Imagine a coverage area where each mobile device is communicating with a preferred set of wireless access points (among many) that are selected based on its needs and cooperate to jointly serve it, instead of creating autonomous cells. This effectively leads to a user-centric post-cellular network architecture, which can resolve many of the interference issues and service-quality variations that appear in cellular networks. This concept is called User-centric Cell-free Massive MIMO (multiple-input multiple-output) and has its roots in the intersection between three technology components: Massive MIMO, coordinated multipoint processing, and ultra-dense networks. The main challenge is to achieve the benefits of cell-free operation in a practically feasible way, with computational complexity and fronthaul requirements that are scalable to enable massively large networks with many mobile devices. This monograph covers the foundations of User-centric Cell-free Massive MIMO, starting from the motivation and mathematical definition. It continues by describing the state-of-the-art signal processing algorithms for channel estimation, uplink data reception, and downlink data transmission with either centralized or distributed implementation. The achievable spectral efficiency is mathematically derived and evaluated numerically using a running example that exposes the impact of various system parameters and algorithmic choices. The fundamental tradeoffs between communication performance, computational complexity, and fronthaul signaling requirements are thoroughly analyzed. Finally, the basic algorithms for pilot assignment, dynamic cooperation cluster formation, and power optimization are provided, while open problems related to these and other resource allocation problems are reviewed. All the numerical examples can be reproduced using the accompanying Matlab code.
翻译:想象一下每个移动设备与首选的一组无线接入点( 包括许多) 进行沟通的覆盖区域, 这些无线接入点是根据需求选择的, 并合作为它共同服务, 而不是创建自主的细胞。 这有效地导致一个以用户为中心的后细胞网络结构, 能够解决许多干扰问题和细胞网络中出现的服务质量差异。 这个概念叫做“ 以用户为中心的无细胞无细胞大规模 MIMO ( 多重输入多输出) ”, 其根源在于三个技术组成部分的交叉点: Massive MIMO, 协调的多点处理, 以及超临界网络。 主要的挑战是如何以实际可行的方式实现无细胞运行的好处, 实现无细胞运行的配置, 以计算复杂性和前导要求为主, 以可实现的基价配置和分布的 数据配置问题 。 最终的光谱交易效率, 以激励和数学计算为主的模型, 将数据转换到其它的系统 。