Active Users Detection Based on Orthogonal Least Squares

Abstract

The Internet of Things (IoT) is the network of numerous physical users that are able to gather and share electronic information with each other. One of the main challenges of IoT is to detect the active users. We first employ the orthogonal least squares (OLS) algorithm to detect the active users. We then prove that under some conditions on the noise vector v, OLS can successfully detect all the K active users from the linear model y = Hx + v in at most K iterations provided that H satisfies the restricted isometry property with δ K+1 < 1/ √ K + 1. Numerical tests are also performed to show the efficiency and effectiveness of the OLS algorithm. INDEX TERMS Internet of Things (IoT), Active users detection, Orthogonal least squares (OLS), Missed detection probability, False alarm detection probability.