Decoding complexity analyses of PEG-based methods with the improved hybrid iterative/Gaussian elimination decoding algorithm
Reem Ibrahim Alkanhel, Marcel Ambroze · 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA) · 2017
This paper focuses on analysing the operational complexity of decoding the progressive-edge-growth-based (PEG-based) method for the extended grouping of radio frequency identification (RFID) tags using the improved hybrid iterative/Gaussian elimination decoding algorithm. In addition, the joint use of two decoding components is adapted based on the missing amounts of RFID tags and group sizes in order to avoid iterative decoding when the missing amounts is larger than a threshold and thus to save more decoding time. Various simulations have been carried out to analyse and evaluate the decoding complexity as well as the impact of the threshold value on decoding time. Simulation results are presented, demonstrating that the improved hybrid decoding algorithm achieves low decoding complexity and thus decoding time when compared to the full Gaussian elimination decoding algorithm.