Advanced Physical Layer Techniques for Wireless Communication Networks - A Factorization Approach

该研究项目探讨了先进物理层技术在无线通信网络中的潜在优势。在项目的前一部分，我们分析了一个基于Shannon速率模型的网络效用最大化问题，该模型用于描述网络中的无差错信息传输。这导致了分解方法，称为网络分解，它与作为首选介质访问技术的调度密切相关。因此，所提出的方法固有地对应于各自网络的未知容量区域的内部近似。在这个更新项目中，我们依赖于一个概念上的新模型，该模型基于对如何在网络编码通信网络中建模无线广播优势的不同理解。这个新概念是基于抽象广播函数的引入，用于描述网络中发送节点在其输出链路上的信息流。证明了适当定义的广播函数及其相应的速率域与图论中的多边形公式密切相关。因此，本更新项目的目标是在其最一般的概念中理解网络编码通信系统的多矩阵流模型，并基于所建议的多矩阵流模型同时分析无线通信网络中的信息流、介质访问控制机制和底层物理层参数的联合优化。与项目的第一部分相比，我们将重点扩展到非香农速率广播模型、随机访问技术和纯广播频道之外的物理层技术。

The research project addresses the potential benefits of Advanced Physical Layer Techniques in wireless communication networks. In the previous part of the project, we analyzed a Network Utility Maximization problem on the basis of Shannon Rate Models for describing error-free information transfer in a network. This led to decomposition approach, referred to as Network Factorization, which is tightly related to Scheduling as the Medium Access Technique of first choice. The proposed approach thus inherently corresponds to an inner approximation of the unknown capacity region of the respective network. In this renewal project we rely on a conceptionally new model based on a different understanding how to model the Wireless Broadcast Advantage in network coded communication networks. The new concept is based on the introduction of abstract Broadcast Functions for describing the information flow from a transmitting node in a network over its outgoing links. It has been shown that an appropriately defined broadcast function and its respective rate region is tightly related with a Polymatroid Formulation known from graph theory. The goal of this renewal project is thus to understand Polymatriod Flow Models for network coded communication systems in its most general conception and to analyze the joint optimization of the information flow, the Medium Access Control mechanism, and the underlying Physical Layer Parameters in a wireless communication network simultaenously based on the suggested polymatroid flow models. In contrast to the first part of the project we extend our focus on Non-Shannon Rate Broadcast Models, Random Access Techniques, and Physical Layer Techniques beyond pure broadcast channels.