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arXiv 0704.0967cs.ITcs.ARmath.IT
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基于高斯矢量广播信道的MIMO Mesh网络跨层优化

Cross-Layer Optimization of MIMO-Based Mesh Networks with Gaussian Vector Broadcast Channels

Jia Liu, Y. Thomas Hou

摘要:

MIMO技术是过去十年来增加信道容量的最重要的进步之一,并且具有提高网状网络的网络容量的巨大潜力。在基于MIMO的网状网络中,从共享公共通信频谱的每个节点传出的链路可以被建模为高斯矢量广播信道。最近,研究人员表明,“脏纸编码”(DPC)是高斯矢量广播信道的最佳传输策略。到目前为止,很少有人研究这个基本结果将如何影响基于MIMO的网状网络的跨层设计。为了填补这一空白,我们考虑的问题,共同优化DPC功率分配在链路层中的每个节点和多跳/多路径路由在MIMO为基础的网状网络。事实证明,这个优化问题是一个非常具有挑战性的非凸问题。为了解决这个困难,我们利用通道的对偶性将原问题转化为等价问题。对于转换后的问题,我们开发了一个有效的解决方案,集成拉格朗日对偶分解方法,共轭梯度投影方法的基础上矩阵微分,切割平面方法,和次梯度方法。在我们的数值示例中,表明使用DPC可以实现34.4%的网络性能提升。

英文摘要:

MIMO technology is one of the most significant advances in the past decade to increase channel capacity and has a great potential to improve network capacity for mesh networks. In a MIMO-based mesh network, the links outgoing from each node sharing the common communication spectrum can be modeled as a Gaussian vector broadcast channel. Recently, researchers showed that ``dirty paper coding'' (DPC) is the optimal transmission strategy for Gaussian vector broadcast channels. So far, there has been little study on how this fundamental result will impact the cross-layer design for MIMO-based mesh networks. To fill this gap, we consider the problem of jointly optimizing DPC power allocation in the link layer at each node and multihop/multipath routing in a MIMO-based mesh networks. It turns out that this optimization problem is a very challenging non-convex problem. To address this difficulty, we transform the original problem to an equivalent problem by exploiting the channel duality. For the transformed problem, we develop an efficient solution procedure that integrates Lagrangian dual decomposition method, conjugate gradient projection method based on matrix differential calculus, cutting-plane method, and subgradient method. In our numerical example, it is shown that we can achieve a network performance gain of 34.4% by using DPC.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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