GSOC2024RLUsability5G

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Project Overview

• Project Name: Enhancement of RL Approach Accessibility in NR
• Student: Hyerin Kim
• Mentors: Amir Ashtari, Katerina Koutlia, Bijana Bojovic, Gabriel Ferreira
• Google page: https://summerofcode.withgoogle.com/programs/2024/projects/vPuZgTe1
• Project Goals: In this project, I will design a new RL based MAC scheduler of NR and implement it in 5g-lena integrating with ns3-gym. Additionally, I will enhance the usability of 5G-lena in terms of RL approach by providing an example using the designed RL based scheduler.
• Repository: https://github.com/mye280c37/GSoC-2024
• About Me: I am currently pursuing a Master's degree in Computer Science and Engineering at Seoul National University, South Korea. My research at the Mobile Computing & Communications Laboratory focuses on resource allocation methods in NR V2X Sidelink. As an undergraduate, I conducted research on improving spatial reuse in dense Wi-Fi environments and implemented a Reinforcement Learning (RL)-based modified OBSS/PD algorithm using ns3 gym. I believe that participating in GSoC 2024 presents an excellent opportunity for me to contribute to enhancing the usability of 5G and RL experiences on ns-3, while also deepening my understanding of 5G technology, mechanisms, and system architecture.

Milestones

Phase1. Design example (3 weeks)

• Familiar with 5g-lena (2 weeks)
• Design Scenario (e.g., UEs deployment, UEs speed, cell configuration, …) (1 week)

- Define Assumption (e.g., delay, TDMA/OFDMA, …)

Phase2. Design RL based Scheduler (6 +1 weeks)

• Design scheduler (2 weeks)

- input/output

- goal of optimization

• Design RL process (1 week)

- Define suitable RL techniques considering optimization objective of the scheduler and computational complexity

• Implementation of RL based scheduler in 5g lena (3 +1 weeks)

- Create the test

- Create documentation

- Create MR to 5g lena (Milestone 1)

Phase3. RL Integration (4 weeks)

• Design RL framework (1 week)

- Define RL technique

• Develop gym scripts (3 weeks)

- Develop gym python scripts

- Develop ns3 gym interface in RL 5g lena example

- Validate RL process of the example

- Create MR to 5g lena (Milestone 2)

Phase4. Evaluation (3 +1 weeks)

• Evaluate the result of example compared with other schedulers

- Write simulation campaign scripts

- Execute scripts

- Plotting python scripts

• Address review comment of the MR 1 and 2
• Update MR 1 and 2 with necessary modification
• Create brief description of the work and the results for 5g lena blog (Milestone 3)

Weekly Report

Week 1 [May 27 - Jun. 02]

Familiar with 5g-lena (1)

• Studied cttc-nr-demo example with cttc-nr-demo tutorial

- quasi-ideal assumption

- RAN Lifecycle (i.e. downlink packet flow from gNB to UE)

- How to configure the scenario, EPC, physical layer, and traffic(application)

- *(Doubt) What do I consider when I configure bands, carrier component, BWP?*

Week 2 [Jun. 02 - Jun. 09]

Familiar with 5g-lena (2)

• Studied schedulers in 5g-lena

- Studied MAC Layer section related to schedulers in NR module documentation

- Studied cttc-nr-simple-qos-sched example