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This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

In RFID systems, the performance of each reader such as interrogation range and tag recognition rate may suffer from interferences from other readers. Since the reader interference can be mitigated by output signal power control, spectral and/or temporal separation among readers, the system performance depends on how to adapt the various reader arbitration metrics such as time, frequency, and output power to the system environment. However, complexity and difficulty of the optimization problem increase with respect to the variety of the arbitration metrics. Thus, most proposals in previous study have been suggested to primarily prevent the reader collision with consideration of one or two arbitration metrics. In this paper, we propose a novel cross-layer optimization design based on the concept of combining time division, frequency division, and power control not only to solve the reader interference problem, but also to achieve the multiple objectives such as minimum interrogation delay, maximum reader utilization, and energy efficiency. Based on the priority of the multiple objectives, our cross-layer design optimizes the system sequentially by means of the mixed-integer linear programming. In spite of the multi-stage optimization, the optimization design is formulated as a concise single mathematical form by properly assigning a weight to each objective. Numerical results demonstrate the effectiveness of the proposed optimization design.

Radio frequency identification (RFID) is a non-contact technology that helps machines or computers identify objects, record metadata or control individual target through radio wave. Essentially, RFID is a technology that connects objects to Internet, so the objects can be tracked and their information can be shared. The concept of RFID technology is simple: Place a tag,

Recently, ultra high frequency (UHF) band passive RFID systems, which operate in the 860–960 MHz, have received considerable attention. It is generally accepted that the UHF RFID system connected to intelligent wireless sensor network can revolutionize commercial processes or present many opportunities for process improvement such as supply-chain management [

There are two primary types of controllable reader interference in the UHF RFID system; reader-to-tag interference and reader-to-reader interference [

The reader interference problem can be solved by output signal power control of each reader, spectral and/or temporal separation among the interfering readers. The system performance in terms of tag recognition rate, interrogation coverage and delay, reader utilization,

In this paper, we introduce a novel cross-layer optimization design based on mixed-integer linear programming (MILP), which optimally assigns communication channel, time, and output power to each RFID reader. The solution from the optimization design not only solves the reader interference problem, but also achieves multiple objectives such as minimum interrogation cycle, maximum reader utilization, and energy efficiency. Based on the priority of the multiple objectives, our cross-layer design is presented as a three-stage optimization problem. In the first stage, we optimize the RFID system to have minimum cycle time. Here, each RFID reader should be scheduled to successfully recognize the tags within its desired interrogation range at least once during a cycle. Once the temporal schedule is assigned, the RFID readers repeat the same temporal pattern after one cycle. Our first aim is to minimize this cycle so that interrogation delay of RFID reader can be minimal. In general, the solution,

The rest of the paper is organized as follows. The existing proposals to solve the RFID reader interference problem are reviewed in Section 2, and the network model and interference model are introduced in Section 3. The cross-layer optimization designs are presented in Section 4. Numerical results and comparative view of the anti-collision approaches are shown in Sections 5 and 6. Finally, we give our concluding remarks in Section 7.

Interference caused by the operation of an RFID reader is referred to as a reader collision [

Space division multiple accesses (SDMA) relates to techniques that reuse channel capacity in spatially separated areas. The simplest solution is to significantly reduce the range of a single reader, but it requires a number of readers to cover the operation field. Another solution is to use an electronically controlled directional antenna on the reader, the directional beam can be pointed directly at a tag. Thus, various tags can be differentiated by their angular position in the interrogation zone of the reader. However, the SDMA technique requires the relatively high implementation cost of the complicated antenna system.

RFID standards such as ISO/IEC 18000-6 [

Fully distributed frequency allocation (FDFA) and semi distributed frequency allocation (SDFA) [

In TDMA based collision resolution schemes, transmission time is divided into frames with several fixed-length time slots. To avoid simultaneous transmissions each reader is required to operate at a different time slot in a frame. To execute the slot distribution a pair of distributed algorithms called DCS and VDCS (or Colorwave) [

In DCS, the frame size is fixed and thus its implementation is simple. However, the performance is decreased when the frame size does not match the number of readers. For example, if the frame size is small and the number of active readers is large, then the efficiency may be low due to heavy collisions. The opposite may be also inefficient due to lots of idle slots. To solve this problem, Colorwave allows each reader to dynamically change its frame size. In Colorwave, each reader monitors the percentage of successful transmissions during a particular time period. If the percentage of successful transmission goes below a lower threshold, the frame size is incremented. If the percentage increases beyond an upper threshold, the frame size is decremented. Since Colorwave builds upon DCS, the process to solve the reader collision is the same as that of DCS.

Colorwave is an effective algorithm to avoid collisions based upon local information. However, in Colorwave the readers may experience a number of collisions until it eventually reaches the steady state. The major drawback of the algorithm is that it takes some time for readers to find appropriate frame size. Furthermore, each reader cannot determine whether current frame size is optimal and it may keep changing its frame size. To cope with the oscillation problem, Enhanced colorwave was proposed [

Neighbor friendly reader anti-collision (NFRA) [

In the European regulation as outlined in ETSI EN 302 208 [

Slotted-LBT [

Reader synchronized(RS)-LBT schemes [

PULSE [

Tanaka and Sasase [

Recent works have explained that higher interference merely causes a reduction in the interrogation range of the RFID reader [

In [

On the other hand, PPC attempts to temporally separate the readers by appropriately assigning a time period to each of them, along with the power control. However, any scheme to adaptively distribute the time period is not provided due to the complexity of the problem. Consequently, PPC is only implemented using a fixed power distribution and distribution sets obtained from a neural network, which is one of heuristic methods.

When a number of RFID readers operate in a region, the performance of distributed anti-collision schemes may reduce [

HiQ [

RA-GA [

Most solutions to the reader collision problem do not simultaneously consider various reader arbitration metrics such as channel, time, and power. For more effective anti-collision solution, it is desirable to analytically model the reader interference with consideration of the various metrics. Then, based on the analytic models, useful optimization schemes can be extracted and solved. In the next section, the reader-to-reader interference model to analyze the relationship between the interference powers from multiple readers and the interrogation range of a desired reader, and the network model for the problem formulation are introduced.

Consider a passive RFID system in which _{R}_{C}_{S}

Let
_{R}_{C}_{S}_{min} and _{max} denote the minimum output power required for the tag operation and the limit on the maximum output power, respectively. For example,

As the requirement of active readers, the reply of any tag within their interrogation ranges should be successfully decodable. That means that the SINR of a signal backscattered from the tag should meet a given threshold. The SINR of the backscattered signal is influenced by the output power of the reader, interference from the other readers and others. In the next sub-section, we derive the reader interference model to determine active readers and their corresponding powers.

In a passive RFID system, to successfully recognize a tag, the SINR of a signal backscattered from the tag must exceed a threshold, which depends on the tag encoding method and the desired BER. Let _{A}_{A}_{BA}_{0} denotes the background noise power and Γ represents the required SINR threshold. Since the tag reflects a fraction of the power received from reader _{A}_{A}_{A}_{tag} is the effective power reflection coefficient of a tag, _{A}_{T} and _{R} are the gains of the transmit antenna and the receive antenna, respectively. As the received signal travels to and from the tag, it experiences channel path-losses. Since the forward and backward path-losses are identical, the total path-loss becomes
_{BW} denotes the fractional power ratio in the bandwidth that is used. _{BW} can be expressed, using the power spectral density (PSD) function Φ(_{BW} is approximated to 0.86 for FM0 code and 0.78 for Miller subcarrier sequence code, respectively [

For the tag operation, each tag must be supplied with the energy more than that of the threshold power, which is determined according to the chip design of the tag and matching condition of the antenna. The minimum output signal power of reader _{A}_{TH} denotes the threshold power,

The interference power from reader _{BA}_{BA}_{A}_{B}

So far, we have presented an FDMA-based interference model with two readers. In case of the FDMA-based anti-collision scheme, when the number of active readers is larger than that of available channels, the readers may suffer from persistent reader collision. Thus, we need to employ the TDMA scheme also to eliminate more readers from competing with each other. In adopting TDMA scheme, we have the SINR constraint for an active reader _{i}_{1} and _{2} represent

In this section, we propose a novel MILP based cross-layer optimization design, which optimally assigns communication channel, time, and output power to each RFID reader. Based on the priority of the multiple objectives, our cross-layer design is presented as a three-stage problem, which sequentially optimizes the system. However, this approach is cumbersome to reach the optimal solution due to the nature of multi-stage problem. Thus, we propose an equivalent single-stage problem and prove that the three-stage problem can be converted to a compact single-stage problem by properly assigning a weight to each of the three objectives.

Since each reader must be active at least in a frame and the communication schedules repeat the same temporal pattern after one frame, the maximum waiting time for the next service is determined by the frame size. We put the highest priority to minimize the frame size in the cross-layer optimization.

After the minimum frame size is found, our next priority is to find the maximum reader utilization while maintaining the minimum frame size obtained in the first stage. The utilization is defined as the total number of active time slots in a frame. Finally, our last goal is to control the output power so that the minimum power can be assigned to the readers while maintaining the frame size and the utilization obtained from previous stages.

In the first stage, the objective is to find the minimum frame size, ^{*}, during which each reader must be activated at least once. The first stage optimization problem is formulated as follows.

When reader

When reader

We define the utilization of the RFID readers as the total number of active time slots for all the readers. Let ^{*} be the maximum utilization found in the second stage. Note that our second goal is to maximize the utilization while maintaining the minimum frame size obtained in the first stage. Then, the second stage optimization problem is formulated as follows.

The objective in the last stage is to minimize the total output power of the RFID readers while maintaining the optimality found in the first and second stages. The last stage optimization problem is formulated as follows.

The three-stage design sequentially optimizes the RFID system based on the priority of the multiple objectives. This is a bit inconvenient to derive a final solution. For simplicity of the derivation, we show the following key result.

In the first step, we prove that the solution of single-stage problem ^{+}, ^{+}, ^{+}) be a solution to problem ^{+} being the frame size, ^{+} and ^{+} being the corresponding power allocation matrix and the reader schedule matrix, respectively. Note that there may be many optimal solutions to problem ^{+}. Therefore,(^{+}, ^{+}, ^{+}) may be one of them.

Similarly, let (^{*}^{*}, ^{*}, ^{*}^{*}^{*}^{*}^{*}^{*}^{*}^{*}^{+} using contradiction. Suppose ^{*}^{+}. Since both ^{*} and ^{+} are integers, we have

The minimum utilization is identical with the number of readers because each reader should be scheduled at least once in a frame. Thus, the utilization is not less than the number of readers.

When each reader is spatially separated enough, all the readers may be scheduled at a time slot regardless of the number of available channels. Since the maximum frame size is set to the number of readers, the utilization does not exceed the square of the number of readers.

^{*}and

^{*}are equivalent with those of

^{+}and

^{+}.

Apparently, (^{+}, ^{+}, ^{+}, ^{+}, ^{+}) satisfies constraints ^{*}, ^{*}, ^{*}, ^{*}, ^{*}) is an optimal solution to the single-stage problem. Therefore, we should have ^{*} ≤ ^{+}. On the other hand, (^{*}, ^{*}, ^{*}) satisfies constraints ^{*}, ^{*}, ^{*}, ^{*}, ^{*}) is an optimal solution to the single-stage problem. This means that (^{*}, ^{*}, ^{*}) is also a feasible solution to problem ^{+}, ^{+}, ^{+}) is an optimal solution to problem ^{*} ≥ ^{+}. Together with the fact that ^{*} ≤ ^{+}, it can be concluded that ^{*} = ^{+}.

In the second step, we prove that the solution to single-stage problem ^{#}, ^{#}, ^{#}) is an optimal solution to problem ^{*}, and ^{*} > ^{#}. Since both ^{*} and ^{#} are integers, we have
^{*}, ^{#}, ^{#}, ^{#}, ^{#}) satisfies ^{*}, ^{*}, ^{*}, ^{*}, ^{*}) is an optimal solution to the single-stage problem. Therefore, we should have ^{*} ≤ ^{#}. On the other hand, (^{*}, ^{*}, ^{*}, ^{*}) satisfies constraints ^{*}, ^{*}, ^{*}, ^{*}) is also a feasible solution to problem ^{*}, ^{*}, ^{*}, ^{*}) is an optimal solution to problem ^{*} ≥ ^{#}. Therefore, it can be concluded that ^{*} = ^{#}.

In the third step, we prove that the solution of single-stage problem ^{†}, ^{†}, ^{†}) is an optimal solution to problem ^{*} and the negative utilization ^{*}, and ^{*} > ^{†}. Since (^{*}, ^{†}, ^{†}, ^{*}, ^{†}) satisfies ^{*}, ^{*}, ^{*}, ^{*}, ^{*}) is an optimal solution to the single-stage problem. Therefore, we should have ^{*} ≤ ^{†}. On the other hand, (^{*}, ^{*}, ^{*}, ^{*}, ^{*}) satisfies the constraints ^{*}, ^{*}, ^{*}, ^{*}, ^{*}) is also a feasible solution to problem ^{*}, ^{†}, ^{†}, ^{*}, ^{†}) is an optimal solution to the problem ^{*} ≥ ^{†}. Therefore, it can be concluded that ^{*} = ^{†}.

From the preceding three steps, it can be concluded that three-stage optimization problem

Both the three-stage and the single-stage optimization problems are always feasible if the desired interrogation range is acceptable because each reader can be separately scheduled at a time slot even in the worst case. At this time, the frame size and the utilization is identical with the number of readers. For the feasibility, the maximum output power should be large enough to achieve the desired interrogation range. In the next section, we present the numerical results from the software package LINGO [

Consider a passive RFID system as shown in _{max}, is set to 1 watt [

According to theorem 1, the three-stage problem should produce the same optimal solution as that of the single-stage problem. To show that how the three-stage optimization sequentially optimizes the system, we show the results obtained in each stage of the three-stage optimization and compare them with the single-stage solutions. To clearly compare them, we inactivate some readers and find the solutions.

Since the proposed optimization problems should be solved in a centralized manner, the processing time is important for practical use. We simulated the software package LINGO on a PC with 2.13 GHz CPU, 2 GB RAM, Windows XP to solve the problem. It took The time needed by the PC to derive the solution to the single-stage problem and the solution to each stage in the three-stage problem was approximately three seconds and one second, respectively. Therefore, the proposed design can be effectively applied to small- or medium-size RFID systems.

Most anti-collision approaches prevent reader-to-tag and reader-to-reader collisions by distributing operation time among the readers or dynamically assigning frequencies to the readers. The early approaches such as Colorwave, HiQ and LBT cannot fully utilize the potential capacity of RFID systems due to the heuristic nature of these approaches. Though there are several studies, such as Enhanced colorwave, Slotted-LBT, RS-LBT, DFSA, to remedy the shortcomings of the early works and multi-channel approaches using extra control channel, their performance is not satisfactory yet [

In general, the optimization-based approaches develop elaborate models for the reader-to-tag and reader-to-reader collision problems and achieve their respective goals while minimizing collisions. FDFA/SDFA and DIA aim to achieve max-min fair channel allocation among the readers and dynamically allocate communication channels to the readers. DAPC/PPC and RA-GA aim to maximize the overall coverage area of the system while maintaining a desired read rate. To achieve the objective, DAPC/PPC controls the output power of readers and RA-GA uses a combination of FDMA and TDMA. Although such approaches formulate the optimization problems to achieve the goals, they have difficulty in finding optimal solution due to non-convex optimization problem [

As a centralized approach, the proposed optimization design requires information on distances between the readers and computation time to derive the solution. For the formulation of the optimization model, we assume that there is no shadowing or fading, and the signal power at the receiver is attenuated due to path loss with the path attenuation exponent being equal to two. Furthermore, the computation to find solution may not be consistent with mobile RFID networks. Therefore, the solution from the proposed approach is appropriate for stable RFID networks with stationary readers, rather than mobile readers.

In this paper, we surveyed and classified a series of countermeasures to reader collision problem. Then, a novel MILP based cross-layer optimization problem for RFID reader arbitration was proposed, and its interaction with resource scheduling and power control was also derived. To formulate the problem, the reader-to-reader interference model was renovated with consideration of both resource scheduling and power control. Based on the priority of the multiple objectives, to sequentially optimize the system, our cross-layer design basically consists of three stages. Since it is cumbersome to derive the final solution due to the nature of the multi-stage problem, we presented an equivalent single-stage problem and proved the equivalence between the three-stage problem and the single-stage problem. Through the numerical results, we showed the effectiveness of our approach.

The main contribution of this paper is threefold: (i) For a UHF RFID system, we mathematically modeled the system requirements as linear equations and designed the MILP based optimization problem, (ii) we provided insights into how to arbitrate RFID readers with consideration of resource scheduling and power control, and (iii) we explained how to make the three-stage problem into an equivalent single-stage problem with more compact and concise mathematical form by properly assigning a weight to each objective. The proposed design can be easily extended to the analysis of various interferences from RFID readers or other systems such as short-range devices.

A preliminary version of this paper was appeared in IEEE GLOBECOM 2010, December 6–10, Miami, USA. This version additionally includes countermeasures to the reader interference problem, derivation of an equivalent single-stage problem, an extended analysis of the numerical results and a comparative view of anti-collision approaches.

Taxonomy of anti-collision solutions for RFID readers.

RFID reader deployment.

Evaluation Parameters.

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

Operating Frequency | 915 Mhz | |

Channel bandwidth | 500 kHz | |

Target SINR (BER ≤ 10^{−5}) |
11.6 dB | |

Tag threshold level (_{TH}) |
−15 dBm | |

Tag’s power reflection coefficient (_{tag}) |
0.1 | |

Fading coefficient ( |
1 | |

Normalized spectrum power (α_{BW}) - FM0 code |
0.86 | |

Background noise (_{0}) |
−60 dBm | |

Antenna Gain (_{T} = _{R}) |
6 dBi | |

Spectrum mask |
0 dBc | |

−30 dBc | ||

−60 dBc | ||

−65 dBc |

The optimal solutions when d = 5 m.

Frame size | Reader utilization | Energy consumption | Time slot | Scheduled reader (channel number, power(mW)) |
---|---|---|---|---|

5 | 12 | 0.572W | 1st | R1(1, 97), R6(4, 23), R12(2, 97) |

2nd | R4(4, 97), R9(3, 97), R7(1, 23) | |||

3rd | R2(1, 23), R8(4, 23) | |||

4th | R5(4,23), R11(1,23) | |||

5th | R3(4, 23), R10(1, 23) |

The optimal solutions when d = 15 m.

Frame size | Reader utilization | Energy consumption | Time slot | Scheduled reader (channel number, power(mW)) |
---|---|---|---|---|

3 | 12 | 0.408 W | 1st | R1(2, 36), R3(4, 36), R10(3, 39), R11(1, 29) |

2nd | R2(4, 33), R4(3, 35), R7(1, 36), R9(2, 34) | |||

3rd | R5(3, 31), R6(1, 34), R8 (4, 31), R12(2, 34) |

The optimal solutions to the first stage

Frame size | Reader utilization | Energy consumption | Time slot | Scheduled reader (channel number, power(mW)) |
---|---|---|---|---|

3 | 10 | 3.234W | 1st | R1(1, 24), R4(3, 1000), R6(4, 1000) |

2nd | R2(4, 32), R8(3, 40), R10(2, 42), R12(1, 35) | |||

3rd | R3(3, 31), R5(4, 30), R11 (1, 1000) |

The optimal solutions to the second stage

Frame size | Reader utilization | Energy consumption | Time slot | Scheduled reader (channel number, power(mW)) |
---|---|---|---|---|

3 | 12 | 1.825 W | 1st | R4(3, 36), R5(2, 46), R8(1, 31), R11(4, 32) |

2nd | R1(2, 238), R4(1, 999), R6(4, 37), R12(3,62) | |||

3rd | R2(4, 128), R3(1, 128), R8(2, 76), R10(3, 75) |

The optimal solutions to the third stage

Frame size | Reader utilization | Energy consumption | Time slot | Scheduled reader (channel number, power(mW)) |
---|---|---|---|---|

3 | 12 | 0.386 W | 1st | R1(3, 30), R4(4, 27), R6(1, 31), R12(2, 33) |

2nd | R5(3, 31), R8(2, 34), R10(1, 31), R12(4, 27) | |||

3rd | R2(4, 29), R3(2, 41), R11(1, 35), R12(3, 37) |