Reliable activity detection for massive machine to machine communication via multiple measurement vector compressed sensing
Reliable activity detection for massive machine to machine communication via multiple measurement vector compressed sensing
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DOI：
10.1109/glocomw.2014.7063573
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发表时间：
2014-12
期刊：
影响因子：
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通讯作者：
F. Monsees;C. Bockelmann;A. Dekorsy
中科院分区：
文献类型：
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作者：
F. Monsees;C. Bockelmann;A. Dekorsy
基于压缩感知的多用户检测是大规模机器对机器通信中的一个新颖的研究领域。该方法主要着眼于减少信令开销，在物理层实现复杂的检测算法，共同估计活动和数据。因此，活动检测的可靠性对于系统性能至关重要，因为如果用户被错误地分类为不活动，数据就会丢失。本文介绍了一种通过多测量矢量压缩感知方法来估计每帧节点活动的新方法。这种方法允许可靠的活动检测，其复杂性与传输帧的长度无关。此外，我们能够证明这种方法仅适用于探测器可用的少量测量。特别是，我们证明，如果观测数量大于系统中节点数量的平方根，则可以进行可靠的活动检测。
Compressed sensing based multiuser detection is a novel research field in massive machine to machine communication. Mainly focusing at decreasing signaling overhead, this approach implements sophisticated detection algorithms at the physical layer that jointly estimate activity and data. As a consequence, the reliability of the activity detection is crucial for the system performance as data is lost if users are erroneously classified as inactive. This paper introduces a novel approach to estimate node activity on a per frame basis by Multiple Measurement Vector Compressed Sensing approaches. This approach allows for reliable activity detection with complexity invariant of the length of the transmitted frame. Moreover, we are able to show that this approach works with only a few measurements available to the detector. In particular we demonstrate that reliable activity detection is possible if the number of observations is larger than the square root of the number of nodes in the system.