The number of wireless devices is drastically increasing, resulting in many devices contending for radio resources. In this work, we present an algorithm to detect active devices for unsourced random access, i.e., the devices are uncoordinated. The devices use a unique, but non-orthogonal preamble, known to the network, prior to sending the payload data. They do not employ any carrier sensing technique and blindly transmit the preamble and data. To detect the active users, we exploit partial channel state information (CSI), which could have been obtained through a previous channel estimate. For static devices, e.g., Internet of Things nodes, it is shown that CSI is less time-variant than assumed in many theoretical works. The presented iterative algorithm uses a maximum likelihood approach to estimate both the activity and a potential phase offset of each known device. The convergence of the proposed algorithm is evaluated. The performance in terms of probability of miss detection and false alarm is assessed for different qualities of partial CSI and different signal-to-noise ratio.

翻译：无线装置的数量正在急剧增加,导致许多设备争夺无线电资源。 在这项工作中,我们提出了一个算法,用于检测用于无源随机访问的主动装置,即这些装置不协调。这些装置在发送有效载荷数据之前使用一个独特的但非垂直的前言,这是网络所知道的。它们不使用任何载体遥感技术,盲目传输序言和数据。为了检测活跃用户,我们利用部分频道状态信息,这些信息可以通过先前的频道估计获得。对于静态装置,例如,“事物节点”的互联网,显示CSI比许多理论作品中假设的时间变化性要小。所展示的迭代方算法使用了最大可能性的方法来估计每个已知装置的活动和潜在阶段的抵消。所拟议的算法的趋同性得到了评估。从误测概率和假警报的性能评估了部分 CSI 和不同信号到噪音比率的不同质量。