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首页> 外文期刊>IEEE Transactions on Information Theory >Compute-and-Forward in Large Relaying Systems: Limitations and Asymptotically Optimal Scheduling
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Compute-and-Forward in Large Relaying Systems: Limitations and Asymptotically Optimal Scheduling

机译：大型中继系统中的计算和前进：限制和渐近最佳调度

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摘要

Compute and Forward (CF) is a coding scheme which enables receivers to decode linear combinations of simultaneously transmitted messages while exploiting the linear properties of lattice codes and the additive nature of a shared medium. The scheme was originally designed for relay networks, yet, it was found useful in other communication problems, such as MIMO communication. Works in the current literature assume a fixed number of transmitters and receivers in the system. However, following the increase in communication networks density, it is interesting to investigate the performance of CF when the number of transmitters is large. In this work, we show that as the number of transmitters, L, grows, CF becomes degenerated, in the sense that a relay prefers to decode only one (strongest) user instead of any other linear combination of the transmitted codewords, treating the other users as noise. Moreover, the system's sum-rate tends to zero as well. This makes scheduling necessary in order to maintain the superior abilities CF provides. We thus examine the problem of scheduling for CF. We start with insights on why good scheduling opportunities can be found. Then, we provide an asymptotically optimal, polynomial-time scheduling algorithm and analyze its performance. We conclude that with proper scheduling, CF is not merely non-degenerated, but, in fact, provides a gain for the system sum-rate, up to the optimal scaling law of O(log log L).
机译：计算和前进（CF）是一种编码方案，其使接收器能够在利用晶格代码的线性属性和共享介质的添加剂性质的同时解码同时发送的消息的线性组合。该方案最初设计用于中继网络，但发现它被发现在其他通信问题中有用，例如MIMO通信。在当前文献中的工作假设系统中的固定数量的发射器和接收器。然而，在通信网络密度的增加之后，当变送器的数量大时，有趣的是研究CF的性能。在这项工作中，我们表明，随着发射器的数量，L，增长，CF变得退化，即中继更喜欢仅解码一个（最强）用户而不是发送码字的任何其他线性组合，处理另一个用户作为噪音。此外，系统的总和率也趋于零。这使得能够维持优势能力CF提供的调度。因此，我们检查了对CF的调度问题。我们从洞察中开始了解为什么可以找到良好的调度机会。然后，我们提供渐近最优，多项式调度算法并分析其性能。我们得出结论，通过适当的调度，CF不仅仅是非退化的，而且实际上为系统总和率提供了增益，直至O（日志LOG L）的最佳缩放法。

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