Self-Coupling Random-Access Communications

即将到来的无线通信应用中有很大一部分致力于物联网（IoT）和机器对机器（M2M）通信。未来的物体，如智能家居、智能汽车、机器人和自动机的部分，将在不需要人工干预的情况下交换信息，并将共同执行各种任务。这种M2M和IoT通信场景期望高密度的通信设备按需发送短消息，不需要协调和预留时间和带宽资源。节能、高可靠性和低延迟是许多此类应用（包括远程控制和虚拟现实）所要求的优先特性列表。当前的多址通信技术是一种多个发射机同时共享通信媒体的场景，不适合大量设备在没有协调、按需、随机时间、存在信道损伤和移动性的情况下访问信道。该计划和未来研究的目标是为5G系统之外的大规模异步随机访问开发一种数据通信格式，为M2M和物联网通信基础设施提供基础。在数据包、发射器和接收器的设计方面，系统需要满足低延迟高可靠性的要求，在具有移动性和能量限制的毫米波信道中运行，能够有效地利用大量多天线接收器，并在复杂性和吞吐量方面达到最佳。研究方法包括使用空间图耦合技术，其中每个消息表示为连接数据位和时间/频率通信资源的图。这些图在接收端耦合成一个图链，从而实现高效的数据提取。为了实现随机访问，我们建议使用自耦合结构，其中每个数据包由一个迷你耦合链表示。当接收到时，即使在随机时间，单个数据包的链也会在接收端耦合成单个图链。用于数据解码和干扰消除的消息传递算法可以提供一种在可实现吞吐量意义上接近最佳性能的方法。该格式允许包含迭代包获取和信道均衡。对该领域的预期贡献是一种可以在多种设备中实现并可能标准化的通信格式。我们的目标是基于最优性的理论原理，在严格的分析框架和空间耦合、压缩感知、机器学习和信道跟踪等新颖的突破性技术的支持下进行系统设计。预计此次开发的技术将为未来的无线设备连接奠定基础，并对加拿大经济产生重大影响，因为5G、物联网（IoT）、M2M将成为信息技术（it）领域未来业务发展的工具。

A large share of upcoming wireless communication applications is dedicated to the Internet of Things (IoT) and Machine-to-Machine (M2M) communications. Objects of the future, such as parts of smart homes, smart vehicles, robots and automata, will exchange information without any need for human intervention and will perform various tasks jointly. Such M2M and IoT communication scenarios anticipate high density of communicating devices that send short messages on demand, without coordination and reservation of time and bandwidth resources. Energy saving, high reliability, and low latency are on the priority list of features demanded by many such applications including remote control and virtual reality. Current techniques for multiple-access communications, a scenario when a number of transmitters share communication media simultaneously, are not suitable for a massive number of devices accessing the channel without coordination, on demand, at random times, in presence of channel impairments and mobility. The goal of the proposed program and future research is to develop a data communication format for massive asynchronous random-access beyond 5G systems providing a base for M2M and IoT communications infrastructure. In terms of data packets, transmitter, and receiver design, the system needs to satisfy low-latency high-reliability requirements, operate in mmWave channel with mobility and energy constraints, be able to efficiently utilize massive multiple antenna receivers, and be optimal in terms of complexity and throughput. The research methodology includes use of spatial graph coupling techniques, where each message is represented as a graph that connects data bits and time/frequency communication resources. The graphs couple at the receiver into a graph chain that allows for efficient data extraction. To enable random access, we propose to use a self-coupling structure where each packet is represented by a mini coupled chain. When received, even at random times, the chains of individual packets couple into a single graph chain at the receiver. Message-passing algorithms for data decoding and interference cancellation can provide a way to approach optimal performance in the sense of the achievable throughput. The format enables for inclusion of iterative packet acquisition and channel equalization. The expected contribution to the field is a communication format that can be implemented in a multitude of devices and potentially standardized. We target a systematic design based on theoretic principles of optimality, supported by rigorous analysis framework and novel breakthrough techniques of spatial coupling, compressed sensing, machine learning, and channel tracking. The developed technology is expected to lay a pathway to future wireless device connectivity and have a significant impact on the Canadian economy as 5G, IoT, and M2M will serve as a vehicle for the future development of business in the information technology sector.