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The Midpoint Formula

In coordinate geometry, determining the central point between two locations is common. This central point, or midpoint, lies exactly halfway along the line segment connecting two points in a two-dimensional space. It has applications in mathematics, physics, engineering, and various planning disciplines.Given two points labeled as A (x1, y1) and B (x2, y2) on a coordinate plane, a straight line segment can be plotted between them. The midpoint, labeled point M, divides this segment into two...
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Related Experiment Video

Updated: Jul 16, 2026

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

A Measurement-Supported Extrapolation Framework for Lowband MIMO Coverage and Capacity Enhancement in Future

Kornél Merkli1,2, Szilvia Nagy2, Péter Prukner1

  • 1Digital Development Center, Széchenyi István University, 9026 Győr, Hungary.

Sensors (Basel, Switzerland)
|July 15, 2026
PubMed
Summary

Future low-frequency wireless networks can improve coverage and capacity using advanced antenna systems (AAS) and multiple-input multiple-output (MIMO) technology. These enhancements aim to boost network performance and reduce reliance on higher frequency bands.

Keywords:
AAS-assisted beamformingcell-edge throughput sustainabilitycoverage and capacity enhancementlowband MIMOlowband active antenna systemsmidband and highband offloading

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Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels
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Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels

Published on: June 2, 2020

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Last Updated: Jul 16, 2026

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Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels
10:00

Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels

Published on: June 2, 2020

Area of Science:

  • Wireless communication engineering
  • Radio frequency engineering
  • Network capacity optimization

Background:

  • Low-frequency mobile bands are crucial for wide-area and penetration-limited wireless coverage.
  • Limited channel bandwidth in low-frequency bands restricts achievable capacity.
  • Existing network infrastructure faces increasing traffic load, necessitating resource optimization.

Purpose of the Study:

  • To present a measurement-supported extrapolation framework for assessing lowband MIMO and AAS enhancements.
  • To evaluate the potential of low-frequency deployments to serve as a robust coverage and capacity support layer.
  • To determine if these enhancements can reduce the load on midband and higher-frequency resources.

Main Methods:

  • Controlled radiated SISO and 2x2 MIMO measurements using a base-station simulator and commercial user equipment.
  • Utilized RSRP, CQI, BLER, MAC-layer, and IP-layer throughput thresholds for a 25 Mbit/s downlink target.
  • Employed the Extended Hata model for coverage estimation and conditional extrapolation.

Main Results:

  • Measured 2x2 MIMO thresholds showed a 43% larger estimated radius at 800 MHz compared to 1800 MHz.
  • A 10 dB AAS beamforming gain scenario indicated a 93% increase in radius.
  • Conditional 4x4 MIMO extrapolations predicted data rates exceeding 100 Mbit/s (10 MHz) and 200 Mbit/s (10 MHz carrier aggregation) under ideal conditions.

Conclusions:

  • Future lowband AAS deployments show significant potential for enhancing wireless network coverage and capacity.
  • Higher-order MIMO and AAS in low-frequency bands can improve overall network performance.
  • Results suggest low-frequency bands can be effectively utilized as a primary support layer for general traffic.