Radio frequency identification technology is one of the main technologies of Internet of Things (IoT). Through the transmission and reflection of wireless radio frequency signals, non-contact identification is realized, and multiple objects identification can be realized. However, when multiple tags communicate with a singleton reader simultaneously, collision will occur between the signals, which hinders the successful transmissions. To effectively avoid the tag collision problem and improve the reading performance of RFID systems, two advanced tag identification algorithms namely Adaptive M-ary tree slotted Aloha (AMTS) based on the characteristics of Aloha-based and Query tree-based algorithms are proposed. In AMTS, the reader firstly uses the framed slotted Aloha protocol to map the tag set to different time slots, and then identify the collided tags using binary search method based on collision factor or mapping table. Both performance analysis and extensive experimental results indicate that our proposed algorithms significantly outperforms most existing anti-collision approaches in tag dense RFID systems.

Radio frequency identification (RFID) technology is rapidly emerging as one of key technologies for Industrial Internet of Things (IIoT) [

The rapid multi-tag identification is the first type of issue that attracted the attention of researchers in the RFID community. Generally speaking, mainstream tag identification algorithms are divided into two categories according to the functional characteristics: Aloha-based algorithms
[

In this paper, we designed and implemented a hybrid architecture of tag identification, and proposed two hybrid tag identification algorithms. These two algorithms inherit the advantages of Aloha-based and deterministic algorithms, and abandon mutual shortcomings. In particular, our proposed algorithms do not need to provide an accurate estimation of the number of tags in collision phase, thereby avoiding the negative impact of estimation errors on performance, and reducing the computational complexity. Moreover, their efficiency will not be affected by the number of tags and tag IDs distribution.

The remainder of this paper is organized as follows. In Section 2, we reviewed the existing the anti-collision algorithms. Section 3 presents the system model and our proposed hybrid algorithm. In Section 4, mathematical analysis and performance evaluation through simulations is conducted. Section 5 concludes the whole paper.

As mentioned above, existing anti-collision algorithm mainly consists of two types: Aloha-based and deterministic algorithm. The deterministic algorithm can be further divided into two types: Query tree [

In Aloha-based algorithm, each tag randomly picks up a slot to respond
to the reader after extracting the parameters including frame size and communication rate from the reader’s command. The representative is the adaptive Q-algorithm based on UHF RFID standard EPC C1 Gen2 protocol.
According to [^{Q} −1); here,

All tags to be identified in each identification round are successfully read in one round. Thus there is only one

If the access event is a collision, the reader sends a _{fp}

If the access event is empty, the reader sends a

If the access event is success, the reader sends a _{fp}_{fp}

The advantage of the Aloha-based algorithms represented by the Q-algorithm is that they are easy to implement on the reader side. However, the random nature of such type of algorithm will cause the performance to fluctuate with the number of tags.

Our proposed Adaptive M-ary tree slotted Aloha (AMTS) algorithm starts
a round of identification process by broadcasting a probe command with a key parameter named frame size [

In what follows, we elaborate on the principles and operating mechanisms of these two algorithms.

(1) CF-AMTS: Algorithm description

In this paper, we define a variable called collision factor, which is expressed as

In the above formula, k represents the number of collision bits in the
current time slot, and n is the tag ID length. We make the following assumption that the current slot is a collision slot and there are m tags to be identified. For any bit in a string responded by the tag, the probability that it will not collide can be expressed as 1/2^{m −1},

Correspondingly, we can derive the average number of slots spent by the reader to identify

According to

Combining formula

(2) MF-AMTS: Algorithm description

In the next, we elaborate on the second AMTS algorithm, namely MF-AMTS algorithm. The salient feature of this algorithm is to use the mapping table to estimate the tag cardinality in a collision slot.

2 bits | 4 bits |
---|---|

00 | 000 |

01 | 00 |

10 | 0 |

11 |

slot | Search command | Response | Identification |
---|---|---|---|

1 | 0xx0 | ||

2 | 110 | 0100 | 11010001 |

3 | 111 | 0010 | 11101010 |

By comparing

Where _{e}_{r}_{c}_{e}_{r}_{c}

If

We theoretically analyze the total number of slots required for our proposed two AMTS algorithms and then deduce the system efficiency. Specifically, the total number of slots can be obtained by summing the frame size

Herein

Through

Referring to the analysis in [

in which

Then, the total number of slots taken by MF-AMTS is calculated as

Then, the system efficiency of CF-AMTS and MF-AMTS can be calculated as

We implement the proposed algorithm in MATLAB on a ThinkPad X1 Carbon desktop with an Intel 2.4 GHz CPU. Our simulation setting follows the specifications of the EPC C1 Gen2 standard. The number of tags is from 50 to
1000 in step of 50. The reader-to-tag transmission rate and the tag-to-reader data rate are not symmetric, which depends on specific physical implementations and practical environments. The main time parameters used in MATLAB simulations are listed in

Parameters | Values |
---|---|

Tari | 12.5 |

BLF | 125 kHz |

Tpri | |

TRrate | 125 kbps |

RTrate | 64 kbps |

TRcal | 64 |

T1 | 80 |

T2 | 40 |

T3 | 40 |

The performance of the our proposed AMTS algorithms are evaluated in terms of average required slots for one tag identification, the number of total slots, and energy efficiency.

In

To further evaluate the performance of our proposed algorithms. We use
another important evaluation metric, i.e., energy efficiency. We define the energy efficiency metric for every energy unit _{u}

where Q, S and W are number of queries, slots and mode switches, respectively. _{q}_{s}

In this paper, we present 2 multi-tag identification algorithms based on hybrid architecture to improve the reading efficiency in tag dense RFID scenarios. The contributions are concluded as follows. Compared with existing anti-collision algorithms, our proposed approaches in this paper not only have higher system throughput, but also do not require precise cardinality estimation of the entire tag set, and hence they can be easily implemented on low-cost RFID readers. Both theoretical analysis and various experimental results verify that our proposed algorithms are superior to prior art in terms of system throughput, the total number of slots and energy efficiency.