LAUSR

Radio frequency identification (RFID)-assisted management systems have been widely applied in warehousing, logistics, retailing, etc. In these scenarios, RFID-aided applications, e.g., object tracking and human behavior sensing, rely on a high-efficiency tag reading to realize accurate analyses and timely responses. However, serious tag collisions in those large-scale RFID systems will inevitably lead to significant decreases in the tag reading rates. To meet the strict timeliness requirements of those practical applications, we aim to treat the individual reading rate for each item tag differently and focus more attention on those user-interactive ones. However, due to unpredictable user behaviors, it is impractical to infer the user-interactive tags in advance. In addition, keeping focusing on them for continuous monitoring despite user movements and multipath-prevalent environments is also challenging. To solve these problems, we propose Spotlight, the first concurrent rate-adaptive reading system in passive RFIDs. Spotlight screens the ID-agnostic user-interactive tags by proposing a multichannel feature for narrow-band RFID systems without any hardware or protocol modification and achieves rate-adaptive reading by implementing real-time MU-MIMO beamforming. Substantial experiments with 1000+ COTS RFID tags exhibit that Spotlight outperforms the commercial reader by $2.7\times $ and the SDR-based reader by $6.12\times $ . In addition, Spotlight first proposes the online parallel decoding method to realize concurrency among multiple users, which breaks the commercial protocol’s throughput ceiling (37%) and achieves up to 59% throughputs.