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Advanced Chipless RFID by Chamath Divarathne, Mohammad Zomorrodi, Nemai Chandra Karmakar

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CHAPTER 11COMPUTATIONALLY FEASIBLE TAG DETECTION TECHNIQUES

11.1 INTRODUCTION

Maximum likelihood (ML)-based detectors generally produce better tag detection performances as they utilize all information available, prior to making a decision. However, one of the main drawbacks of ML detectors is its higher computation complexity. In the proposed tag detection techniques, they compare the received signal with all possible tag combinations and select the one with the highest probability as the detected tag. If a radio frequency identification (RFID) tag has c11-math-0001 bits, they compare the received signal with all c11-math-0002 tag combinations to calculate individual probabilities. In the case of tags being used to identify the object category not the object itself, the number of bits required in a tag can be small. In such cases, direct application of the tag detection techniques presented in Chapter 10 may be feasible. However, when the number of bits in the tag is large, computation complexity is increasing exponentially, hence utilizing the tag detection techniques presented in Chapter 10 may not be feasible. Higher computation complexity brings up two main challenges. First, the RFID reader needs higher computation capability to evaluate the likelihood expressions derived in Chapter 10. The second ...

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