RFID tag acquisition via compressed sensing

We focus on simultaneously identifying a small subset of radio frequency identification tags out of a large known total set. This, for instance, applies to the popular use-case of a supermarket checkout where the items in a shopping cart need quick and reliable identification. Since the number of items in the cart is usually very small compared to the total amount of inventoried items in a store, it appears natural to formulate the identification problem according to compressed sensing, exploiting the inherent sparsity of the problem and allowing collisions in tag responses rather than avoiding them. This yields a very efficient way of identifying tags with only a small number of measurements. We introduce a novel tag identification scheme that utilizes the computationally cheap Approximate Message Passing (AMP) algorithm. A simulation-based heuristic is introduced to minimize the number of required measurements for AMP recovery. Furthermore, a method of implementation is sketched, and the performance of the proposed scheme is investigated and compared to the well known frame slotted aloha protocol. A large gain in identification throughput is achieved.