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---
language: en
license: mit
tags:
- mobility
- telecommunications
- synthetic-data
- 5g
- network-optimization
datasets:
- mobility-pattern
---
# Mobility Pattern Dataset
## Dataset Description
- **Repository:** [mobility-prediction/dataset](https://huggingface.co/datasets/unifyair/mobility_data)
- **Paper:** N/A
- **Point of Contact:** hello@unifyair.com
### Dataset Summary
This dataset contains synthetic mobility patterns and network performance metrics for 100 users over a 3-day period. The data simulates realistic user movement patterns in a cellular network environment, including various mobility types, signal strengths, and network conditions.
### Supported Tasks and Leaderboards
- **Task 1:** Mobility Pattern Prediction
- **Task 2:** Network Performance Optimization
- **Task 3:** Handover Decision Making
### Languages
English
## Dataset Structure
### Data Instances
Each data instance represents a single measurement point for a user, containing:
- Timestamp
- User ID
- Spatial coordinates (x, y)
- Velocity and heading
- Connected cell information
- Signal strength
- Handover information
- Pattern type
- Network conditions
### Data Fields
- `timestamp`: DateTime - Time of measurement
- `user_id`: String - Unique identifier for each user
- `x`: Float - X-coordinate in meters
- `y`: Float - Y-coordinate in meters
- `velocity`: Float - Movement speed in m/s
- `heading`: Float - Direction of movement in radians
- `connected_cell`: String - ID of the currently connected cell tower
- `signal_strength`: Float - Signal strength in dBm
- `handover_needed`: Boolean - Whether a handover is needed
- `handover_target`: String - Target cell for handover if needed
- `pattern_type`: String - Type of mobility pattern ('commuter', 'random_walk', 'stationary', 'high_mobility')
- `network_load`: Float - Network congestion level (0-1)
- `sinr`: Float - Signal to Interference plus Noise Ratio
- `throughput_mbps`: Float - Network throughput in Mbps
- `device_type`: String - UE capability category
- `handover_latency`: Float - Handover latency in milliseconds
- `handover_success`: Boolean - Whether the handover was successful
### Data Splits
The dataset is provided as a single split containing 3 days of continuous data.
## Dataset Creation
### Curation Rationale
This synthetic dataset was created to facilitate research in mobility prediction and network optimization. It simulates realistic user movement patterns and network conditions that would be encountered in a real cellular network environment.
## Considerations for Using the Data
### Social Impact of Dataset
This dataset can be used to:
- Develop and test mobility prediction algorithms
- Optimize network resource allocation
- Improve handover decision making
- Train machine learning models for network optimization
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