Cloud RAN Architecture for Hardware-Agnostic Deployment
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Solution Overview
Problem
Current cloud radio access network (C-RAN) solutions face challenges in configuring and deploying computing resources due to limitations in server capabilities, interconnect interfaces, latency, and resource availability, making it difficult to achieve scalable and efficient wireless service delivery across various hardware configurations.
Innovation Solution
Implementing a cloud-based C-RAN architecture that uses virtualized network functions and self-configuration methods to dynamically allocate processing resources and channel configurations based on available hardware capabilities, allowing for flexible deployment across cloud and non-cloud hardware, and enabling horizontal and vertical scaling of resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud-based C-RAN architecture is implemented with virtualized network functions, then adaptability to different hardware configurations is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal C-RAN architecture using virtualized network functions that can operate across diverse hardware platforms including cloud and non-cloud environments. The virtualization layer abstracts hardware-specific details, allowing the same software stack to function on different server configurations, cloud infrastructure, and edge devices, thereby achieving multi-functionality and broad hardware compatibility.
Solution Approach 2:
The patent introduces a self-configuration mechanism as an intermediary layer between the virtualized network functions and the underlying hardware. This mediator automatically detects hardware capabilities and configures appropriate parameters, eliminating the need for manual optimization for each hardware platform and reducing the complexity of managing diverse configurations.
2Productivity
If self-configuration methods are used to dynamically allocate processing resources, then resource utilization efficiency is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements self-configuration capabilities that enable the C-RAN system to automatically allocate and optimize processing resources without human intervention. The system autonomously detects available hardware resources, determines optimal configuration parameters, and adjusts resource allocation dynamically based on workload demands, thereby improving efficiency while removing the burden of manual configuration management.
3Adaptability or versatility
If processing resources are distributed across multiple cloud nodes, then scalability is improved, but device complexity increases
Solution Approach 1:
The patent divides the C-RAN processing functions into distributed units that can be deployed across multiple cloud nodes independently. Each node handles specific processing tasks (e.g., L1, L2, or L3 functions), allowing incremental scaling by adding or removing individual nodes without redesigning the entire system. This segmentation enables flexible scalability while managing complexity through modular architecture.
Data Source
AI summary
A Cloud Radio Access Network (C-RAN) includes at least one cloud node. In a flexi-split architecture, the at least one cloud node implements at least a portion of L1 processing for a distributed unit (DU) using a first at least one processing core and L2 processing for the DU using a second at least one processing core. The L1 and L2 processing can be implemented in the same or different cloud node and/or server as each other. The L1 processing and the L2 processing communicate via a network functional application platform interface (nFAPI). The cloud node(s) also determine at least one self-configuration decision, based on an available hardware configuration, which indicates a number of processor cores needed to implement the C-RAN using the hardware configuration and/or a channel configuration for the C-RAN to use when exchanging RF signals with a plurality of UEs.