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A Four-Year Retrospective of Mobile Access Bandwidth Evolution:
The Inspiring, The Frustrating, and The Fluctuating

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Table of Contents

Introduction

Data Release

Implementation of Cross-Layer and Cross-Technology Measurement Tool

Introduction

Our study focuses on characterizing mobile access bandwidth in the wild. We work with a major commercial mobile bandwidth testing app to conduct a long-term (2020-2023) and large-scale (involving 4.76M users) measurement study, based on fine-grained sampling diagnostics collected by our cross-layer and cross-technology measurement tool. Below we release our dataset and the source code of the cross-layer and cross-technology measurement tool to benefit the community.

Data Release

Our dataset contains three parts.

1) a four-month (from Aug. 1st to Nov. 30th) fine-grained dataset collected by us in 2021,

2) another four-month (from Feb. 15th to Jun. 15th) fine-grained dataset collected by us in 2023,

3) a four-year coarse-grained dataset (collected by BTS-APP operation team).

The first part was released at here. For the second part, currently we have released a portion of the representative sample data (with proper anonymization) belonging to the former dataset for references, including the fine-grained collected data of 5K tests in 4G, 5G, and WiFi 4, 5, 6 access technologies (1K tests each). These data are organized in 4G.csv, 5G.csv, wifi4.csv, wifi5.csv, and wifi6.csv, respectively (for detailed data, please click here). For each CSV file, we list the specific information coupled with the regarding description as follows. As to the last part, we are still dicussing with the authority to what extend can it be released.

4G.csv

Column Name Description
user_uid Unique ID generated to identify a user (cannot be related to the user’s true indentity)
brand Mobile device brand
model Mobile device model
network_type Network type
os_version Android version
user_isp_id ISP id
user_region_id Region (province) of a user
user_city_id City of a user
bandwidth_Mbps Bandwidth testing result in Mbps
cell_asuLevel LTE signal strength in ASU value
cell_dbm LTE signal strength in dBm
cell_level Abstract level value for the overall signal quality
cell_mcc 3-digit mobile country code
cell_mnc 2 or 3-digit mobile network code
cell_mobileNetworkOperator 5 or 6-digit code (MCC+MNC) for mobile network operator
cell_rssi Received signal strength indication (RSSI) in dBm
cell_timingAdvance Timing advance value for LTE
cell_bands Bands of the LTE connection
cell_bandwidth Cell bandwidth in kHz
cell_ci 28-bit cell identity code
cell_earfcn 18-bit absolute radio frequency channel node
cell_tac 16-bit Tracking Area Code
cell_rsrp Reference signal received power in dBm
cell_rsrq Reference signal received quality
cell_rssnr Reference signal signal-to-noise ratio

5G.csv

Information Description
user_uid Unique ID generated to identify a user (cannot be related to the user’s true indentity)
brand Mobile device brand
model Mobile device model
network_type Network type
os_version Android version
user_isp_id ISP id
user_region_id Region (province) of a user
user_city_id City of a user
bandwidth_Mbps Bandwidth testing result in Mbps
cell_asuLevel LTE signal strength in ASU value
cell_dbm LTE signal strength in dBm
cell_level Abstract level value for the overall signal quality
cell_mcc 3-digit mobile country code
cell_mnc 2 or 3-digit mobile network code
cell_bands Bands of the LTE connection
cell_tac 16-bit Tracking Area Code
cell_nrarfcn New radio absolute radio frequency channel number
cell_csiRsrp CSI reference signal received power
cell_csiRsrq CSI reference signal received quality
cell_ssRsrp SS reference signal received power
cell_ssRsrq SS reference signal received quality
cell_ssSinr SS signal-to-noise and interference ratio
cell_isNrAvailable the identifier of 5G SA mode (joint use with cell_isEndcAvailable)
cell_isEndcAvailable the identifier of 5G SA mode (joint use with cell_isNrAvailable)

wifi4/wifi5/wifi6.csv

Information Description
user_uid Unique ID of a user (cannot be related to the user’s true indentity)
brand Mobile device brand
model Mobile device model
network_type Network type
os_version Android version
user_isp_id ISP id
user_region_id Region (province) of a user
user_city_id City of a user
bandwidth_Mbps Bandwidth testing result in Mbps
wifi_rssi The received signal strength indicator of the current 802.11 network in dBm
wifi_linkSpeed Current link speed
wifi_hiddenSSID Whether this network does not broadcast its SSID
wifi_frequency Current WiFi frequency in MHz
wifi_rxLinkSpeedMbps Current receive link speed in Mbps
wifi_txLinkSpeedMbps Current transmit link speed in Mbps
wifi_maxSupportedRxLinkSpeedMbps Maximum supported receive link speed in Mbps
wifi_maxSupportedTxLinkSpeedMbps Maximum supported transmit link speed in Mbps
wifi_wifiStandard Connection Wi-Fi standard
wifi_dualWiFi the identifier of whether the WiFi AP adopts dual WiFi acceleration

Implementation of Cross-Layer and Cross-Technology Measurement Tool

We have released the project of our cross-layer and cross-technology (CLCT) measurement tool here. Note that this project can be directly compiled and run using the Android Studio platform with the support of Java SE Development Kit 8.