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Renewable Energy Powered and Open RAN-based Architecture for 5G Fixed Wireless Access Provisioning in Rural Areas

Anselme Ndikumana, Kim Khoa Nguyen, Mohamed Cheriet

TL;DR

This paper proposes renewable energy powered and Open RAN-based architecture for 5G FWA serving LDRAs using three-level closed-loops, a new energy model that leverages renewable energy, and proposes reinforcement learning and successive convex approximation to solve problems.

Abstract

Due to the high costs of optical fiber deployment in Low-Density and Rural Areas (LDRAs), 5G Fixed Wireless Access (5G FWA) recently emerged as an affordable solution. A widely adopted deployment scenario of 5G FWA includes edge cloud that supports computing services and Radio Access Network (RAN) functions. Such edge cloud requires network and energy resources for 5G FWA. This paper proposes renewable energy powered and Open RAN-based architecture for 5G FWA serving LDRAs using three-level closed-loops. Open RAN is a new 5G RAN architecture allowing Open Central Unit and Open Distributed Unit to be distributed in virtualized environment. The first closed-loop distributes radio resources to Open RAN instances and slices at the edge cloud. The second closed-loop allocates radio resources to houses. We design a new energy model that leverages renewable energy. We jointly optimize radio and energy resource allocation in closed-loop 3. We formulate ultra-small and small-time scale optimization problems that link closed-loops to maximize communication utility while minimizing energy costs. We propose reinforcement learning and successive convex approximation to solve the formulated problems. Then, we use solution data and continual learning to improve resource allocation on a large timescale. Our proposal satisfies 97.14% slice delay budget.

Renewable Energy Powered and Open RAN-based Architecture for 5G Fixed Wireless Access Provisioning in Rural Areas

TL;DR

This paper proposes renewable energy powered and Open RAN-based architecture for 5G FWA serving LDRAs using three-level closed-loops, a new energy model that leverages renewable energy, and proposes reinforcement learning and successive convex approximation to solve problems.

Abstract

Due to the high costs of optical fiber deployment in Low-Density and Rural Areas (LDRAs), 5G Fixed Wireless Access (5G FWA) recently emerged as an affordable solution. A widely adopted deployment scenario of 5G FWA includes edge cloud that supports computing services and Radio Access Network (RAN) functions. Such edge cloud requires network and energy resources for 5G FWA. This paper proposes renewable energy powered and Open RAN-based architecture for 5G FWA serving LDRAs using three-level closed-loops. Open RAN is a new 5G RAN architecture allowing Open Central Unit and Open Distributed Unit to be distributed in virtualized environment. The first closed-loop distributes radio resources to Open RAN instances and slices at the edge cloud. The second closed-loop allocates radio resources to houses. We design a new energy model that leverages renewable energy. We jointly optimize radio and energy resource allocation in closed-loop 3. We formulate ultra-small and small-time scale optimization problems that link closed-loops to maximize communication utility while minimizing energy costs. We propose reinforcement learning and successive convex approximation to solve the formulated problems. Then, we use solution data and continual learning to improve resource allocation on a large timescale. Our proposal satisfies 97.14% slice delay budget.

Paper Structure

This paper contains 17 sections, 41 equations, 15 figures, 1 table, 2 algorithms.

Table of Contents

  1. Introduction
  2. Related Work
  3. System model
  4. Energy Efficient Sliced Resource Allocation in O-RAN enabled 5G FWA
  5. Communication Model
  6. RB distribution to vO-DUs using closed-loop $2$
  7. Closed-loop $1$ for intra-slice RB allocation to CPEs
  8. Feedback for closed-loops 1 and 2
  9. Zero-touch resource adjustment
  10. Energy Model of Edge Cloud
  11. Problem Formulation
  12. Closed-loop $3$ for Joint Problem of Radio Resource and Energy Management
  13. Proposed Solution
  14. Performance Evaluation
  15. Simulation Setup
  16. ...and 2 more sections

Figures (15)

  • Figure 1: O-RAN control loops alliance2018ran
  • Figure 2: Illustration of our system model.
  • Figure 3: Illustration of our energy model.
  • Figure 4: The Ape-X implementation and closed-loops.
  • Figure 5: CL for closed-loop $3$.
  • ...and 10 more figures

Theorems & Definitions (1)

  • Remark 1