This is the code implementation for the E-WMMSE algorithm.
CLick here for the original paper link:
A Novel Extrapolation Technique to Accelerate WMMSE
WMMSE.m : The main function for the WMMSE algorithm.
E-WMMSE.m : The main function for the E-WMMSE algorithm.
find_U.m : The function for finding the U in each iteration.
find_W.m : The function for finding the W in each iteration.
find_V.m : The function for finding the V in each iteration.
sumrate.m : The function for computing the sum rate.
Test_E_WMMSE.m : This is a function used to test E-WMMSE performance, enter the required parameters and the function would return the number of iterations, running time and sum rate information
Test_WMMSE.m : This is a function used to test WMMSE performance, enter the required parameters and the function would return the number of iterations, running time and sum rate information
Test.m : This script is used to assess the performance gap between the two algorithms WMMSE and E-WMMSE. The indicators include running time, number of iterations and final sum rate. Currently this script only supports the simulation scenario of a single base station.
figs : The folder that stores the results in different scenario configurations.
Run Test.m in matlab and get the following figures, one for running time and the other for sum rate:
CPU : 13600K (5.3 GHz, 6 Performance-cores, 8 Efficient-cores)
Motherboard : ASUS PRIME Z790-P
DRAM : 64G DDR5 6000MHz (KINGBANK)
Disk : 2T (SHPP41-2000GM)
GPU : NVIDIA Geforce RTX 4070
OS : Windows 11 Pro (23H2)
MATLAB Version : R2023a