5G NR Channel Model

Usage no npm install needed!

<script type="module">
  import gChannel from 'https://cdn.skypack.dev/5g-channel';



5G NR channel model: currently only implemented pathloss (7.4.1) and LOS probability (7.4.2)


3GPP TR 38.901 V16: Study on channel model for frequencies from 0.5 to 100 GHz, Chapter 7 Channel model(s) for 0.5-100 GHz


Option 1: import all functions

const g5_channel = require('5g-channel');

g5_channel.pathloss.pathloss_rma_los(2, 400); // 2 GHz, 400m distance


Option 2: selective import

const { pathloss_rma_los } = require('5g-channel/pathloss');

pathloss_rma_los(2, 400)

Includes: pathloss and line-of-sight probability for the following scenarios

Rural Macro

  • LOS probability: pr_los_rma(d_2d_out)
  • Pathloss:
    • LOS: pathloss_rma_los(fc, d_2D, h_BS, h_UT, W, h)
    • NLOS: pathloss_rma_nlos(fc, d_2D, h_BS, h_UT, W, h)
    • Average: pathloss_rma(fc, d_2D, h_BS, h_UT, W, h)

Urban Macro

  • LOS probability: pr_los_uma(d_2d_out, h_UT)
  • Pathloss:
    • LOS: pathloss_uma_los(fc, d_2D, h_BS, h_UT, h_E)
    • NLOS: pathloss_uma_nlos(fc, d_2D, h_BS, h_UT, h_E, option)
    • Average: pathloss_uma(fc, d_2D, h_BS, h_UT, h_E, option)

Urban Micro-streen canyon

  • LOS probability: pr_los_umi(d_2d_out)
  • Pathloss:
    • LOS: pathloss_umi_los(fc, d_2D, h_BS, h_UT)
    • NLOS: pathloss_umi_nlos(fc, d_2D, h_BS, h_UT, option)
    • Average: pathloss_umi(fc, d_2D, h_BS, h_UT, option)

Indoor-office (InH)

  • LOS probability:
    • mixed office: pr_los_inh_mixed(d_2d_in)
    • open office: LOS probability: pr_los_inh_open(d_2d_in)
    • both types: LOS probability: pr_los_inh(type, d_2d_in)
  • Pathloss:
    • LOS: pathloss_inh_los(fc, d_3D)
    • NLOS: pathloss_inh_nlos(fc, d_3D, option)
    • Average: pathloss_inh(fc, d_3D, d_2D, type, option)

Infoor Factory (InF)

  • LOS probability: pr_los_inf(type, d_2d, h_BS, h_UT, h_c, r)

  • Pathloss:

    • LOS: pathloss_inf_los(fc, d_3D)
    • NLOS: pathloss_inf_nlos(fc, d_3D, type)
    • Average: pathloss_inf(fc, d_3D, h_BS, h_UT, h_c, r, type)

    Different types of InF

    • InF-SL (sparse clutter, low BS)
    • InF-DL (dense clutter, low BS)
    • InF-SH (sparse clutter, high BS)
    • InF-DH (dense clutter, high BS)
    • InF-HH (high Tx, high Rx)

A top-level pathloss function for all scenarios

pathloss(scenario, los, fc, h_BS, h_UT, W, h, d_2D, type, option, h_c, r)