Centralized Baseband Pooling for RAN Energy Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for higher data rates in mobile communication systems leads to a need for more base stations, resulting in high power consumption and operational expenses, as base station transceivers are major contributors to energy usage, with processing capacity underutilized during non-peak hours.
Innovation Solution
Decoupling the BaseBand Unit (BBU) from the Remote Radio Head (RRH) allows for centralized processing and virtualization, enabling resource pooling and flexible assignment, along with the use of specialized routers for seamless data traffic management between edge devices and RRHs, facilitating load balancing, energy optimization, and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of base stations is increased to meet growing data rate demands, then network capacity is improved, but power consumption and operational expenses increase
Solution Approach 1:
Multiple baseband processing units are merged into a shared pool that serves multiple remote radio heads. Instead of each RRH having a dedicated BBU, the patent creates a centralized resource pool where processing capabilities are shared across multiple RRHs, reducing the total number of processing units needed while maintaining network capacity.
Solution Approach 2:
The shared baseband processing pool provides multi-functional capabilities to serve multiple RRHs with different requirements. The same processing resources can be dynamically allocated to different RRHs based on demand, making the system universal rather than dedicated, thereby reducing overall power consumption while maintaining productivity.
2Reliability
If dedicated processing capacity is provided for each base station transceiver, then service reliability is improved, but resource underutilization occurs during non-peak hours
Solution Approach 1:
The patent implements dynamic resource allocation where the shared baseband processing pool can flexibly adjust its capacity allocation based on real-time demand. During peak hours, more processing resources are allocated to meet high traffic demands; during non-peak hours, resources are scaled back or shared across multiple RRHs, eliminating the static over-provisioning that causes underutilization while maintaining service reliability.
Solution Approach 2:
The system enables self-service through automated resource management where the shared processing pool dynamically serves multiple RRHs based on their instantaneous needs. The architecture allows RRHs to access processing capacity on-demand without requiring dedicated reserved capacity, and the system automatically manages the allocation to ensure service reliability while optimizing resource utilization.
3Area of stationary object
If base stations are spread out to ensure coverage and service continuity, then network coverage is improved, but installation complexity and spatial requirements increase
Solution Approach 1:
The patent segments the base station functionality into two independent parts: remote radio heads for radio functions and a centralized baseband processing pool for processing functions. This segmentation allows RRHs to be strategically placed for optimal coverage while the complex processing infrastructure is consolidated in centralized locations, reducing installation complexity at each site while maintaining extensive network coverage.
Solution Approach 2:
The high-speed optical interface acts as an intermediary connecting the distributed RRHs to the centralized baseband processing pool. This intermediary enables the separation of radio and processing functions, allowing RRHs to be placed in locations optimized for coverage while the processing infrastructure is concentrated in locations optimized for installation and maintenance, thereby reducing overall system complexity.
4Use of energy by moving object
If processing capacity is centralized to reduce power consumption, then energy efficiency is improved, but routing complexity and data traffic management increase
Solution Approach 1:
The patent introduces specialized routing engines as intermediaries between the distributed RRHs and the centralized baseband processing pool. These routing engines handle the complexity of data traffic management, packet routing, and protocol conversion, thereby shielding the energy-efficient centralized processing architecture from routing complexities while enabling effective resource allocation and traffic management.
Solution Approach 2:
The system replaces traditional mechanical/dedicated connectivity with intelligent software-based routing and optical interfaces. The routing engines use software-based packet inspection and intelligent forwarding decisions rather than fixed physical connections, reducing the need for complex physical infrastructure while managing the centralized processing architecture efficiently.
Data Source
AI summary
Embodiments can provide an apparatus, a method and/or a computer program for routing data packets in a radio access network. The apparatus 10 comprises means for receiving 12 a data packet 804 from a source network node, the data packet comprises a data packet header and a data packet payload. The apparatus 10 further comprises means for inspecting 14 the data packet. The means for inspecting 14 is operative to perform a first packet inspection on the data packet header to determine information on a source or a destination of the data packet from the data packet header, and the means for inspecting 14 is operative to perform a second packet inspection on the data packet payload based on the information on the source or the destination of the data packet to determine information on an identification of the destination of the data packet. The apparatus 10 further comprises means for determining 16 information on a subsequent network node based on the information on the identification of the destination of the data packet.