H （Human-to-Human） users and increasing number of MTC （Machine-Type-Communication） devices in M2M （Machine-to-Machine） communications is one of the main problems. An analytical model is conducted to compute the throughput for message 1 and message 2. This is done using a Markov chain model for the four messages signaling flow with buffering for message 4. This model is used in LTE 3GPP （Third-Generation Partnership Project） random access. The network performance will be enhanced by determining a dedicated arrival rate corresponding to maximum throughput of message 2 that will assist the network planner to optimize the network performance. In this paper, a deduced arrival rate less than 3.333 requests/ms will maximize network throughput.

Help from space:grant-free massive access for satellite-based IoT in the 6G era

The Sixth-Generation(6G)standard for wireless communications is expected to realize ubiquitous coverage for massive Internet of Things(IoT)networks by 2030.Satellite-based communications are recognized as a highly promising technical enabler to satisfy IoT service requirements in the 6G era.This study analyzes multiple access technologies,which are essential for the effective deployment of satellite-based IoT.First,we thoroughly investigate the existing research related to massive access,including information-theory considerations as well as Non-Orthogonal Multiple Access(NOMA)and Random Access(RA)technologies.Then,we explore the influence of the satellite transmission environment on multiple access technologies.Based on this study,a Non-orthogonal Massive Grant-Free Access(NoMaGFA)scheme,which reaps the joint benefits of RA and NOMA,is proposed for asynchronous transmissions in satellite-based IoT to achieve improved system throughput and enhance the system robustness under varying traffics.Finally,we identify some important and interesting future developments for satellite-based IoT,including waveform design,transceiver design,resource allocation,and artificial intelligence-enhanced design.

Multi-Cluster Flocking Behavior Analysis for a Delayed Cucker-Smale Model with Short-Range Communication Weight

This paper analyzes the multi-cluster flocking behavior of a Cucker-Smale model involving delays and a short-range communication weight.In each sub-flocking group,the velocity between agents is alignment and the position locates at a limited domain;but in different sub-flocking groups,the position between agents is unbounded.By constructing dissipative differential inequalities of subensembles together with Lyapunov functional methods,the authors provide the sufficient condition for the multi-cluster flocking emerging.The sufficient condition includes the estimation of the range of coupling strength and the upper bound of time delay.As a result,the authors show that the coupling strength among agents and initial threshold value determine the multi-cluster flocking behavior of the delayed Cucker-Smale model.

Design of intelligent detecting system based on wireless transmission

An intelligent detecting system based on wireless transmission is designed. Its hardware includes the card reading module, the wireless digital transmission module, the LCD module, the random password keyboard module and a 16×16 lattice word database based on e-Flash MM36SB020. Its software is a communication protocol between the central control computer and the entrance management base station. To resolve the conflicting problems occurred during the data transmission, a method of delaying time at random is proposed.

Achievable Secrecy Rate Region of Two-Way Communication with Secret Key Feedback

This paper investigates the achievable secrecy rate region of the Gaussian two-way wiretap channel,which describes the simultaneous secure two-way transmission of a confidential message. Through adjusting the time-sharing factor and the rate at which the random secret key is fed back, the allocation and optimization for the secrecy rates of two-way communication are achieved. Under peak and average power constraints, the achievable secrecy rate regions of the two-way communication are derived respectively.

Enhanced Multiparty Controlled QSDC Using GHZ State

Recently, Gao et al. [Opt. Commun. 283 （2010） 192] pointed out that Wang et al,＇s multiparty controlled quantum secure direct communication （CQSDC） protocol [Opt. Commun. 266 （2006） 732] has the information leakage problem and proposed an improved protocol. However, in the improved protocol, due to the introduction of an additional random sampling to avoid the weakness, the qubit efficiency is decreased. By introducing the base changing technique to the random sampling in Wang et al. ＇s protocol, this study overcomes the information leakage problem and provides a better qubit efficiency.

Distributed Optimal Control of Nonlinear Time-Delay System Subject to Delayed Measurements and Communication Disruptions

This paper is focused on a distributed optimal control design for a class of nonlinear timedelay systems with delayed measurements and communication disruptions.The innovation lies in three aspects.The distributed optimal control method which includes an optimal controller and a bounded controller is designed based on Lyapunov function.The availability of data transmitted through the communication channel depends on a feasibility problem.And a sufficient condition to guarantee ultimate boundedness of the system is given based on appropriate assumptions.The significance of this paper is that this distributed optimal control method is applied to time-delay system.Finally,a simulation example is given to verify the effectiveness of the proposed method.

Optimal Secondary Control of Islanded AC Microgrids with Communication Time-delay Based on Multi-agent Deep Reinforcement Learning

In this paper,an optimal secondary control strategy is proposed for islanded AC microgrids considering communi-cation time-delays.The proposed method is designed based on the data-driven principle,which consists of an offine training phase and online application phase.For offline training,each control agent is formulated by a deep neural network(DNN)and trained based on a multi-agent deep reinforcement learning(MA-DRL)framework.A deep deterministic policy gradient(DDPG)algorithm is improved and applied to search for an optimal policy of the secondary control,where a global cost function is developed to evaluate the overall control performance.In addition,the communication time-delay is introduced in the system to enrich training scenarios,which aims to solve the time-delay problem in the secondary control.For the online stage,each controller is deployed in a distributed way which only requires local and neighboring information for each DG.Based on this,the well-trained controllers can provide optimal solutions under load variations,and communication time-delays for online applications.Several case studies are conducted to validate the feasibility and stability of the proposed secondary control.Index Terms-Communication time-delay,global cost function,islanded AC microgrid,multi-agent deep reinforcement learning(MA-DRL),secondary control.

随机环境中受传染性疾病影响的分枝过程的极限性质

给出了独立随机环境中受传染性疾病影响的分枝过程{Z_(n),n∈N}的模型,讨论了该模型的极限性质,并给出了分枝过程经{S_(n),n∈N}和{U_(n),n∈N}规范化后{W_(n),n∈N}和{W_(n),n∈N}几乎处处收敛和L^(1)收敛的充分条件,得到{W_(n),n∈N}L^(2)收敛的充分条件和{W_(n),n∈N}极限非退化到0的充分条件和必要条件。

Synchronization of Stochastic Memristive Neural Networks with Retarded and Advanced Argument

In this paper, we discuss the driving-response synchronization problem for two memristive neural networks with retarded and advanced arguments under the condition of additional noise. The control law is related to the linear time-delay feedback term, and the discontinuous feedback term. Moreover, the random different equation is used to prove the stability of this theory. At the end, the simulation results verify the correctness of the theoretical results.