Improved Linearized Combinatorial Model (ILCM) for Optimal Frame Size Selection in ALOHA-based RFID Systems

Radio Frequency Identification (RFID) technology became the most important tool for identification of items and tracking. Nowadays, the most popular in terms of best price-performance ratio is passive RFID technology, where tags are both powered- up and communicating using the same radio waves transmitted via reader antenna(s). Since the objects with tags are usually moving in and out of range interrogated by the reader, it is crucial to identify all of them as soon as possible. In order to exchange data, reader and tags commonly use Dynamic Frame Slotted ALOHA (DFSA) transmission scheme, where the communication is divided in the time frames, latter divided in time slots. In DFSA system, tags randomly pick the time slot for the response. To increase tag reading rate it is necessary to set DFSA frame size properly. Calculations show that maximum tag reading rate can be achieved if frame size is set to a number of interrogating tags. Since the number of tags is generally unknown, it should be estimated correctly and the frame size set properly. In this paper we present the state of the art in the tag estimate methods along with performances of Q-Selection algorithm, a simple mechanism for frame size adaptation suggested as the standard in Gen2 RFID system. We introduce a new efficient optimal frame size selection method denoted as Improved Linearized Combinatorial Model (ILCM). Simulations results show that ILCM outperforms Q-Selection.