Combined Massive MIMO and Interference Alignment for Future Wireless Networks Involving Machine Type Communications

针对涉及机器类型通信的未来无线网络的大规模 MIMO 和干扰对齐相结合

• 批准号: RGPIN-2020-07005
• 负责人: Ikki, Salama
• 金额: $ 2.4万
• 依托单位: Lakehead University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741540
• 关键词: Combined; Massive; MIMO; Interference; Alignment

Machine Type Communications (MTC), such as the Internet of Things (IoT), device-to-device, Machine-to-Machine and wireless sensor nodes, have been recently introduced as groundbreaking concepts in the field of wireless communications, offering communication between devices and everyday objects.  It has been widely accepted that cellular networks play an essential part in providing such a wide range of connected machines and their related services in attaining the IoT. The Cisco Visual Networking Index report projects that 100 billion physical objects will be connected to the cloud by 2025. To maintain high Quality-of-Service (QoS),  and to address the ever-increasing demand of data rate, one of the essential objectives of researchers in both industry and academia is to significantly improve the spectral and energy efficiencies for future wireless networks. There are three primary ways of adding capacity to wireless systems: a) moving into a new spectrum (mm wave), 2) making that spectrum more efficient, and 3) densifying the network. To accommodate an immense number of devices, the nodes must be extremely energy efficient. Large-scale antenna systems (i.e. Massive MIMO) pave the way towards improving both spectral and energy efficiency. In small-sized cells, extra antennas at the base stations diminish intra-cell interference among users served in the same frequency-time-code resource by concentrating the energy into fewer areas of space. One of the limitations in the spectral efficiency of heterogeneous networks is the interference management and limited radio resources. It is known that Interference Alignment (IA) is one of the potential interference mitigation methods that benefits from the increased deployment of Massive MIMO at both the access point, i.e., base station, and the user side. The main idea is to minimize the dimension of the interference subspace by aligning multiple interference signals in a signal subspace with a dimension smaller than the number of interference signals. The aim of this research program is to establish a unified theoretical framework for the fundamental limits concerning the marriage of IA and Massive MIMO involving MTC with various practical constraints, and to develop sophisticated signal processing algorithms to realize such a concept in realistic environments. On the system-level, our research will develop novel and refined interference mitigation algorithms and techniques through the combination of IA and Massive MIMO involving MTC. There are also goals regarding the design of new models for wireless network architecture layouts under realistic scenarios (i.e. with the impacts of hardware-impairments and selection of multiple access strategies). Analysis of the performance of the proposed algorithms regarding error probability, outage probability, received signal-to-noise ratio statistics, and throughput will be assessed numerically and via simulations for conclusive results.

机器类型通信（MTC），诸如物联网（IoT）、设备到设备、机器到机器和无线传感器节点，最近已经作为无线通信领域中的突破性概念被引入，已经被广泛接受的是，蜂窝网络在提供如此广泛的连接机器及其相关设备方面发挥着重要作用。实现IoT的服务。思科视觉网络指数报告预测，到2025年，将有1000亿个物理对象连接到云。为了保持高的服务质量（QoS），并满足不断增长的数据速率需求，工业界和学术界的研究人员的基本目标之一是显着提高未来无线网络的频谱和能量效率。增加无线系统容量的主要方法有三种：a）进入新的频谱（毫米波），2）使该频谱更有效，3）使网络密度更大。为了容纳大量的设备，节点必须非常节能。 大规模天线系统（即大规模MIMO）为提高频谱和能源效率铺平了道路。在小规模的小区中，基站处的额外天线通过将能量集中到更少的空间区域来减少在相同频率-时间-码资源中服务的用户之间的小区内干扰。已知干扰对准（IA）是潜在的干扰减轻方法之一，其受益于在接入点（即，基站和用户侧。其主要思想是通过将多个干扰信号在一个维数小于干扰信号个数的信号子空间中对齐来最小化干扰子空间的维数。本研究计划的目的是建立一个统一的理论框架，有关婚姻的IA和大规模MIMO涉及MTC与各种实际约束的基本限制，并开发复杂的信号处理算法，以实现这样的概念在现实环境中。在系统级，我们的研究将通过IA和涉及MTC的Massive MIMO的组合来开发新颖且精细的干扰抑制算法和技术。还有关于在现实场景下（即，具有硬件损伤和多址接入策略的选择的影响）的无线网络架构布局的新模型的设计的目标。所提出的算法的性能分析，关于错误概率，中断概率，接收到的信噪比统计，和吞吐量将进行评估，并通过模拟的结论性结果。