Parallel decoding of backscatter improves communication throughput by enabling concurrent transmission of backscatter tags. In practical applications of parallel decoding, it is extremely difficult to distinguish collided signals in superclusters where multiple signal clusters overlap. Existing methods are usually effective for superclusters with uniformly distributed signals. Nevertheless, there are many more scenarios in which signals in superclusters tend to gather unevenly, and existing methods cannot work. Such uneven clustering of signals occurs due to the following two possible causes: (1) signal-strengthdifferences (SSDs) among tags; or (2) cluster drifting (CD) driven by interferences from other objects within communication environments. This paper proposes a novel scheme called SalixLeaf, which aims to identify the main veins of signal clusters to address this problem of superclusters with unevenly distributed signals. Salix-Leaf identifies the main vein of each signal cluster for fine-grained clustering so that the direction of the main veins can be used to verify the accuracy of clustering. In addition, SalixLeaf employs a supercluster decomposer that divides signals into different segments for clustering analysis, enhancing robustness and practicability. Experimental results show that Salix-Leaf achieves a 1.2-fold increase in throughput and a 25% reduction in bit error rate (BER) compared to the state-of-the-art.

Summary The main challenge of access control system is how to allow authorized users to access quickly and accurately. In reality, most access control system cannot run smoothly with the adverse impact of a security problem, it is because the access control card is easy to duplicate. To improve system security, recent efforts introduced biological technologies, such as fingerprint identification, facial recognition, and iris recognition. However, these methods are costly for installation and later maintenance. In this paper, we introduce a cloud access control system that employs the ability of sensing acceleration of Wireless Identification and Sensing Platform (WISP) tags combined with customized motions. Users are allowed to pass the access control system only if they operate user‐defined motions correctly. Authorized users can define the authentication motions by themselves, which not only facilitates the daily use but also improves the security of the cloud access control system. We conduct intensive experimental measurements. The experimental results verify the effectiveness of our proposed system.