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ai-agent

Matlab-code-TGCN-Mar2018: Improve Cell-Edge User Performance

Get Matlab code for MISO-NOMA systems improvement, useful for founders in telecommunications and networking.
advanced⏱ 1-2 hoursπŸ’΅ Free (self-hosted)
32 stars11 forksMATLABQuality 8/10Updated 3/3/2022100% free Β· open source
What it is

Use a pre-existing Matlab code to improve cell-edge user performance in MISO-NOMA systems.

What you can make with it

Specific Matlab code like: a modified 'cell-edge_user_performance_improvement.m' file.

How it helps

This pre-existing Matlab code helps developers implement complex MISO-NOMA system improvements without having to recreate the research themselves.

Real use case example

"A founder of a telecommunications company can use this pre-existing Matlab code to modify the cell-edge user performance in their MISO-NOMA system. First, they import the Matlab code into their project. Next, they customize the code to fit their specific MISO-NOMA system setup. Finally, they run the modified code to see the improvements in cell-edge user performance."

If you're new

Beginners might want to pick this up when they start working with pre-existing code.

If you're senior

Senior engineers and professionals would reach for this when refining or optimizing a complex telecommunications system.

Common confusion cleared up

Some developers might confuse this pre-existing Matlab code with a custom solution, but it's simply a pre-existing implementation of a specific technique.

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Why we list it on WorkflowStacks: This marketplace of AI tools includes this pre-existing Matlab code, making it easily accessible for telecommunications and networking founders.
What it does

Improves the performance of cell-edge users in MISO-NOMA systems using TAS and SWIPT-based cooperative transmissions with provided Matlab code

Install / run
Clone the repository using 'git clone https://github.com/trinhudo/Matlab-code-TGCN-Mar2018.git'
When to use it
  • β€’When optimizing MISO-NOMA systems for better cell-edge user performance
  • β€’For researching and developing cooperative transmission strategies in telecommunications
  • β€’To simulate and analyze the impact of TAS and SWIPT on MISO-NOMA system performance
Quick start
  1. 1Open Matlab and navigate to the cloned repository directory
  2. 2Run the script 'TGCN_Mar2018.m' to start the simulation
  3. 3Modify the parameters in 'system_parameters.m' to configure the MISO-NOMA system
  4. 4Use the 'plot_results.m' script to visualize the simulation results
  5. 5Refer to the 'README.md' file for detailed instructions and explanations
Ready-to-paste prompt
Run 'TGCN_Mar2018' with 'Nb = 2' and 'K = 4' to simulate a MISO-NOMA system with 2 base stations and 4 users
Heads up: Ensure you have Matlab version R2017a or later installed, as the code uses features introduced in this version
Saves to your device
What's inside β€” free to inspect
No purchase needed

Read the entire source before you build β€” unlike paid marketplaces that hide it behind a buy button.

27
top-level files
0
folders
13K
repo size
β€”
license
Key files
README.md
File tree
alpha_run_S1.m
alpha_run_S2.m
alpha_run_S3.m
asym_S1.m
asym_S2.m
asym_S3.m
distance_S0_random.m
distance_S1_F_sim_ana.m
distance_S2_F_sim_ana.m
distance_S3_F_sim_ana.m
fig_OMA_noncoop_coop.m
fig3_verification_S1.m
Integral_0_mu.m
Integral_mu_inf.m
non_coop_S1.m
PowerAllocation.m
README.md
rho_run_S1.m
rho_run_S2.m
rho_run_S3.m
Rth_S1.m
Rth_S2.m
Rth_S3.m
S0_random.m
Quick Actions
Details
Creator
trinhudo
Language
MATLAB
Category
ai-agent
Published
1/5/2019

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