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Throughput Region of Spatially Correlated Interference Packet Networks

机译：空间相关干扰分组网络的吞吐量区域

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摘要

In multi-user wireless packet networks, interference, typically modeled as packet collision, is the throughput bottleneck. Users become aware of the interference pattern via feedback and use this information for contention resolution and packet retransmission. Conventional random access protocols interrupt communication to resolve contention, which reduces network throughput and increases latency and power consumption. In this paper, we take a different approach, and we develop opportunistic random access protocols rather than pursuing conventional methods. We allow wireless nodes to communicate without interruption and to observe the interference pattern. We then use this interference pattern knowledge and channel statistics to counter the negative impact of interference. We prove the optimality of our protocols using an extremal rank-ratio inequality. An important part of our contributions is the integration of spatial correlation in our assumptions and results. We identify spatial correlation regimes in which inherently outdated feedback becomes as good as idealized instantaneous feedback and correlation regimes in which feedback does not provide any throughput gain. To better illustrate the results, and as an intermediate step, we characterize the capacity region of finite-field spatially correlated interference channels with delayed channel state information at the transmitters.
机译：在多用户无线分组网络中，通常将其建模为分组冲突的干扰是吞吐量瓶颈。用户通过反馈了解干扰模式，并将此信息用于争用解决和数据包重传。传统的随机访问协议会中断通信以解决争用，这会降低网络吞吐量并增加等待时间和功耗。在本文中，我们采用了不同的方法，并且我们开发了机会随机访问协议，而不是追求常规方法。我们允许无线节点无间断地进行通信并观察干扰模式。然后，我们使用这种干扰模式知识和信道统计信息来应对干扰的负面影响。我们使用极值秩比不等式证明了协议的最优性。我们贡献的重要部分是将空间相关性整合到我们的假设和结果中。我们确定了空间相关性机制，其中固有的过时反馈变得与理想化的瞬时反馈一样好，相关性机制中的反馈不提供任何吞吐量增益。为了更好地说明结果，并作为中间步骤，我们用发射机处的延迟信道状态信息来表征有限域空间相关干扰信道的容量区域。

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