Law enforcement and position locating in LTE network (status and challenges)

Abstract

Since the advent of cellular networks represented by the first-generation GSM to the current generations (4G, 5G) represented by the LTE network. This brought about a qualitative revolution in cellular networks in terms of quality, speed, and efficiency. The emergence of cellular networks accompanied by the need to locate the user for commercial and marketing purposes, therefore emerge need for the concept of location-based services (LBS). However, with the increased reliance on cellular networks by users, there appeared a second trend to locate the user for security purposes and emergency. This was the first system established in the United States of America, called federal communication commission (FCC) 911. Position locating has also penetrated the military, security, and police investigations fields to locate criminals. Therefore, we review the methods of determining location in LTE networks. We evaluate each method and identify its weaknesses. In addition, we determine the most appropriate method for law enforcement. Based on the evaluation that showed the most effective way to determine the location used by law enforcement authorities is the radio frequency (RF) fingerprint. Then employment of artificial intelligence (AI)/machine learning (ML) to obtain an optimal method.