PCNM: A New Platform for Cellular Networks Measurements and Optimization

TL;DR

This paper introduces PCNM, a novel mobile platform that combines real cellular network measurements with theoretical models to enhance network maintenance, extension, and performance evaluation.

Contribution

The paper presents PCNM, a new platform integrating measurement modules, a network measurement protocol, and methods for network extension, bridging real data with theoretical predictions.

Findings

Genetic algorithm effectively reduces node mobility for measurements

Connecting real measurements with models improves network maintenance

PCNM enhances cellular network extension and performance evaluation

Abstract

In this paper, we present PCNM, a new mobile platform for cellular networks measurements. PCNM is based on a set of techniques that tailors theoretical calculations and simulations to the real cellular network environment. It includes: (a) modules that measure different parameters of a base station (BS) such as localization, cells identification, time advance information, reception level and quality, (b) a new protocol that optimizes the task of network measurement by monitoring a set of mobile nodes and finally (c) the ability to extend an existing cellular network by adding new base stations. We evaluate our genetic algorithm used to reduce the nodes mobility and optimize the measurement extraction of N base stations using k mobile sensors (k >= 1). We show how connecting real measurements (using mobile sensors in a collaborative way) to theoretical and prediction methods is of high benefits for cellular networks maintenance, extension and performances evaluation.