A Prospective Look on Optimization Methods For RFID Systems: Requirements, Challenges and Implementation Aspects

Abstract

The radio frequency identification (RFID) is a configuration of wireless communication that uses radio frequency (RF) waves for following up and recognizing data. The RFID system includes important parts as antenna and integrated circuit (IC) for radiating and storing data, respectively. Hence, high performance antenna and IC circuits must be designed for assembling the energy from the radio waves and feeding the RFID chip. One of the important circuit/block in the IC part is the amplifier where the antenna is sensing the radiated output power. For this case, it is substantially important to design high performance antenna and amplifier where the specifications of these circuits must be optimized in a professional way. In this paper, we collect the recently published optimization methods that are employed for designing antenna and RF/analog-based amplifiers. Any researcher by referring to these algorithms can access and find the solutions for their problems, straightforwardly.

Keywords

• Amplifier
• antenna
• radio frequency identification (RFID)
• radio frequency (RF)
• optimization methods
• power amplifier (PA).

References

1. [1] A. Tzitzis, A. Raptopoulos Chatzistefanou, T. V. Yioultsis, and A. G. Dimitriou, “A real-time multi-antenna sar-based method for 3d localization of rfid tags by a moving robot,” IEEE Journal of Radio Frequency Identification, 2021.
2. [2] D. Le, S. Ahmed, L. Ukkonen, and T. Bjorninen, “A small all- ¨ corners-truncated circularly polarized microstrip patch antenna on textile substrate for wearable passive uhf rfid tags,” IEEE Journal of Radio Frequency Identification, 2021.
3. [3] Z. Liu, Z. Fu, T. Li, I. White, R. Penty, and M. Crisp, “An isar-sar based localization method using passive uhf rfid system with mobile robotic platform,” in 2020 IEEE International Conference on RFID (RFID), 2020.
4. [4] S. Qi, Y. Lu, W. Wei, and X. Chen, “Efficient data access control with fine-grained data protection in cloud-assisted iiot,” IEEE Internet of Things Journal, 2021.
5. [5] R. Seyfert, M. Maibaum, and S. Kroll, “Rfid data storage and their key role in exploitation of metallic second life materials,” IEEE Journal of Radio Frequency Identification, 2022.
6. [6] J. Yu, P. Zhang, L. Chen, J. Liu, R. Zhang, K. Wang, and J. An, “Stabilizing frame slotted aloha-based iot systems: A geometric ergodicity perspective,” IEEE Journal on Selected Areas in Communications, 2021.
7. [7] Y. Zhang, K. Liu, Y. Ma, J. Wang, and S. Li, “Vehicular localization with using china electronic license plate system,” IEEE Journal of Radio Frequency Identification, 2020.
8. [8] P. Avaltroni, S. Nappi, and G. Marrocco, “Antennifying orthopedic boneplate fixtures for the wireless monitoring of local deep infections,” IEEE Sensors Journal, 2021.

9. [9] M. Boada, A. Lazaro, R. Villarino, E. Gil-Dolcet, and D. Girbau, “Battery-less nfc bicycle tire pressure sensor based on a force-sensing resistor,” IEEE Access, 2021.
10. [10] Q. Liu, Y. Yu, D.-W. Wang, and G. Wang, “An rfid-based wireless multistate controller with quasi-isotropic radiation pattern for remote control applications,” IEEE Antennas and Wireless Propagation Letters, 2021.
11. [11] S. Khan, W.-K. Lee, and S. O. Hwang, “A flexible gimli hardware implementation in fpga and its application to rfid authentication protocols,” IEEE Access, vol. 9, 2021.
12. [12] D. Inserra and G. Wen, “Dual orthogonal port stacked patch antenna with vertical pins for simultaneous transmit and receive application,” IEEE Transactions on Antennas and Propagation, vol. 69, 2021.
13. [13] W. Sabat, D. Klepacki, K. Kamuda, and K. Kuryło, “Analysis of electromagnetic field distribution generated in an semi-anechoic chamber in aspect of rf harvesters testing,” IEEE Access, vol. 9, 2021.
14. [14] Z. Wang, M. Xu, N. Ye, F. Xiao, R. Wang, and H. Huang, “Computer vision-assisted 3d object localization via cots rfid devices and a monocular camera,” IEEE Transactions on Mobile Computing, vol. 20, no. 3, 2021.
15. [15] A. DiNatale, A. DiCarlofelice, and E. DiGiampaolo, “A crack mouth opening displacement gauge made with passive uhf rfid technology,” IEEE Sensors Journal, vol. 22, no. 1, 2022.
16. [16] M. Kokkonen, S. Myllymaki, J. Putaala, and H. Jantunen, “A resonator ¨ enhanced uhf rfid antenna cable for inventory and warehouse applications,” IEEE Journal of Radio Frequency Identification, 2022.
17. [17] A. Adeyeye, C. Lynch, A. Eid, J. Hester, and M. Tentzeris, “5.8-ghz low-power tunnel-diode-based two-way repeater for non-line-of-sight interrogation of rfids and wireless sensor networks,” IEEE Microwave and Wireless Components Letters, 2021.
18. [18] M. Kim, U. Ha, Y. Lee, K. Lee, and H.-J. Yoo, “A 82nw chaotic-map true random number generator based on sub-ranging sar adc,” in ESSCIRC Conference 2016: 42nd European Solid-State Circuits Conference, 2016.
19. [19] V.-H. Duong, N. X. Hieu, H.-S. Lee, and J.-W. Lee, “A batteryassisted passive epc gen-2 rfid sensor tag ic with efficient battery power management and rf energy harvesting,” IEEE Transactions on Industrial Electronics, 2016.
20. [20] M. Nariman, F. Shirinfar, A. Papio Toda, S. Pamarti, A. Rofougaran, ´ and F. De Flaviis, “A compact 60-ghz wireless power transfer system,” IEEE Transactions on Microwave Theory and Techniques, 2016. [21] B. Lee, M. Kiani, and M. Ghovanloo, “A smart wirelessly powered homecage for long-term high-throughput behavioral experiments,” IEEE Sensors Journal, 2015.
21. [22] J. Lorenzo, A. Lazaro, R. Villarino, and D. Girbau, “Active backscatter transponder for fmcw radar applications,” IEEE Antennas and Wireless Propagation Letters, 2015.
22. [23] S. Khaledian, F. Farzami, H. Soury, B. Smida, and D. Erricolo, “Active two-way backscatter modulation: An analytical study,” IEEE Transactions on Wireless Communications, 2019.
23. [24] M.-S. Kim, S.-C. Jung, J. Jeong, H. Kim, M. Seo, J. Ham, C.-S. Park, and Y. Yang, “Adaptive tx leakage canceler for the uhf rfid reader front end using a direct leaky coupling method,” IEEE Transactions on Industrial Electronics, vol. 61, 2014.
24. [25] A. Bucciarelli, E. Olivetti, A. Adami, and L. Lorenzelli, “Design of experiment rational optimization of an inkjet deposition of silver on kapton,” IEEE Sensors Journal, 2021.
25. [26] N. Cordeschi, F. De Rango, and M. Tropea, “Exploiting an optimal delay-collision tradeoff in csma-based high-dense wireless systems,” IEEE/ACM Transactions on Networking, 2021.
26. [27] F. Bernardini, A. Buffi, A. Motroni, P. Nepa, B. Tellini, P. Tripicchio, and M. Unetti, “Particle swarm optimization in sar-based method enabling real-time 3d positioning of uhf-rfid tags,” IEEE Journal of Radio Frequency Identification, 2020.
27. [28] B.-Q. Zhao, H.-M. Wang, and P. Liu, “Safeguarding rfid wireless communication against proactive eavesdropping,” IEEE Internet of Things Journal, 2020.
28. [29] X. Zhang, H.-X. Li, and H. S.-H. Chung, “Setup-independent uhf rfid sensing technique using multidimensional differential measurement,” IEEE Internet of Things Journal, 2021.
29. [30] A. Tzitzis, S. Megalou, S. Siachalou, T. G. Emmanouil, A. Filotheou, T. V. Yioultsis, and A. G. Dimitriou, “Trajectory planning of a moving robot empowers 3d localization of rfid tags with a single antenna,” IEEE Journal of Radio Frequency Identification, 2020.
30. [31] H. Liu, Q. Chen, N. Pan, Y. Sun, Y. An, and D. Pan, “Uav stocktaking task-planning for industrial warehouses based on the improved hybrid differential evolution algorithm,” IEEE Transactions on Industrial Informatics, 2022.
31. [32] J. Xu, H. Sato, M. Motoyoshi, N. Suematsu, K. Yasui, and Q. Chen, “A low-loss and compact uhf rfid tag antenna for implanted denture,” IEEE Journal of Radio Frequency Identification,2022.
32. [33] “The radio frequency identification system architecture,” http://http:// smartt-tags.com/#what-is-rfid?, accessed: 2022-01-01.
33. [34] C. Bredendiek, D. A. Funke, J. Schopfel, V. Kloubert, B. Welp, K. Aufin- ¨ ger, and N. Pohl, “A 61-ghz sige transceiver frontend for energy and data transmission of passive rfid single-chip tags with integrated antennas,” IEEE Journal of Solid-State Circuits, 2018.
34. [35] J. Zhu, C. Jin, and H. Liu, “Mutual inductance modeling of two coaxial solenoid antennas with large ferrite core for underground rfid applications,” IEEE Transactions on Magnetics, 2021.
35. [36] G. M. Bianco, S. Amendola, and G. Marrocco, “Near-field constrained design for self-tuning uhf-rfid antennas,” IEEE Transactions on Antennas and Propagation, 2020.
36. [37] S. Ahmed, D. Le, L. Sydanheimo, L. Ukkonen, and T. Bj ¨ orninen, ¨ “Wearable metasurface-enabled quasi-yagi antenna for uhf rfid reader with end-fire radiation along the forearm,” IEEE Access, 2021.
37. [38] Y. Chen, C. Hua, and Z. Shen, “Circularly polarized uhf rfid tag antenna for wireless sensing of complex permittivity of liquids,” IEEE Sensors Journal, 2021.
38. [39] S. Khaledian, F. Farzami, D. Erricolo, and B. Smida, “A full-duplex bidirectional amplifier with low dc power consumption using tunnel diodes,” IEEE Microwave and Wireless Components Letters, 2017.
39. [40] D. Zouache, Y. Ould Arby, F. Nouioua, and F. Ben Abdelaziz, “Multi-objective chicken swarm optimization: A novel algorithm for solving multi-objective optimization problems,” Computers Industrial Engineering, 2019.
40. [41] W. Shi, W. Wang, Y. Yu, S. Zhang, Y. Cao, S. Yan, and J. Gao, “Optimal deployment of phased array antennas for rfid network planning based on an improved chicken swarm optimization,” IEEE Internet of Things Journal, 2021.
41. [42] S. Cheng, Y. Shi, and Q. Qin, Population Diversity of Particle Swarm Optimization Algorithm on Solving Single and MultiObjective Problems, ser. Handbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems.
42. [43] B. Cao, Y. Gu, Z. Lv, S. Yang, J. Zhao, and Y. Li, “Rfid reader anticollision based on distributed parallel particle swarm optimization,” IEEE Internet of Things Journal,, 2021.
43. [44] F. Passos, E. Roca, J. Sieiro, R. Fiorelli, R. Castro-Lopez, J. M. L ´ opez- ´ Villegas, and F. V. Fernandez, “A multilevel bottom-up optimization ´ methodology for the automated synthesis of rf systems,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020.
44. [45] L. Kouhalvandi, O. Ceylan, and S. Ozoguz, “Automated matching network modeling and optimization for power amplifier designs,” in 2019 11th International Conference on Electrical and Electronics Engineering (ELECO), 2019.
45. [46] F. Mir, L. Kouhalvandi, L. Matekovits, and E. O. Gunes, “Electromagnetic bottom-up optimization for automated antenna designs,” in 2020 IEEE Asia-Pacific Microwave Conference (APMC), 2020.
46. [47] F. Mir, L. Matekovits, L. Kouhalvandi, and E. O. Gunes, “Optimization for wideband linear array antenna through bottom-up method,” in 2020 IEEE International Conference on Electrical Engineering and Photonics , 2020.
47. [48] R. Gonzalez-Echevarr ´ ´ıa, E. Roca, R. Castro-Lopez, F. V. Fern ´ andez, ´ J. Sieiro, J. M. Lopez-Villegas, and N. Vidal, “An automated design ´ methodology of rf circuits by using pareto-optimal fronts of emsimulated inductors,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2017.
48. [49] M. H. Bakr, J. W. Bandler, K. Madsen, and J. Søndergaard, “An introduction to the space mapping technique,” Optimization and Engineering, Dec 2001.
49. [50] S. Fidler, M. Boben, and A. Leonardis, “A bottom-up and top-down optimization framework for learning a compositional hierarchy of object classes,” in 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2009.
50. [51] L. Kouhalvandi, O. Ceylan, and S. Ozoguz, “Automated top-down pruning optimization approach in RF power amplifier designs,” Analog Integrated Circuits and Signal Processing, Mar 2021.
51. [52] L. Kouhalvandi, L. Matekovits, and I. Peter, “Deep learning assisted automatic methodology for implanted mimo antenna designs on large ground plane,” Electronics, 2022.
52. [53] S. M. Aslam and S. Samreen, “Gesture recognition algorithm for visually blind touch interaction optimization using crow search method,” IEEE Access, 2020.
53. [54] H. Yin, J. Zhai, P. Chen, and C. Yu, “Directed graph navigated digital predistortion of mmwave power amplifiers for 6g hopping applications,” IEEE Microwave and Wireless Components Letters, 2021.
54. [55] N. L. K. Nguyen, N. S. Killeen, D. P. Nguyen, A. N. Stameroff, and A.-V. Pham, “A wideband gain-enhancement technique for distributed amplifiers,” IEEE Transactions on Microwave Theory and Techniques, 2020.
55. [56] L. Kouhalvandi, M. Pirola, and S. Ozoguz, “Automated two-step power amplifier design with pre-constructed artificial neural network,” in 2020 43rd International Conference on Telecommunications and Signal Processing , 2020.
56. [57] S. Yarman, “Design of ultra wideband power transfer networks,” New York, NY, USA: Wiley, 2010.
57. [58] F. Mir, L. Kouhalvandi, L. Matekovits, and E. O. Gunes, “Automated optimization for broadband flat-gain antenna designs with artificial neural network,” IET Microwaves, Antennas & Propagation, 2021.
58. [59] J. Nan, H. Xie, M. Gao, Y. Song, and W. Yang, “Design of uwb antenna based on improved deep belief network and extreme learning machine surrogate models,” IEEE Access, 2021.
59. [60] J. Gao, Y. Tian, and X. Chen, “Antenna optimization based on cotraining algorithm of gaussian process and support vector machine,” IEEE Access, vol. 8, pp. 211 380–211 390, 2020.
60. [61] W. Su, J. Zhu, H. Liao, and M. M. Tentzeris, “Wearable antennas for cross-body communication and human activity recognition,” IEEE Access,2020.
61. [62] L. Kouhalvandi, O. Ceylan, and S. Ozoguz, “Automated rf power amplifier optimization and design: From lumped elements to distributed elements,” in 2019 27th Telecommunications Forum , 2019.
62. [63] J. Jin, C. Zhang, F. Feng, W. Na, J. Ma, and Q. Zhang, “Deep neural network technique for high-dimensional microwave modeling and applications to parameter extraction of microwave filters,” IEEE Transactions on Microwave Theory and Techniques, 2019.
63. [64] Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, vol. 521, pp. 436–44, 05 2015.
64. [65] L. Li, X. Yu, Z. Liu, Z. Zhao, K. Zhang, and S. Zhou, “Rfid dynamic performance measurement system embedded in multiscale deep learning,” IEEE Transactions on Instrumentation and Measurement, , 2021.
65. [66] L. Kouhalvandi, O. Ceylan, and S. Ozoguz, “Automated deep neural learning-based optimization for high performance high power amplifier designs,” IEEE Transactions on Circuits and Systems I: Regular Papers, 2020.
66. [67] ——, “Multi-objective efficiency and phase distortion optimizations for automated design of power amplifiers through deep neural networks,” in 2021 IEEE MTT-S International Microwave Symposium (IMS), 2021.
67. [68] P. Yan, S. Choudhury, and R. Wei, “A machine learning auxiliary approach for the distributed dense rfid readers arrangement algorithm,” IEEE Access, 2020.
68. [69] C. Peng, H. Jiang, and L. Qu, “Deep convolutional neural network for passive rfid tag localization via joint rssi and pdoa fingerprint features,” IEEE Access, 2021.
69. [70] X. Li, Y. Zhang, I. Marsic, A. Sarcevic, and R. Burd, “Deep learning for rfid-based activity recognition,” vol. 2016, 11 2016.
70. [71]Hussein M. , Özyurt F. A New Technique for Sentiment Analysis System Based on Deep Learning Using Chi-Square Feature Selection Methods. Balkan Journal of Electrical and Computer Engineering. 2021.