## 1 Introduction  
Radio Frequency Identification (RFID) is a wireless technology that uses radio waves to collect and transfer data from an RFID tag or (transponder) attached to an object linked to an RFID reader or (interrogator) for the purpose of identification, tracking, and data capturing. It is expected to be the next generation mutation in auto identification technologies, and the future seems very auspicious for this technology [1]. The reason behind using RFID instead of other auto identification techniques, such as barcode and smart cards, relates to its advantages of disregarding the line of sight, working for a long range between tags and the reader (over 100 m long), capability of writing on tags, simultaneous reading of multiple tags, immunity against harsh weather conditions such as rain and fog, and susceptibility to being integrated using sensors [2]. Despite these advantages, RFID technology has the limitation of tags collision when multiple tags existing in the reader interrogation zone respond to its request simultaneously. Therefore, many anti-collision protocols have been proposed by researchers to overcome the collision problem and ensure a full read rate when the capture effect phenomenon exists with good identification efficiency and a low time delay. However, they experienced drawbacks, including the influence of interference and a lack of the blocking technique [3; 4; 5]. Anti-collision protocols are mainly categorized into three classes: aloha-based(probabilistic), tree-based (deterministic), and hybrid protocols [6]. In aloha-based protocols, such as dynamic frame slotted aloha (DFSA), the time is divided into several frames by the reader, and each frame consists of several slots, such that the \(i\)-th slot belongs to the frame length F, which is from 0 to F\(-\)1. At the beginning of the identification process, the reader broadcasts the frame length to the tags that exist in its interrogation zone, and then each tag randomly selects a time slot to respond. If multiple tags respond to the same slot, a collision slot would occur. Alternatively, if no tag responds to a specific slot, an idle slot would result. Intuitively, a readable slot occurs when only one tag responds to a slot. At the end of the frame, the reader estimates the number of collided tags in order to adjust the frame length F of the next reading cycle. Aloha protocols have simple implementation but suffer from the problem of \"tags starvation\", in which some tags might not be identified (recognized), even after a long identification period [7]. In addition, the throughput of aloha protocols depends on the tags estimation methods and has a peak efficiency of 37% for dynamic frame slotted aloha (DFSA) and 43% for tree slotted aloha (TSA), accompanied by complex implementation and a high identification delay [6; 8]. Secondly, tree-based protocols are mainly divided into binary tree (memory based protocols) and query tree (memoryless based protocols). In both classes, the collided tags are recursively divided into two disjoint subsets from root to leaves, until there is one tag or no tag in each leaf. The root of the tree represents the beginning of the identification process. The intermediate nodes denote the collided tags, and the leaves of the tree indicate the readable and idle cycles [9]. Moreover, tree-based protocols have shown better performance and efficiency compared to aloha protocols. However, they suffer from many collisions at the beginning of the identification process, with a system efficiency below 50% [6]. Moreover, the identification efficiency of deterministic protocols is affected by the length and distribution of the tag IDs and the population size [7].