Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This extensive mathematical model developed for linear chipless RFID systems in clutter scenarios holds the potential to greatly assist researchers in their exploration of RCS-based tags. By relying solely on simulations, this model provides a tool to effectively analyze and understand RCS-based tags, ultimately simplifying the process of generating more authentic tag designs. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.
We discuss the channel capacity of multiantenna systems with the Nakagami fading channel. Analytic expressions for the ergodic channel capacity or its lower bound are given for SISO, SIMO, and MISO cases. Formulae for the outage probability of the capacity are presented. It is shown that the channel capacity could be increased logarithmically with the number of receive antennas for SIMO case; while employing 3–5 transmit antennas (irrespective of all other parameters considered herein) can approach the best advantage of the multiple transmit antenna systems as far as channel capacity is concerned for MISO case. We have shown that for a given SNR, the outage probability decreases considerably with the number of receive antennas for SIMO case, while for MISO case, the upper bound of the outage probability decreases with the number of transmit antennas when the transmission rate is lower than some value, but increases instead when the transmission rate is higher than another value. A critical transmission rate is identified.
Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.
This introduction presents an overview of key concepts discussed in this book, which addresses signal processing issues in radio frequency identification (RFID). RFID is a technique to achieve object identification by using radio systems. It is a contactless, usually short distance, wireless data transmission and reception technique for identification of objects. An RFID system consists of two components, namely tag and reader. The book reviews both fundamentals of RFID and the state-of-the-art research results in signal processing for RFID. For the former, it discusses the operating principles, modulation schemes and channel models of RFID. For the latter, the book highlights the following research fields: space-time coding for RFID, blind signal processing for RFID, anti-collision of multiple RFID tags and localization with RFID. Some concrete examples on the analysis of transmission efficiency of tree-splitting algorithms are illustrated in detail before presenting general results.
This chapter contains sections titled: Introduction UWB Relay Systems with SISO at Source and Destination UWB Relay Systems with MIMO at Source and Destination Opportunistic Relaying for UWB Systems Summary Appendix 7.A Derivations of cdfs and pdfs of J and J' Appendix 7.B Derivation of Equation (7.33) Appendix 7.C The pdf of the End-to-End SNR per Bit for the DCF Relay System
In this paper, the performance of various ultra-wideband (UWB) multiple-input multiple-output (MIMO) relay systems is evaluated for the first time based on UWB channel measurements. In particular, the measurement results for UWB relay channels in line-of-sight as well as non-line-of-sight indoor environments are presented. The average bit error rates of dual-hop MIMO relay systems and cooperative MIMO relay systems are examined and compared in the measured channels.
This paper discusses the separation of signals in multiple-tag radio frequency identification (RFID) systems. First, a model for the RFID system in both single and multiple tag environments is presented. Then, an analytical constant modulus algorithm (ACMA) for the blind source separation problem is reviewed. An alternative approach to the traditional ACMA using joint diagonalization is considered. Finally, both the ACMAs are applied to the multiple-tag RFID environment and performance of the system is studied. Simulations are carried out for 4-QAM and 16-QAM modulations at tag and analyses of the simulation results reveal that the ACMA with joint diagonalization takes lesser CPU time to execute compared to the traditional ACMA, but with higher average modulus error (AME). The variation of system performance with the number of measurements, SNR (signal to noise ratio), number of tags and number of antennas at the reader is also studied. Based on these, some design guidelines are presented. Interestingly both the ACMA algorithms work for the 16-QAM case and yield trends similar to those of 8-PSK and 4-QAM.
Accurate tag collision estimation is very important for ALOHA-based anti-collision protocol for passive RFID system. In this paper, a method of pulse detection is proposed to detect the collision and estimate the population of tags accurately by slightly modifying the frame structure in ISO 18000-6 type C specification. And then improved slotted ALOHA-based anti-collision protocol based on pulse detection is proposed. In our protocol, a re-query process may be introduced after reader receiving the replies of tags at the end of one slot to access the collision tags quickly. Simulations results show the proposed protocol achieves a system throughput of 0.48. It is an improvement compared with the performance of existing ALOHA-based protocol, and it is simple and low cost for implementation.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
