融入M2M业务的LTE-A无线网络随机接入优化分析

随着机器通信(MTC)的快速发展及增长,大量MTC设备同时接入网络会造成无线接入网络的过载问题.为了解决这一问题,3GPP已经在LTE-A网络中提出了一些解决因大量MTC同时涌入而造成的无线网拥塞问题的候选方案.本文通过对这些解决方案进行分析与研究,并在此基础上对融入机器对机器(M2M)业务的LTE-A无线网络侧的随机接入提出优化方案.     

LTE-A无线接入网随机接入优化分析

移动通信产业即将走进LTE-A时代的今天,随着物物(M2M)通信业务的快速发展,M2M业务融入到LTE-A移动通信网络已成为了必然的发展趋势。然而,大量MTC设备同时接入网络又会造成无线接入网络的过载问题,从而影响了人与人(H2H)之间的正常通信。为了解决这一问题,3GPP提出了解决因大量机器通信(MTC)设备同时涌入而造成的无线网拥塞问题的候选方案。本文通过对这些解决方案进行分析与研究,并在此基础上对融入M2M业务的LTE-A无线网络侧的随机接入提出优化方案。     

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.     

H2H与M2M共存场景下的上行资源分配算法

未来网络中将有大量的机器与机器（machine-to-machine,M2M）通信终端,比人与人（human to human,H2H）通信终端至少要多出2个数量级,网络中传统的资源分配算法无法满足新业务的通信需求.基于H2H与M2M共存场景,本文通过分析M2M终端特性,提出了一种基于背包模型的分级传输的资源分配算法,此分配算法优先保障H2H与时延敏感的M2M通信业务的服务质量（Quality of Service,QoS）,同时充分考虑时延非敏感的M2M的业务特性,节省能量消耗.仿真结果表明该算法能够提高资源利用率,同时满足H2H与M2M业务的QoS.     

机器类通信中基于NOMA短编码块传输的高可靠低迟延无线资源分配优化方案

针对机器类通信(MTC)应用场景的业务特征和服务质量(QoS)要求,该文考虑基于非正交多址(NOMA)的MTC中短分组/短编码块传输,探讨MTC中基于NOMA的高可靠低迟延无线资源优化问题。首先,上行传输是基于NOMA的MTC通信的瓶颈,考虑无线蜂窝网络中支持NOMA和高可靠低迟延性能要求,该文建立了上行无线资源优化的系统模型;然后,分析上行传输迟延,导出基于距离的链路可靠性函数;进一步,以迟延、可靠性和带宽为约束下条件,提出一种最大化中心用户和速率的无线资源分配算法,并给出算法的收敛性证明和复杂度分析;最后,实验仿真验证了所提算法的性能优势。     

一种固定位置MTC设备的随机接入改进算法

针对海量机器类通信(Massive Machine Type Communications, mMTC)场景下传统随机接入存在大量前导碰撞问题，提出了一种对终端侧和基站侧的接入改进算法，利用前导标记序列和固定位置随机接入终端的定时提前(Timing Advance, TA)信息，使得基站能合理地确定应该向哪些终端回复随机接入响应消息，避免碰撞终端占用资源发送消息3(Message 3,Msg3),实现前导高效利用。仿真表明，该算法在均匀分布和Beta分布接入模型下均能有效降低前导碰撞概率，提高终端的接入成功率，并且拥有合理的平均接入时延。     

LTE-Advanced机器型通信空中接口研究

随着机器型通信(MTC)设备的广泛部署和使用,MTC已经和移动通信网络紧密结合,MTC设备数目的大量增加使得对于通信系统各项技术的要求也变得更为严格.分析了MTC的特点及国内外发展趋势,讨论了LTE-Advanced网络MTC的接入网过载控制、资源分配、节能方案的技术问题,介绍了LTE-Advanced 网络MTC的典型优化方法,针对MTC在R12及以后版本中的可扩展性问题及其发展目标提出了技术改进方案.     

基于M2M终端组的比例公平资源分配研究

基于M2M终端组的资源分配策略可以有效提高M2M通信中的资源利用率.本文研究了M2M通信系统中基于组的保证不同组间传输速率的比例公平资源分配问题,提出了一种次优的能够保证不同终端组间传输速率比例公平的资源分配算法,并通过仿真对算法的性能进行了验证,给出了速率最大化算法与终端组比例公平算法的性能比较.     

一种自适应调整前导的随机接入控制机制

无线通信技术的迅速发展,为机器对机器(machine-to-machine,M2M)间通信的发展提供了良好的环境基础,极大拓展了M2M通信业务的应用范围。但在LTE-A系统中,当大量终端同时地发起随机接入则必然引起接入网络拥塞问题。为缓解接入拥塞,文章提出了一种基于负载估计的接入控制方法,首先参考快速重传的多通道ALOHA协议,建立基于竞争的随机接入信道模型,接着利用最大似然估计衡量时隙接入负载,最后自适应接入时隙的前导资源池大小。仿真结果表明,该方法能够有效降低前导碰撞概率,提高接入成功率,也能一定程度上减少前导重传次数,降低接入时延。     

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。     

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。     

Localization in terrestrial and underwater sensor‐based m2m communication networks: architecture,classification and challenges

Localizing machine‐type communication (MTC) devices or sensors is becoming important because of the increasing popularity of machine‐to‐machine (M2M) communication networks for location‐based applications. These include such as health monitoring, rescue operations, vehicle tracking, and wildfire monitoring. Moreover, efficient localization approaches for sensor‐based MTC devices reduce the localization error and energy consumption of MTC devices. Because sensors are used as an integral part of M2M communication networks and have achieved popularity in underwater applications, research is being conducted on sensor localization in both underwater and terrestrial M2M networks. Major challenges in designing underwater localization techniques are the lack of good radio signal propagation in underwater, sensor mobility management, and ensuring network coverage in 3D underwater M2M networks. Similarly, predicting the mobility pattern of MTC devices, trading‐off energy consumption and location accuracy pose great design challenges for terrestrial localization techniques. This article presents a comprehensive survey on the current state‐of‐the‐art research on both terrestrial and underwater localization approaches for sensor‐based MTC devices. It also classifies localization approaches based on several factors, identifies their limitations with potential solutions, and compares them. Copyright © 2015 John Wiley & Sons, Ltd.     

Overload control in the network domain of LTE/LTE-A based machine type communications

It is expected that the LTE network, which includes the Radio Access Network (RAN) and the Core Network (CN) in 3GPP LTE systems, will be overloaded due to the huge number of Machine-Type Communication (MTC) devices in the near future. Overload in the RAN and CN of the LTE may result in congestion occurrence, resource waste, Quality of Service (QoS) degradation and in the worst-case, it will cause service unavailability. In this paper, we have proposed an adaptive mechanism to manage a large number of MTC devices in both RAN and CN of the LTE network. We use Access Class Barring (ACB) scheme to regulate the MTC traffic according to the congestions level in the RAN and CN. We consider a scenario in which two-priority-based classes of MTC devices are contending for the RAN resources. At first, the overload problem in the RAN is formulated to find the number of allowable contending MTC devices of each class taking into account their required QoS. Then, an active load management policy based on additive increase multiplicative decrease rule is proposed to control the incoming load from multiple cells to the CN. To effectively limit the number of MTC devices in both RAN and CN, in the proposed approach, each Evolved Node B updates the ACB factor upon overload detection in the RAN or CN in an adaptive manner. Simulation results show that the proposed mechanism is able to manage overload in the CN and RAN simultaneously.     

Timed strategic machine type communications for dual-level future wireless networks

For the next generation wireless networks, machine type communication (MTC) is gaining an enormous interest as a new communication paradigm. MTC is expected to become a cost-effective solution for improving the wireless communication performance. In MTC, one of the most critical issues is to support data transfers among devices without human interaction. In this study, we introduce a new MTC control scheme for the future network infrastructure. To effectively support a large number of MTC devices, we investigate a dual-level interaction mechanism by employing the timed strategy game model. In dynamic wireless network environments, our timed strategic game approach can practically adapt current system conditions while maximizing system performance. Main contribution of this research is to show a way of MTC system modeling based on the competitive and cooperative manner. Finally, numerical simulations illustrate the validity of our game-based approach. Our solution enables a better network resource utilization for heterogeneous traffic services in contrast to existing schemes.

     

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。     

Performance evaluation of a priority‐based resource allocation scheme for multiclass services in IoT

Recently, the deployment of novel smart network concepts, such as the Internet of things (IoT) or machine‐to‐machine communication, has gained more attention owing to its role in providing communication among various smart devices. The IoT involves a set of IoT devices (IoTDs) such as actuators and sensors that communicate with IoT applications via IoT gateways without human intervention. The IoTDs have different traffic types with various delay requirements, and we can classify them into two main groups: critical and massive IoTDs. The fundamental promising technology in the IoT is the advanced long‐term evolution (LTE‐A). In the future, the number of IoTDs attempting to access an LTE‐A network in a short period will increase rapidly and, thus, significantly reduce the performance of the LTE‐A network and affect the QoS required by variant IoT traffic. Therefore, efficient resource allocation is required. In this paper, we propose a priority‐based allocation scheme for multiclass service in IoT to efficiently share resources between critical and massive IoTD traffic based on their specific characteristics while protecting the critical IoTDs, which have a higher priority over the massive IoTDs. The performance of the proposed scheme is analyzed using the Geo/G/1 queuing system focusing on QoS guarantees and resource utilization of both critical and massive IoTDs. The distribution of service time of the proposed system is determined and, thus, the average waiting and service times are derived. The results indicate that the performance of the massive IoTDs depends on the data traffic characteristics of the critical IoTDs. Furthermore, the results emphasize the importance of the system delay analysis and demonstrate its effects on IoT configurations.     

Physical layer architectures for machine type communication networks—a survey

Machine‐type communication (MTC) has attracted much attention due to the fact that it provides pervasive connections for billions of MTC devices, forming a basis for the Internet of things. Most works in the literatures on machine‐to‐machine (M2M) communications focused on media access layer (MAC) layer or other upper layer applications, such as e‐health, energy management and entertainment services. On the other hand, physical (PHY) layer plays a pivotal role in M2M communications. To accommodate a large number of MTC devices, M2M should be made efficient enough in terms of its power consumption and spectrum utilisation. Copyright © 2016 John Wiley & Sons, Ltd.     

Dynamic Resource Allocation of Random Access for MTC Devices

In a long term evolution‐advanced (LTE‐A) system, the traffic overload of machine type communication devices is a challenge because too many devices attempt to access a base station (BS) simultaneously in a short period of time. We discuss the challenge of the gap between the theoretical maximum throughput and the actual throughput. A gap occurs when the BS cannot change the number of preambles for a random access channel (RACH) until multiple numbers of RACHs are completed. In addition, a preamble partition approach is proposed in this paper that uses two groups of preambles to reduce this gap. A performance evaluation shows that the proposed approach increases the average throughput. For 100,000 devices in a cell, the throughput is increased by 29.7% to 114.4% and 23.0% to 91.3% with uniform and Beta‐distributed arrivals of devices, respectively.     

Random access scheme for different MTC scenario requirement

For the different random access requirements of the mixed scenarios of ultra-reliable low latency (URLLC) and massive machine type communications (mMTC) in MTC,a random access scheme based on devices grouping was proposed.The proposed scheme divided the MTC devices into several groups based on the timing advance (TA) information:for the URLLC scenario,preamble resources were reserved for core devices in each group,and the URLLC devices accessed the network via the contention-free mechanism,to satisfy the ultra-reliable low latency access requirement; for the mMTC scenario,the base station utilized the different TA information in different group to identify devices selecting the same preamble,and performed successive interference cancellation (SIC) algorithm to detect the data information,to satisfy the massive access requirement.Simulation results demonstrate that the proposed scheme can significantly increase the number of the successful devices.