260418 Enhance publishing|Reproduction Code for "Iterative Parameter Estimation Method for Energy Detection Threshold in Ambient Backscatter"

In environmental backscatter communication (AmBC), the reader uses an energy detector to recover the tag signal, and the required parameters for its detection threshold are determined by the average power of the received signal containing unknown tag symbols "1" and "0". The existing parameter estimation methods assume that the label sends symbols "1" and "0" with equal probability, so the sorted received signal sample power is directly divided equally.

However, the number of symbols sent by the tag is limited, so the number of symbols "1" and "0" is not strictly equal, and equal division can lead to sample misclassification, causing the detection threshold to deviate from the optimal value. To this end, a detection threshold parameter estimation method based on iterative updates has been designed. The core idea is to use existing decision results to re group the sorted samples and iteratively update the threshold parameters to achieve gradual correction of the detection threshold.

To verify the effectiveness of the proposed method, simulations were conducted under three typical RF source conditions: complex Gaussian source, PSK source, and QAM source. The simulation results show that this method can effectively reduce the threshold parameter estimation bias. Compared with existing sorting and grouping parameter estimation methods, it only requires one iteration update, and its detection error rate can achieve performance improvements of about 0.1, 1.5, and 1.3 orders of magnitude under complex Gaussian source, PSK source, and QAM source.