Compressed sensing Bayes-risk detection for frame based multi-user systems

F. Monsees, C. Bockelmann, A. Dekorsy
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Abstract

Performing joint activity and data detection has recently gained attention for reducing signaling overhead in multi-user Machine-to-Machine Communication systems. In this context, Compressed Sensing has been identified as a good candidate for joint activity and data detection especially in scenarios where the activity probability is very low. This paper augments activity and data detection for frame based multi-user uplink scenarios where nodes are (in)active for the duration of a frame. We propose a two stage detector which first estimates the set of active nodes followed by a data detector. Our detector outperforms symbol-by-symbol Maximum a posteriori detection.
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基于帧的多用户系统压缩感知贝叶斯风险检测
在多用户机器对机器通信系统中,执行联合活动和数据检测最近引起了人们的关注,以减少信令开销。在这种情况下,压缩感知已被确定为联合活动和数据检测的良好候选,特别是在活动概率非常低的情况下。本文增强了基于帧的多用户上行场景的活动和数据检测,其中节点在帧持续时间内处于活动状态。我们提出了一种两阶段检测器,它首先估计活动节点集,然后是数据检测器。我们的检测器优于逐个符号的最大后验检测。
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