Non-Cooperative Compute-and-Forward Strategies in Gaussian Multi-Source Multi-Relay Networks
Non-Cooperative Compute-and-Forward Strategies in Gaussian Multi-Source Multi-Relay Networks
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DOI：
10.1109/vtcfall.2015.7391036
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发表时间：
2015-09
期刊：
影响因子：
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通讯作者：
J. Richter;J. Hejtmánek;Eduard Axel Jorswieck;J. Sýkora
中科院分区：
文献类型：
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作者：
J. Richter;J. Hejtmánek;Eduard Axel Jorswieck;J. Sýkora
计算和前向是一种新兴技术，可以增加干扰网络中的吞吐量。它允许继电器解码代码字的方程，而不是每个编码字。选择适当的方程式在性能中起着至关重要的作用。尽管有几种算法可以解决此优化问题，但它们都执行局部优化。在大型继电器网络中，这可能会导致目的地的线性方程，并具有较大的中断概率。在本文中，我们提出了有关如何选择所需方程和执行线性独立方程的新的非合作策略。这允许以局部和分布的方式解决优化问题。此外，我们比较了这些策略的可实现的汇率，并表明相关信号对性能产生了巨大影响。
Compute-and-forward is an emerging technique to increase throughput in interference networks. It allows the relays to decode an equation of codewords instead of each single codeword. Choosing the appropriate equation plays a crucial role on the performance. While there are several algorithms that solve this optimization problem, they all perform a local optimization. In large relay networks this can result in linear dependent equations at the destination and a large outage probability. In this paper we propose new non-cooperative strategies on how to choose the desired equations and enforce linear independent equations. This allows to solve the optimization problem in a localized and distributed manner. Further we compare the achievable sum-rate of those strategies and show that correlated signals have a huge impact on the performance.