Efficient Range Queries for Large-Scale Sensor-Augmented RFID Systems

This paper studies the practically important problem of range query for sensor-augmented RFID systems, which is to classify the target tags according to the ranges specified by the user. The existing RFID protocols that seem to address this problem suffer from either low time-efficiency or the information corruption issue. To overcome their limitations, we first propose a basic classification protocol called Range Query RQ, in which each tag pseudo-randomly chooses a slot from the time frame and uses the ON-OFF Keying modulation to reply its range identifier. Then, RQ employs a collaborative decoding method to extract the tag range information from singleton and even collision slots. The numerical results reveal that the number of queried ranges significantly affects the performance of RQ. To optimize the number of queried ranges, we further propose the Partition& Mergence PM approach that consists of two steps, i.e., top-down partitioning and bottom-up merging. Sufficient theoretical analyses are proposed to optimize the involved parameters, thereby minimizing the time cost of RQPM or minimizing its energy cost. We can trade off between time cost and energy cost by adjusting the related parameters. The prominent advantages of the RQPM protocol over previous protocols are two-fold: i it is able to make use of the collision slots, which are treated as useless in previous protocols. Thus, frame utilization can be significantly improved; ii it is immune to the interference from unexpected tags, and does not suffer information corruption issue. We use USRP and WISP tags to conduct a set of experiments, which demonstrate the feasibility of RQPM. Extensive simulation results reveal that RQPM can ensure 100 query accuracy, and reduce the time cost as much as 40 when comparing with the state-of-the-art protocols.