基于退避预测的ACB动态接入新方案

在LTE-A网络的过载场景中,机器类通信（Machine Type Communication,MTC）设备的突发性接入会使得网络发生严重的拥塞,甚至死锁,造成网络的接入效率低下.在可用前导资源有限的前提下,根据实时负载数控制发起接入的设备数可以有效降低前导的碰撞概率,但是控制方法尚不明确.为此,本文提出了一种接入类别限制（Access Class Barring,ACB）的动态接入机制来优化海量MTC的随机接入性能.建立了一种基于退避预测的估计模型,该模型根据重传的设备数和状态转移过程估计出了实时活跃的设备数.结合估计模型和ACB参数调整可以最优化实时成功接入的设备数,能够有效地提高设备的接入成功率.本文在不同负载强度场景下,将提出的ACB动态接入机制和现有的动态ACB机制的接入性能进行了比较.仿真结果证明,本文提出的ACB动态接入机制的接入成功率为100%.而且,与现有的ACB动态接入机制相比,所提的新方案的平均接入时延更低.     

A Novel Group Paging Control Method for Massive MTC Accesses in LTE Networks

The fifth-generation (5G) systems have to deal with massive deployment of machine-type-communication (MTC) devices. System overload may occur during a random access procedure under a limited number of preamble resources and physical uplink shared channel resources especially when there exist massive MTC devices in a cell. In order to resolve the system overload (caused by the massive MTC deployment), the 3GPP proposed the adopted a group paging (GP)-based uplink access technique. But its performances dramatically decrease as the number of MTC devices increases. In this paper we propose a novel method, named ACB-based group paging overload control method (AGO). To reduce the number of simultaneous access MTC devices, AGO first scatters the MTC devices over a GP interval, and then automatically adjusts ACB parameters according to the load conditions. By doing so, AGO achieves high-channel access probability for MTC devices. Simulation results show that this method is superior to the GP and Pre-backoff mechanisms in terms of success and collision probability, average access latency and resource utilization rate.

     

5G异构网络中基于优先级的深度强化学习联合资源分配

为了研究基于深度强化学习(Deep Reinforcement Learning, DRL)的5G异构网络模型的性能,同时在最小化系统能耗并满足不同类型终端用户的服务质量要求的基础上制定合理的资源分配方案,提出了一种基于DRL的近端策略优化算法,并结合一种基于优先级的分配策略,引入了海量机器类型通信、增强移动宽带和超可靠低延迟通信业务。所提算法相较于Greedy和DQN算法,网络延迟分别降低73.19%和47.05%,能耗分别降低9.55%和6.93%,而且可以保证能源消耗和用户延迟之间的良好权衡。     

机器类通信中基于负载反馈的拥塞控制方法

通过分析LTE-Advanced系统中机器类通信（MTC）设备的随机接入效率,提出一种负载反馈控制的改进方法。利用前导状态信息估计当前负载并预测下一接入时隙的负载,然后基于负载的变化调整MTC设备接入控制参数,减少了大量MTC 设备突发性接入对人与人（H2H）设备的影响,能有效降低重传次数,提升接入成功率。通过仿真分析说明所提方案有效可行,具有良好性能。     

支持混合业务的5G自适应调度和复用技术

5G标准规范目前的版本以满足IMT-2020对数据速率、时延、可靠性等需求为目标,支持增强型移动宽带、超可靠低延时通信、大规模机器类型通信三种应用。为满足5G演进系统中混合部署更多业务类型,服务更加多样化设备的需求,本文研究自适应调度和复用增强的策略,确定通过提高调度准确性、增强基于配置的调度流程、自适应工作带宽调整、改进终端设备内部混合多业务处理流程、增强多业务的复用方式、优化干扰管理和控制、支持同频复用不同空口参数集合方面的技术演进可适配不同等级的设备,满足混合业务各自在可靠性、可获得性、可维护性、安全性和完整性方面的需求。     

卫星通信系统两步随机接入技术研究

为了实现卫星通信系统低延迟高可靠接入,研究了两步随机接入技术中的信道设计及接收端检测算法.针对卫星场景提出了一种两步随机接入信道设计方案,对两步随机接入信道中数据部分的信道结构以及前导和数据之间的映射方式进行了设计.针对传统最小均方串行干扰消除(Minimum Mean Squared Error-Successive Interference Cancellation,MMSE-SIC)算法中存在误差传播问题导致解码性能降低的问题,提出了一种多判决排序串行干扰消除(Multi-decision Ordered Successive Interference Cancellation,MD-OSIC)算法,以提升多用户发起接入时数据部分检测的可靠性.仿真结果验证了所设计信道及检测算法在典型卫星通信场景下应用的可行性.     

Duplicated transmission based-resource scheduling for uplink grant-free SCMA system

Sparse code multiple access-based uplink grant-free transmission (SCMA-UGFT) has been proposed to realize ultra reliable and low latency communication (URLLC) in the fifth generation (5G) system. Without the process of resource request and grant, users may collide in the same resource. To compensate the potential user performance decline, resource scheduling becomes a tough issue in the SCMA-UGFT system. This article proposes a duplicated transmission-based resource scheduling (DTBRS) scheme for SCMA-UGFT system by considering the URLLC scenario. Different from the existing schemes, not only one shared basic transmission units (BTUs) are allocated to a user equipment ( UE) in the proposed DTBRS scheme for initial transmission to realize the duplicated transmission and to guarantee the transmission reliability. Besides, according to the proposed DTBRS scheme, one or two exclusive BTUs are assigned to a UE for retransmission to avoid the re-collision. At last, each packet is given a lifetime to limit the transmission latency to meet the URLLC latency requirement. The simulation demonstrates that the DTBRS scheme can achieve a better performance than the existing state-of-the-art scheme in terms of the average packet drop rate.     

Multiple access based on different lengths super orthogonal codes to support QoS of M2M communications in next generation networks

Global connectivity, low latency, and ready‐to‐use infrastructure of next generation wireless (NGW) networks provide a platform for machine‐to‐machine (M2M) communications on a large scale. However, M2M communications over NGW networks pose significant challenges because of different data rates, diverse applications, and a large number of connections. In this paper, we address M2M challenges over NGW networks, and in particular, we focus on random access overload issue and diverse quality‐of‐service (QoS) requirements to enable M2M communications in the context of NGW networks. To enable massive M2M access while QoS guarantees, we propose group‐based M2M communications on the basis of identical transmission protocols and QoS requirements. Furthermore, to guarantee low energy consumption for M2M devices in the same group, we propose a decentralized group‐head selection scheme. In addition, a solution is proposed by using an effective capacity concept to provide QoS guarantees for M2M devices with a strict time constraint. A new random access approach based on different lengths super orthogonal codes is proposed to ease massive random access challenges with provisioning diverse QoS requirements of M2M communications in heterogeneous NGW networks.     

改进的多信道S-ALOHA暂态性能分析办法及其应用

海量机器类终端(或MTC终端)同步入网时,其业务呈现瞬时突发性,这使得基于齐次或复合泊松假设的多信道S-ALOHA稳态性能分析办法难以直接应用。该文以第i个随机接入时隙内第j次进行随机接入的用户数Mi(j)作为状态变量,提出了一种沿Mi(j) 的j方向迭代进行多信道S-ALOHA暂态性能分析的办法及其近似形式。该迭代办法可建立第i个随机接入时隙内第j次进行随机接入的用户数与第x个随机接入时隙内新到用户数的直接关系(其中xi),也可给出接入时延概率密度函数、概率分布函数和均值的求解办法。以3GPP MTC业务参考模型进行数值仿真,验证了所提迭代办法及其近似形式的有效性。相关研究可为承载网络的优化设计提供参考。     

面向mMIMO系统的模式分割随机接入方案

为提升海量机器类通信（massive machine-type communication,m MTC）设备的随机接入（random access,RA）性能,提出一种面向大规模多输入多输出（massive multiple-input multiple-output,m MIMO）系统的模式分割随机接入（pattern division random access,PDRA）方案。该方案将导频竞争空间扩展到模式域,通过叠加同一ZC(Zadoff-Chu）根序列的L个不同循环移位序列,设计基于“图样叠加”的模式域导频,在不增加物理资源的前提下扩大导频集合。仿真结果表明,在不影响信道估计和数据检测性能的前提下,与传统RA方案相比,PDRA方案能够显著降低导频碰撞概率,提高接入成功率。     

MTC组寻呼基于提前退避接入策略研究

组寻呼方案有效的解决了大量机器类型通信（MTC,Machine—typeCommunications）设备同时接入LTE无线网络的拥塞问题。主要对MTC组寻呼基于提前退避的随机接入策略进行深入研究,通过对组寻呼基于提前退避策略进行理论建模,得到其性能分析表达式。数值分析结果表明,基于提前退避的随机接入策略比基于传统的随机接入策略更能提高组寻呼的接入性能。     

Performance analysis and enhancement of random access process in cellular-IoT

Narrowband Internet of things (NB-IoT) and enhanced machine-type communications (eMTC) are two new IoT-oriented solutions introduced by the 3rd generation partnership project (3GPP) in Rel-13. In order to meet the new requirements (such as long battery life, low device cost, low deployment cost, extended coverage and support for a massive number of devices) of machine-to-machine (M2M) communication, these two technologies had some improvements on the random access (RA) mechanism compared to traditional long term evolution (LTE). For example, repetition of preamble transmission and coverage enhancement (CE) levels have been proposed to offer communication services in a wider area. In addition, NB-IoT has adopted a new spectrum allocation method and proposed a new type of preamble structure to meet the requirement of big amount of connections. We summarize details and differences of the RA process in LTE, eMTC and NB-IoT. Afterwards, as an improvement, we propose an enhanced access protocol for NB-IoT. Finally, performance analysis and comparison are presented in terms of access success probability, average access delay, access spectrum efficiency and average number of RA attempts.     

机器类设备基于不同时延需求分组的随机接入方法

针对大规模机器类通信中拥塞导致的时延敏感设备时延高和接入成功率低的问题，提出将小区中设备按时延要求分组，对不同组设备引入不同的退避模型，分析时延敏感设备的时延和吞吐量，按照不同组中设备的时延需求动态分配前导数目，同时通过调整接入类限制因子实现吞吐量的优化。仿真结果表明，在给定时延敏感设备的时延限制条件时，与统一退避的机制对比，所提分组机制的时延敏感设备能够满足时延要求，并且提高了接入效率。     

LPPA: Lightweight privacy‐preservation access authentication scheme for massive devices in fifth Generation (5G) cellular networks

Because of the requirements of stringent latency, high‐connection density, and massive devices concurrent connection, the design of the security and efficient access authentication for massive devices is the key point to guarantee the application security under the future fifth Generation (5G) systems. The current access authentication mechanism proposed by 3rd Generation Partnership Project (3GPP) requires each device to execute the full access authentication process, which can not only incur a lot of protocol attacks but also result in signaling congestion on key nodes in 5G core networks when sea of devices concurrently request to access into the networks. In this paper, we design an efficient and secure privacy‐preservation access authentication scheme for massive devices in 5G wireless networks based on aggregation message authentication code (AMAC) technique. Our proposed scheme can accomplish the access authentication between massive devices and the network at the same time negotiate a distinct secret key between each device and the network. In addition, our proposed scheme can withstand a lot of protocol attacks including interior forgery attacks and DoS attacks and achieve identity privacy protection and group member update without sacrificing the efficiency. The Burrows Abadi Needham (BAN) logic and the formal verification tool: Automated Validation of Internet Security Protocols and Applications (AVISPA) and Security Protocol ANimator for AVISPA (SPAN) are employed to demonstrate the security of our proposed scheme.     

5G URLLC无线网络部署方案分析

URLLC场景是5G的典型应用场景之一,也是体现5G技术先进性的重要场景。随着URLLC增强技术标准化工作的完成,运营商需要明确5G URLLC网络下承载的典型业务,推动URLLC无线网络的部署。根据3GPP对不同业务网络指标需求的分析,结合ITU对URLLC场景时延与可靠性指标的要求,分析URLLC场景下潜在的应用,探讨了5G URLLC无线网络的部署方案。     

Optimal resource allocation for two-stage connectionless access with collision detection

Connectionless access allows massive machine type communication (mMTC) devices to transmit small packets without establishment of radio bearers,significantly reducing device power consumption and control signaling overhead.Two-stage connectionless access (TSCLA) improves throughput and resource efficiency by optimally allocating resources between scheduling request (SR) phase and data transmission phase,which can be used for bigger packets and high traffic load.Based on this,a comprehensive theoretical analysis of one kind of TSCLA with collision detection was conducted to investigate its performance limit and devise its optimal resource allocation scheme.In addition,to avoid the complexity of user number estimation,a dynamic resource allocation algorithm with feedback control was proposed.Numerical results are provided to validate the effectiveness of aforementioned theoretical results and show that comparing with the genie aided algorithm known exactly the number of users,the performance loss of the proposed algorithm is within 4%.These works together provide good references for appropriate resource dimensioning for mMTC related protocols.     

机器类通信中集中式与分布式Q学习的资源分配算法研究

针对海量机器类通信（massive machine type communication,mMTC）场景,以最大化系统吞吐量为目标,且在保证部分机器类通信设备（machine type communication device,MTCD）的服务质量（quality of service,QoS）要求前提下,提出两种基于Q学习的资源分配算法：集中式Q学习算法（team-Q）和分布式Q学习算法（dis-Q）。首先基于余弦相似度（cosine similarity,CS）聚类算法,考虑到MTCD地理位置和多级别QoS要求,构造代表MTCD和数据聚合器（data aggregator,DA）的多维向量,根据向量间CS值完成分组。然后分别利用team-Q学习算法和dis-Q学习算法为MTCD分配资源块（resource block,RB）和功率。吞吐量性能上,team-Q 和 dis-Q 算法相较于动态资源分配算法、贪婪算法分别平均提高了 16%、23%;复杂度性能上,dis-Q算法仅为team-Q算法的25%及以下,收敛速度则提高了近40%。     

面向电网业务质量保障的5G高可靠低时延通信资源调度方法

该文研究面向电网业务质量保障的5G 高可靠低时延通信(URLLC)的资源调度机制,以高效利用低频段蜂窝通信系统内有限的频谱和功率资源来兼顾电力终端传输速率和调度时延、调度公平性,保障不同电力业务的通信质量（QoS）。首先,基于URLLC的高可靠低时延传输特性,建立电力终端多小区下行传输模型。然后,提出面向系统下行吞吐量最大化的资源分配问题模型并对其进行分步求解,分别提出基于定价机制与非合作博弈的功率分配算法和基于调度时延要求的改进比例公平算法（DPF）动态调度信道资源。仿真结果表明,提出的资源调度方法能在保证一定传输可靠性和公平性的条件下降低电力终端调度时延,满足不同业务等级的QoS需求,与已知算法对比有一定的优越性。     

免调度非正交多址接入上行链路的非2幂次长度二元扩频序列

为了解决5G大规模机器类通信场景下大规模接入和如何提高频谱效率的问题,该文针对免调度非正交多址接入(NOMA)系统上行链路,通过采用插入函数在2元Golay序列上插入元素的方法,提出具有低峰均功率比(PAPR)且长度为非2幂次的2元扩频序列集.仿真结果表明,得到的序列集具有低相干性,这为基于压缩感知的活跃用户检测提供了...     

车联网极低时延与高可靠通信:现状与展望

随着第五代移动通信技术的不断发展,智能交通系统的建设已成为智慧城市建设进程中非常重要的环节,车联网又是智能交通系统中必不可少的组成部分。目前全球汽车使用量急剧上升,为提升人们出行体验,实现车、路、人以及基础设施之间的信息交互,需要一个具备高速大带宽以及高可靠低时延的通信（Ultra-Reliable Low-Latency Communication ,URLLC）网络支撑。而目前基于LTE技术的车联网不能满足URLLC的性能需求,因此提升车联网URLLC的性能成为车联网技术研究的重点。本论文回顾了车联网技术标准的发展历程,对URLLC在车联网应用场景的性能需求进行分析,并对提升车联网高可靠性和极低时延的研究方法进行总结。