大规模M2M通信：LTE-A上行链路资源分配新策略

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"用于LTE-A上的大规模M2M通信的基于分组的上行链路资源分配" 在现代无线通信系统中，随着物联网（IoT）的快速发展，机器类型通信（Machine-Type Communication, MTC）设备，如传感器和执行器，的数量急剧增长。这种增长在LTE-Advanced（LTE-A）网络中表现为大规模M2M（Machine-to-Machine）通信，对网络提出了新的挑战。在这样的环境中，大量的MTC设备同时尝试接入网络，可能导致随机接入（Random Access, RA）和上行链路调度过程中的严重信令拥塞和流量拥堵。传统的RA机制可能无法有效处理大规模M2M通信的接入需求，因为它可能导致大量设备在同一时间请求接入，从而造成冲突和延迟。为了解决这个问题，本文提出了一种创新的基于分组的RA和上行链路调度策略。该策略的核心思想是将MTC设备组织成若干个小组，每个小组由一个组长代表，组长负责发起RA过程并申请上行链路传输资源。这种方法可以显著降低网络中的竞争压力，提高接入效率。具体来说，文章提出了一种第二组寻呼方案，以优化RA过程。这个方案通过更精细的时间划分和优化的寻呼策略，进一步减少了设备的接入延迟，提高了设备的接入概率。此外，通过合理分配资源，该方法还提升了系统的公平性，确保各个设备有均等的机会进行数据传输。文章详细描述了在实际的LTE-A系统中实现这一策略的技术细节，包括组的形成、组长选举、资源分配算法以及第二组寻呼的实现。通过仿真对比，研究证实了所提方案相比于传统的RA和调度方法，在以下几个关键性能指标上表现出优越性： 1. 接入概率：基于分组的策略提高了设备成功接入网络的概率，降低了因冲突导致的失败率。 2. 接入时延：通过优化的组寻呼，设备的平均接入等待时间显著缩短，提升了服务响应速度。 3. 冲突概率：通过减少同时请求接入的设备数量，有效降低了数据包的碰撞概率。 4. 公平性：资源分配策略确保了各设备之间的公平竞争，避免了部分设备长时间无法获得传输机会的情况。这项工作为解决大规模M2M通信在LTE-A网络中的接入和调度问题提供了一种有效的解决方案，对于未来5G及更高级别的物联网通信系统具有重要的参考价值。它不仅有助于缓解网络拥堵，提高服务质量，还能为其他类似场景的资源管理提供启示。

Grouping Based Uplink Resource Allocation for

Massive M2M Communications over LTE-A

Shaoyi Xu

, Junlong Li

, and Xintao Qin

Member, IEEE

School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, 10044, China

Huawei Technologies Co., Ltd., Beijing, China

E-mail: shyxu@bjtu.edu.cn, lijunlong@huawei.com, and 12120130@bjtu.edu.cn

Abstract—Deployment of massive machine type

communication devices (MTCDs) in the LTE-A network may

incur signaling and traffic congestion during the random access

(RA) and uplink scheduling. To overcome these problems, a

grouping based RA and uplink scheduling scheme is proposed in

this paper. The group leader will initiate RA and apply for the

uplink transmission resources on behalf of the group members.

Specifically, a second group paging scheme is designed to further

reduce the access delay and increase the access probability.

Implementation details are described in a practical LTE-A system

and simulations prove that our proposed approach outperforms

the traditional methods with respect to the access probability,

access time delay, collision probability and fairness.

Keywords—machine-to-machine (M2M); Machine Type

Communication Devices (MTCDs); Random Access (RA); Uplink

Scheduling; Signaling Congestion.

NTRODUCTION

To support the so called “Internet of Things” and motivated

by the growing demands of machine-to-machine (M2M)

applications, it is expected that M2M devices will increase

greatly in the near future. An Ericsson report suggests that the

number of M2M devices by 2020 will be around 50 billion for

a projected population of around 8 billion at that time [1]. As a

result, many standardization bodies have been standardizing the

network architecture. In this sense, 3GPP has defined a new

device class category 0 for low-cost machine type

communication devices (MTCDs) and service provision aiming

to support the massive number of MTCDs connected to the

network [2]. It is also considered to be one of the main drivers

for the future 5G communication. Thus, 3GPP has raised the

need to revisit the design of LTE-A network to enable efficient

M2M communication.

It is known to all that there are two bottlenecks in M2M

communications. The first one is preamble collisions on

physical random access channel (PRACH) during random

access. When more than one MTCDs select the same preamble

on the same PRACH, the collision happens. The other is the

limited physical uplink shared channel (PUSCH) and physical

downlink control channel (PDCCH) resource that will be

insufficient when massive MTCDs apply for resources in the

uplink (UL) transmission. During the entire transmission

procedure, such massive deployments may generate an

enormous volume of signaling and traffic considering the fact

that a large number of MTCDs almost simultaneously try to

attach to the network and send data to the eNB.

To overcome these two problems, some solutions have been

proposed. For massive RA, there have been several studies to

tackle the preamble collisions. In the early study, based on the

access class barring (ACB), lots of schemes are developed to

enhance or improve it. The authors in [3] proposed a dynamic

ACB which enables the MTCDs to select an eNB for RA among

multiple eNBs for overload balance. In [4], a scheme is

proposed to provide more preambles by spatially partitioning

the cell coverage into multiple group regions and reducing the

cyclic shift size in RA preambles. To further study the RA delay

and improve RA performance, [5] evaluated the RA delay from

the mathematical perspective and proposed to reduce such delay

by configuring appropriate system parameters. Other

approaches include only allowing the MTCDs to perform RA

which have obtained enough power by harvesting energy [6] or

higher priorities [7]. For avoiding possible uplink signaling

storm and to minimize the energy consumption, the lifetime-

aware scheduling scheme is developed in [8]. For the scenario

that M2M devices coexist with human-to-human user

equipment (UE), [9] puts forward a downlink resource

allocation mechanism for packet downlink control channels

considering the impact of MTCDs on QoS provisioning.

The above work mainly focuses on to decrease the number

of MTCDs which are allowed to access the network

simultaneously. Different from the previous work, based on the

grouping massive MTCDs, a RA and following UL resource

scheduling mechanism is devised in this paper. During the

procedure, the group leader may initiate the RA procedure on

behalf of its group members and send related signaling.

Especially, a second group paging mechanism is developed to

further reduce the access delay and increase the access

probability. For the eNB, by using the group ID to mask the

corresponding signaling, it may send only one control signal

instead of massive information on the control channels such that

a possible signaling congestion is avoided effectively.

Simulation results confirm that the better effectiveness of the

proposed schemes can be obtained by comparing with the

traditional RA methods and scheduling mechanisms with

respect to access probability, access time delay, collision

probability and fairness.

The remainder of this paper is organized as follows. Section

II describes the system model. Section III elaborates the

proposed grouping based RA and UL scheduling mechanism.

Simulation results are presented in Section IV, followed by

conclusions in Section V.

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