Abstract

The objective of this paper is to extend into the OpenAirInterface platform the Coordinated Scheduling (CS) technique to allocate resource blocks among User Equipment (UE) in a wisely way and to control the energy efficiency, the throughput, and the inter-cell interference for Cloud Radio Access Networks (C-RANs). It is achieved by modifying the OpenAirInterface scheduler code, increasing the Remote Radio Unit (RRU) scalability, and employing some component carriers of the Radio Cloud Center (RCC), each one them with one or more UEs. The hardware utilized is composed of general-purpose processors and fast Ethernet transport ports, and the software is recent frequency-domain methodologies in a software-only environment where the use of radio units are not required. However, the USRP B200 mini-i radio unit and the UE (Samsung Galaxy S8) were considered only for validation purposes. The emulations using frequency-domain methodologies, compatible with fourth and fifth-generation cellular systems, allowed real-time emulations and reduced 10-fold the multipath channel’s signal processing complexity compared to time-domain methodologies. The results show we can emulate a real-time static coordinated scheduling proof-of-concept for one C-RAN composed of one RCC, three RRUs, and three UEs. In the end, it is evaluated the reproducibility and the scalability of synthetic networks composed of one RRU and at least one UE, without using software-defined radio units, reducing prototyping uncertainties of the physical hardware and the total price of the experiment.

Highlights

  • The fifth generation (5G) of cellular networks is being deployed around the world, and some use cases have been designed, such as the Enhanced Mobile Broadband, the Massive Machine Type Communications, and the Ultra-Reliable and Low Latency Communications (URLLC)

  • Another important technology is the Cloud Radio Access Network (C-RAN), which has evolved through some generations of cellular networks. It disaggregates the base station’s traditional concept between new entities called the Base Band Unit (BBU) and the Remote Radio Head (RRH). These entities are connected through the CPRI fronthaul interface, and BBUs are pooling at centralized Data Centers (DCs) [2]

  • Real-time Coordinated Scheduling for Cloud Radio Access Networks in a Software-only Environment using the OpenAirInterface platform better understanding, we show in figure 14, the allocation when the emulator lte-softmodem (RCC side) is executed

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Summary

Introduction

The fifth generation (5G) of cellular networks is being deployed around the world, and some use cases have been designed, such as the Enhanced Mobile Broadband (eMBB), the Massive Machine Type Communications (mMTC), and the Ultra-Reliable and Low Latency Communications (URLLC). New emerging radio technologies such as mmWaves, small cells, massive MIMO, and beamforming have been proposed and adopted to solve issues like traffic saturation, macrocell congestion, capacity, and spectral efficiency Another important technology is the Cloud Radio Access Network (C-RAN), which has evolved through some generations of cellular networks. Real-time Coordinated Scheduling for Cloud Radio Access Networks in a Software-only Environment using the OpenAirInterface platform intelligence was utilized to enable an F-RAN testbed employing the OpenAirInterface (OAI) emulation platform [6]. We pool RRUs using the IF4P5 interface (7.1 functional split of the 3GPP standard) where in-phase and quadrature signals are exchanged in the frequency domain and skip the use of radio units to accomplish a software-only emulation This approach increases the reproducibility, improves the scalability, and reduces prototyping uncertainties of software-defined radio frontends, which is an alternative for people without experience with radio devices or those who do not want to invest in expensive radio units. In fourth section, we outline conclusions and future works

Problem Statement and Methodology
Coordinated Scheduling
OpenAirInterface Scheduling Framework
Synthetic Networks Scalability
Performance Evaluation
Allocation of Physical Resource Blocks
Average Computation Time
Conclusions
Full Text
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