异构密集无线通信系统中网络化干扰对齐新方法研究

In heterogeneous dense wireless networks, there exists diverse interference, the demand of degrees of freedom (DoF) of the network cannot be satisfied. This project investigates the interference alignment (IA) techniques for heterogeneous dense wireless networks from the perspective of network, in order to improve the DoF of the system and satisfy the demand of DoF of the network. The parameters of heterogeneous dense wireless networks can be arbitrarily set, resulting in asymmetric network configuration. However, the existing IA schemes are mainly valid for symmetric homogeneous networks with specific parameter configurations, which cannot cover heterogeneous wireless networks with arbitrary parameter configurations. This project investigates the maximum DoF of heterogeneous dense wireless networks by constructing “genie chain” using subspace chain; analyzes feasibility of IA schemes for high performance multiple channel joint extension of heterogeneous dense wireless networks with non-generic IA conditions, by using algebraic geometry and measure theory; proposes the maximum DoF IA algorithm based on Group Lasso (Least Absolute Shrinkage and Selection Operator) by taking account of the group sparse structure of IA conditions; proposes joint IA and network channel resource allocation schemes based on graph theory to improve the network DoF for the scenarios where the maximum DoF cannot be approached or achieved by using only IA schemes.

在异构密集无线网络环境中，干扰关系复杂多变，网络自由度需求无法得到满足。本项目从网络化的角度研究异构密集无线网络中的干扰对齐技术，提升系统自由度，满足网络自由度需求。异构密集无线网络参数具有任意配置、非对称性的特点。然而，已有的干扰对齐方案主要针对具有特定网络参数的对称性同构网络，无法全面涵盖任意配置的无线异构网络。本项目通过子空间链构造“精灵链”，推导异构密集无线网络系统最大可达自由度；针对系统中高性能多信道联合扩展场景下干扰对齐条件的非泛化特点，运用代数几何理论以及测度论，分析异构密集无线网络干扰对齐方案的可行性；针对干扰对齐条件的组稀疏结构，提出基于Group Lasso(Least Absolute Shrinkage and Selection Operator: Lasso)的自由度最大化干扰对齐算法；针对某些场景下，仅靠单一干扰对齐方案无法逼近或者达到网络最大自由度的问题，提出基于图论的联合干扰对齐与网络信道资源分配的网络自由度提升方案。

在异构密集无线网络环境中，干扰关系复杂多变，网络自由度需求无法得到满足。项目组从网络化的角度研究异构密集无线网络中的干扰对齐技术，提升系统自由度，满足网络自由度需求，主要成果如下：.1）推导了无线网络最大自由度.针对任意拓扑的MIMO部分连接干扰信道网络，提出了基于图论的链式干扰对齐方案，获得网络的最大自由度。.2）推导了干扰对齐方案可行的必要条件.分析了三种不同信道扩展场景下，给定自由度需求和系统配置参数下干扰对齐方案的可行性，推导出干扰对齐方案可行的必要条件。.3）突破了网络干扰对齐关键技术.设计了可以逼近甚至达到网络最大自由度的迭代干扰对齐算法；设计了基于广义特征值分解的干扰对齐方法，提高了网络自由度；设计了协作拓扑干扰对齐方案，降低了对信道状态信息的要求，提升了网络性能。.4）设计了联合干扰对齐和信道资源分配以及缓存的方案.设计了无线网络下联合干扰对齐与网络子信道资源分配策略，满足网络中用户差异化的自由度需求；针对密集异构无线网络，设计了联合干扰对齐和缓存技术的方案，提升网络容量；设计了异构网络联合干扰对齐与缓存放置方案，提升传输文件的命中率。