Design and performance evaluation of RFID counting algorithms under time-correlated channels.

• Other Authors: Deng, Yulin.
• Format: Others
• Language: English; Chinese
• Published: 2012
• Subjects: Radio frequency identification systems > Mathematical models; Signal processing > Mathematical models
• Online Access: http://library.cuhk.edu.hk/record=b5549076; http://repository.lib.cuhk.edu.hk/en/item/cuhk-328448

最近，幾種以Kodialam等人提出的RFID數量估計算法為基礎的新算法相繼出現。這些新算法不僅考慮到RFID讀器和RFID標簽之聞無線信道的不穩定性和不確定性，而且還可以保證其估算具有一定的準確性。然而，這些RFID數量估計算法的設計和性能評估都是基於一個比較簡化的信道模型。根據這個信道模型，封包在RFID讀器和標簽之聞傳送時遺失的概率是符合獨立分布的。然而，一些實證測量研究指出，在一般的室内環境，人的活動和設備的移動對信道的影響是不可忽視的。這些活動可以引起多普勒效應，從而使信號變成時域相關。因此，在真實的無線信道傳輸中，封包的遺失也是時域相關的。由於不同的RFID數量估計算法具體的設計和實現方法各有不同，封包遺失的時域相關性可能對這些RFID數量估計算法造成不同程度的影響。 === 在本論文中，我們評估了三系列的算法在更真實的時域相關的無線信道下的性能。具體來，我們重點研究和分析了時域相關性在哪些方面影響了現有的RFID數量估計算法的準確性。依據描述真實無線信道特性的實驗數據，我們改進了原來的信道模型，使其概括了RFID讀器和標簽之聞向前信道/向後信道的時域相關性。通過觀察這三系列算法在更真實的時域相關的無線信道下的表現，我們分析了造成估算值和真實值之間差距的原因。同時，提出了一些改善數量估計算法準確性的方法，並且通過模擬試驗證明這些改進可以提高算法在真實無線信道下的準確性。 === Recently, several new RFID counting algorithms have been proposed based on the probabilistic counting schemes introduced by Kodialam et. al.. These existing algorithms took into account the unreliable and non-deterministic nature of the radio communication channels between the RFID reader and the tags,and are capable of providing tag-count estimates that satisfy a desired level of accuracy. However, all algorithms were designed and evaluated based on a simplistic packet loss model. It assumes that the loss probability of a packet between the reader and the tag-set follows an independent, identical distribution. No characterizations of possible temporal correlations of the channels were performed. As presented by some empirical measurements, movements of personnel or equipments in a building can generate Doppler effect, which introduces time correlations to the fading signal. Thus, the realistic packet loss caused by the wireless channels is temporally correlated due to the frequent change of the nearby environment. Depending on specific implementation details of each individual algorithm,temporally correlated packet loss might have significant impact on the tag-set cardinality estimation. === In this thesis, we will evaluate the performance of the aforementioned RFID counting algorithms under a more sophisticated time-correlated channel fading model. In particular, we focus on investigating and analyzing how the temporal correlations would influence the accuracy of these existing counting algorithms. Based on the experimental statistics that characterized the realistic indoor channels, we refine the channel model to describe the time-correlation of the forward and backward channel between the RFID reader and the tags. We also modify the model to support implementations of different communication scenarios. Comparisons of the performance of the existing counting schemes under the simplistic uncorrelated packet loss channel model and the refined correlated channel model are conducted. We also propose extensions for these RFID counting schemes to mitigate the estimation inaccuracy generated by the correlated packet loss. === Detailed summary in vernacular field only. === Detailed summary in vernacular field only. === Deng, Yulin. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. === Includes bibliographical references (leaves 99-107). === Abstracts also in Chinese. === Abstract --- p.i === Acknowledgement --- p.vi === Chapter 1 --- Introduction --- p.1 === Chapter 2 --- Background and related work --- p.7 === Chapter 3 --- Modeling time-correlated channels in RFID systems --- p.13 === Chapter 3.1 --- Memoryless channel model --- p.14 === Chapter 3.2 --- Backscattering channel model --- p.16 === Chapter 3.2.1 --- Discussions of channel differences with active tags --- p.18 === Chapter 3.3 --- Difficulties in extending mathematical analysis for Memoryless channel model to time-correlated Backscattering channel model --- p.19 === Chapter 3.4 --- Implementations of Backscattering channel model --- p.20 === Chapter 3.4.1 --- Model the one-way fading channel based on the Clarke and Gans model --- p.20 === Chapter 3.4.2 --- Other implementation aspects of the Twoway Backscattering channel model --- p.25 === Chapter 4 --- Performance evaluation of the First-two-moment implicit approach under time-correlated channels --- p.27 === Chapter 4.1 --- System model --- p.28 === Chapter 4.2 --- Estimator Accuracy --- p.30 === Chapter 4.3 --- Performance evaluation of the First-two-moment implicit RFID counting scheme over time-correlated channels --- p.32 === Chapter 4.3.1 --- Modeling differences --- p.34 === Chapter 4.3.2 --- Coherence time --- p.37 === Chapter 4.3.3 --- Rician fading channel --- p.40 === Chapter 4.3.4 --- Discussions for the case with active tags --- p.42 === Chapter 4.4 --- Correcting estimation errors under time-correlated channels --- p.44 === Chapter 4.4.1 --- Correcting estimation mean --- p.44 === Chapter 4.4.2 --- The impact of time-correlated channels on estimation variance --- p.47 === Chapter 4.5 --- Chapter summary --- p.49 === Chapter 5 --- Performance Evaluation of the Capture-Recapture approach under time-correlated channels --- p.50 === Chapter 5.1 --- System model --- p.51 === Chapter 5.2 --- Different estimation algorithms --- p.53 === Chapter 5.2.1 --- Union-based approach --- p.53 === Chapter 5.2.2 --- The Capture-Recapture approach --- p.55 === Chapter 5.3 --- Performance evaluation of the estimation schemes under time- correlated channels --- p.58 === Chapter 5.3.1 --- Simulation Setup --- p.60 === Chapter 5.3.2 --- Observations and Analysis --- p.65 === Chapter 5.4 --- Extensions of correcting the errors under timecorrelated channels --- p.69 === Chapter 5.5 --- Chapter Summary --- p.72 === Chapter 6 --- Performance evaluation of adaptive RFID counting algorithms under time-correlated channels --- p.74 === Chapter 6.1 --- System Model --- p.75 === Chapter 6.2 --- Adaptive RFID counting Algorithms --- p.76 === Chapter 6.2.1 --- Adaptive Union approach --- p.77 === Chapter 6.2.2 --- Probabilistic Estimation For Lossy Channels (PELOC) --- p.78 === Chapter 6.3 --- Performance evaluation of the adaptive counting algorithms under time-correlated channels --- p.80 === Chapter 6.3.1 --- Simulation Setup --- p.81 === Chapter 6.3.2 --- Observation and analysis --- p.82 === Chapter 6.4 --- Extensions to correct the inaccuracy under timecorrelated channels === Chapter 6.5 --- Chapter Summary --- p.93 === Chapter 7 --- Conclusion and Future work --- p.95 === Bibliography --- p.99