# Predicting a User's Next Cell With Supervised Learning Based on Channel States

arXiv: https://arxiv.org/abs/1305.2776 · HTML: https://mlsanity.com/paper/1305.2776/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 May 2013.

## Built on by (most cited first, 1 of 1)

- [Data-Driven Cellular Network Selector for Vehicle Teleoperations](https://mlsanity.com/paper/2410.19791/) (2024)

## Abstract (arXiv)

Knowing a user's next cell allows more efficient resource allocation and enables new location-aware services. To anticipate the cell a user will hand-over to, we introduce a new machine learning based prediction system. Therein, we formulate the prediction as a classification problem based on information that is readily available in cellular networks. Using only Channel State Information (CSI) and handover history, we perform classification by embedding Support Vector Machines (SVMs) into an efficient pre-processing structure. Simulation results from a Manhattan Grid scenario and from a realistic radio map of downtown Frankfurt show that our system provides timely prediction at high accuracy.