Communications Signal Processing Based Solutions for Massive Machine-to-Machine Networks (M3NETs)

基于通信信号处理的大规模机器对机器网络 (M3NET) 解决方案

• 批准号: EP/R006377/1
• 负责人: Jonathon Chambers
• 金额: $ 35.11万
• 依托单位: University of Leicester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR006377%2F1
• 关键词: Communications; Signal; Processing; Based; Solutions

Future wireless networks should have the capability of serving a wide range of personal wireless devices and appliances with stringent end-to-end delay requirements. These appliances will be equipped with the capabilities to sense various real time events and be able to self-configure via network connections, thereby paving the way for many emerging applications including e-health, intelligent transportation and smart cities. The most important enabling technologies for these applications is seamless machine-to-machine (M2M) wireless communications, which is the key to sustaining large-scale massive interconnections between things. The number of M2M devices has been growing exponentially, and is expected to reach up to 50 billion by 2020. This trend in the market growth for both M2M devices and M2M connectivity segments will further accelerate in the future. Along with it, by 2020, M2M connections will generate 6.7 percent of total mobile traffic-up from 2.7 percent in 2015. As such, M2M communications is envisioned as one of the five disruptive technology directions for fifth generation (5G) wireless networks and beyond.Despite the importance of machine-type communications, there are many critical challenges that need to be addressed in terms of network congestion and overload due to presence of massive M2M devices with heterogeneous traffic patterns, unprecedented level of inter and intra interference among M2M and human-to-human (H2M) communications, complex resource management due to irregular traffic patterns and energy constraints. The focus of this project is on tackling these critical challenges, by advancing aspects of communications signal processing, stochastic geometry, convex optimizations and game theory. In particular, we will contribute in terms of characterising heterogeneous traffic patterns associated with massive M2M communications, development of distributed random access channel protocols, proposal of convex and game theoretic resource allocation methods and design of energy harvesting constraint based cross-layer optimisation algorithms and protocols. All the concepts and algorithms developed will be integrated and the radio link layer performance will be assessed using a simulation reference system based on LTE-Advanced standards and its evolution towards 5G. Industrial partners will be engaged throughout the project to ensure industrial relevance of our work.

未来的无线网络应该具有服务于具有严格的端到端延迟要求的广泛的个人无线设备和电器的能力。这些设备将具备感知各种真实的时间事件的能力，并能够通过网络连接进行自我配置，从而为电子健康、智能交通和智能城市等许多新兴应用铺平道路。这些应用最重要的支持技术是无缝机器对机器（M2M）无线通信，这是维持事物之间大规模互连的关键。M2M设备的数量呈指数级增长，预计到2020年将达到500亿台。M2M设备和M2M连接领域的市场增长趋势将在未来进一步加速。沿着，到2020年，M2M连接将占总移动的流量的6.7%，高于2015年的2.7%。因此，M2M通信被设想为第五代（5G）无线网络及以后的五个颠覆性技术方向之一。尽管机器类型通信很重要，但由于存在具有异构业务模式的大量M2M设备，在网络拥塞和过载方面存在许多需要解决的关键挑战。M2M和人对人（H2 M）通信之间前所未有的内部和内部干扰水平，由于不规则的业务模式和能量约束而导致的复杂资源管理。该项目的重点是通过推进通信信号处理，随机几何，凸优化和博弈论等方面来应对这些关键挑战。特别是，我们将有助于与大规模M2M通信，分布式随机接入信道协议的发展，凸和博弈论资源分配方法的建议和设计的能量收集约束为基础的跨层优化算法和协议的异构流量模式的特征。所有开发的概念和算法将被集成，无线链路层性能将使用基于LTE-Advanced标准及其向5G演进的模拟参考系统进行评估。工业合作伙伴将参与整个项目，以确保我们的工作的工业相关性。

项目成果

Efficient Low-Complexity Antenna Selection Algorithms in Multi-User Massive MIMO Systems With Matched Filter Precoding

• DOI: 10.1109/tvt.2020.2966565
• 发表时间: 2020-01
• 期刊: IEEE Transactions on Vehicular Technology
• 影响因子: 6.8
• 作者: Zaid Abdullah;C. Tsimenidis;Gaojie Chen;M. Johnston;J. Chambers

A Cooperative Jamming Scheme for Physical Layer Security enhancement in Multihop IoT Networks with Colluding Eavesdroppers

• DOI: 10.1109/ssp49050.2021.9513798
• 发表时间: 2021-07
• 期刊: 2021 IEEE Statistical Signal Processing Workshop (SSP)
• 作者: Zaid Abdullah;Gaojie Chen;J. Chambers

Performance Analysis of Cognitive Clustered Machine-to-Machine Networks with Device Selection

• DOI: 10.1109/glocomw.2018.8644158
• 发表时间: 2018-12
• 期刊: 2018 IEEE Globecom Workshops (GC Wkshps)
• 作者: Mohammed A. M. Abdullah;Gaojie Chen;Mahmoud Alageli;A. Ikhlef;J. Chambers

Cell-Edge-Aware Antenna Selection and Power Allocation in Massive MIMO Systems

大规模 MIMO 系统中的小区边缘感知天线选择和功率分配

• 发表时间: 2019
• 作者: Abdullah Z

Performance Analysis of Cognitive Clustered M2M Random Networks With Joint User and Machine Device Selection

• DOI: 10.1109/access.2019.2924522
• 发表时间: 2019-06
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Mohammed A. M. Abdullah;Zaid Abdullah;Gaojie Chen;Jie Tang;J. Chambers