Header detection for massive IoT wireless networks over Rayleigh fading channels

Abstract

In this paper, we propose header detection technique for massive internet of things (IoT) networks over Rayleigh fading channels. We consider coded random access (CRA) as a multiple access scheme for IoT to keep low computational complexity of detection, where header detection is of significant important. We perform header detection by computing cross correlation using Hadamard codes. Hadamard codes are chosen because of its simplicity to be generated, where the value of the matrix component is only ±1. To avoid data rate loss due to bits allocation to header, the length of the header should be kept small. We use Hadamard codes with size of 128×128 as a header for packets suffering from Rayleigh fading channels. We also use capture effect algorithm to improve detection performances when multiple IoT devices are transmitting at the same time-slot. Although the algorithms is simple, we found that header detection using Hadamard codes for massive IoT connections over Rayleigh fading channels is still providing high accuracy, which is suitable for future massive IoT wireless networks.