Simulation Of An Anti Collision Algorithm For Rfid Systems Using A Code Division Multiple Access With Adaptive Interference Cancellation Cdma Aic Approach With Dynamic Processing Gain Gp
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Simulation of an Anti-collision Algorithm for RFID Systems Using a Code Division Multiple Access with Adaptive Interference Cancellation (CDMA/AIC) Approach with Dynamic Processing Gain (Gp)
Radio Frequency Identification (RFID) Systems are modern wireless communication systems that transmit information from a transponder (tag) to a reader. RFID systems are well known because of their contactless feature. However, tag performance is limited by collision problems when multiple tags transmit simultaneously. Due to the collision problem, much research has been developed using anti-collision algorithms to enhance the systems' efficiency, save energy, and ensure the correct transmission of information. Most research has used a Time Division Multiple Access (TDMA) approach with anti-collision ALOHA-type algorithms. The time slots and frames of the tags are manipulated to deal with the collision problem. They work with different ALOHA protocol variants that are always trying to reduce the number of collisions compared to the previous techniques. The most promising of the ALOHA protocol variants is Dynamic Frame Slotted ALOHA (DFSA). In addition, research has been conducted with a Code Division Multiple Access (CDMA) approach, called CDMA with Adaptive Interference Cancellation (CDMA/AIC). The time slots are not used for this anti-collision algorithm; instead, Spread Spectrum (SS) technology and Processing Gain (Gp) were employed. In previous work, the Gp was a fixed value equal to sixty-four (64). In contrast, this research involved a CDMA/AIC approach with a dynamic Gp reached by generating different chip rates. This technique depended on the number of collisions from the previous run to resize the Gp for a subsequent run. CDMA gave the flexibility to use Spread Spectrum. The modulated signal was spread across the channel using orthogonal pseudorandom (PN) codes (generated for each tag) and was demodulated at the reader using the same PN code. The more spread the signal was in the channel, the greater the Gp. The research proved an enhancement in the system's performance compared to the previous work. The system's efficiency enhancement and the anti-collision algorithm were proven using MatLab as the simulation software. No hardware implementation was developed in this research. Both the CDMA and the modified DFSA code were exposed to the same conditions of noise (12, 9, 6 dB SNR), number of tags (20, 60, 80, 100, 150, and 200), number of simulations (1000), and Gp/slots (32, 64, 128, and 256). After the data was collected and processed, the performance of CDMA in noisy scenarios and with a large number of tags was faster and more efficient than DFSA. CDMA presented stability and fast information processing due to its error correction and code spreading features.
Extension of the CDMA/AIC Protocol Through Analysis and Simulation
RFID tags find their application in many areas such as inventory tracking, shipment tracking, vehicle tracking and identification, and animal tracking and identification. Passive RFID tags have been used in most of the applications as they are extremely cost-efficient, and they have a longer lifespan. Previous researchers have developed a CDMA based Adaptive Interference cancellation protocol to increase energy efficiency and reduce multipath effects. In Adaptive Interference Cancellation, we would read the strongest tag and remove its effect and then read the next strongest, remove its effects and so on. In analyzing the protocol, researchers have used a Rayleigh distribution to establish the relative amplitudes for each of the tags to simulate the effects of multipath and shadowing for each tag. The Rayleigh distribution, which models received signal strength with no line-of-sight component, is the worst case for many applications but is not the worst case for assessing the performance of the protocol. This research aims to extend the Adaptive Interference Cancellation algorithm to a broader group of applications. We evaluate the CDMA based Adaptive Interference Cancellation Protocol with different types of distributions such as Rician fading and Lognormal distributions. Rician fading technique has less fluctuations and a series of Rice factors due to reflections and Line of Sight which may reduce the performance of the AIC method. We also aim to use standard lognormal distributions to represent extremely strong Line of Sight.
The Simulation and Analyisis of RFID Anti-collision Algorithms and One Method to Improve BTSA Algorithm
The goals of this research are the analysis and review of current Radio Frequency Identification (RFlD) anti-collision algorithms and the improvement of the binary tree slot ALOHA algorithm. The improved binary tree slot ALOHA (BTSA) algorithm makes the system efficiency greater than do the original algorithms. The new algorithm keeps the system efficiency higher than 40%, when the numbers of tags are greater than 100. When the length of frame is equal to the number of tags in the interrogation area, the system works best. So the key to improving the RFID anti-collision algorithm is finding the number of tags in the interrogation area and then resetting the frame, which makes it as close as the number of tags. The research collects and analyzes the distributions of the collision, when the number of tags falls between 10 and 1000. The research makes those data become a table. After that, the improved BTSA algorithm uses several slots to build an estimation section. The estimate section is the first three slots in the first frame. The improved BTSA algorithm compares the data in the estimate section to the table of distribution, and then finds the number of tags in the interrogation area. After the system gets the number of tags in the interrogation area, the reader resets the length of frame, which keeps the system working in the best situation. After the research analyzes and summarizes the distribution of collisions, it produces the simple protocol to improve the current BTSA algorithm. The first frame is equal to 64. According to the data in the estimate section, if more than two slots in the estimate section are idle slots, the system will reset the frame to 32. If there is any one slot in the three slots that is greater than 5 collisions, the system will reset the frame to 256. According to the distributions of collisions, the improved BTSA algorithm resets the frame. The values of those two points are obtained by data analysis. The simulation result shows that the system efficiency keeps greater than 40%, when the number of tags is between 100 and 1000. When the number of tags is greater than 300 (300, 400, 500) or less then 40, the system will reset the frame. The improved BTSA algorithm successfully keeps the system efficiency higher than 40% when the number of tags is greater than 100. The improved protocol is much easier than current protocols. Using the same method and programs, future research can get the distributions of collisions in different simulation conditions and improve protocols in different systems.