This is the code implementation for the R-WMMSE algorithm.
CLick here for the original paper link:
Rethinking WMMSE: Can Its Complexity Scale Linearly With the Number of BS Antennas?
WMMSE.m : The main function for the WMMSE algorithm.
R-WMMSE.m : The main function for the R-WMMSE algorithm.
find_U1.m : The function for finding the U in each iteration of the WMMSE algorithm.
find_W1.m : The function for finding the W in each iteration of the WMMSE algorithm.
find_V1.m : The function for finding the V in each iteration of the WMMSE algorithm.
sumrate.m : The function for computing the sum rate in the WMMSE algorithm.
Test_R_WMMSE.m : This is a function used to test R_WMMSE performance, enter the required parameters and the function would return the number of iterations, running time and sum rate information
find_U.m : The function for finding the U in each iteration of the R-WMMSE algorithm.
find_W1.m : The function for finding the W in each iteration of the R-WMMSE algorithm.
find_X.m : The function for finding the X in each iteration of the R-WMMSE algorithm.
sumrate.m : The function for computing the sum rate in the R-WMMSE algorithm.
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 R-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