Performance Analysis of Sparse Vector Coding over $\kappa-\mu$ Fading Channel
Jingjing Guo, Xuewan Zhang, Li You, Xiaoming Xu, Di Zhang · 2022
In this paper, the symbol error rate (SER) per-formance of sparse vector coding (SVC) for the short packet transmission over independent and identically distributed (i. i. d.) k - u shadowed fading channels is studied. We firstly analyze the signal to interference plus noise ratio (SINR) of the SVC scheme and show that the corresponding signal to noise ratio (SNR) performance can be improved with the increasing number of resource blocks compared to the conventional baseline, which indicates that the reliability of the system is improved. Then, we derive the simple SER analytical expression over the$\kappa-\mu$fading scenario with low computational complexity. The versatility of the$\kappa-\mu$fading model determines that the other well-known fading distributions and their inclusive ones can be derived as special cases. Simulation results indicate the validness of our derivations, and that the SVC scheme can greatly improve the system reliability with longer spreading sequences.