Front-Haul Data Prioritization for BBU-RRU Link Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wireless telecommunications systems face challenges in managing stringent bandwidth and latency requirements at the interface between base band units (BBUs) and remote radio units (RRUs), particularly in complex scenarios like CoMP, multi-site carrier aggregation, and higher MIMO in 5G, leading to increased cost and complexity in remote radio head (RRH) deployment.
Innovation Solution
The proposed solution involves altering the front-haul transport link structure between BBU and RRU to differentiate service levels based on data components' requirements and radio channel conditions, using techniques like layer mapping, pre-coding, and resource mapping to prioritize and packetize data, and optimizing transmission characteristics such as bandwidth and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If stringent bandwidth and latency requirements are imposed on the front-haul interface between BBU and RRU, then network performance and reliability are improved, but deployment cost and device complexity increase
Solution Approach 1:
The patent segments front-haul data into different priority levels (high priority and low priority data) and processes them through different queues. High priority data undergoes urgent processing while low priority data is handled separately, allowing the system to meet stringent bandwidth and latency requirements for critical data without unnecessarily complex processing for all data types, thereby improving reliability while controlling deployment complexity
Solution Approach 2:
The patent dynamically adjusts processing parameters such as queue priority levels, bandwidth allocation, and latency thresholds based on network conditions and data requirements. By changing these parameters adaptively, the system can optimize performance for different scenarios without requiring permanently complex deployment configurations
2Adaptability or versatility
If complex implementation scenarios like CoMP, multi-site carrier aggregation, and higher MIMO are supported, then network capability and service quality are improved, but deployment cost and complexity increase
Solution Approach 1:
The patent segments data processing into modular functional blocks including layer mapping, pre-coding, resource mapping, and priority-based queue management. Each module handles specific aspects of complex scenarios like CoMP and MIMO independently, allowing the system to support advanced network capabilities through composed modular functions rather than monolithic complex processing, thereby reducing deployment cost and complexity
Solution Approach 2:
The patent implements a universal front-haul data processing framework that can handle multiple complex scenarios (CoMP, carrier aggregation, MIMO) through the same prioritization and queue management mechanisms. This multi-functional approach allows a single deployment to support various network capabilities without requiring separate complex infrastructure for each scenario
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A device may include one or more processors. The device may receive, via a plurality of data streams of a front haul link, a set of packets including information for transmission via an air interface. The set of packets may be associated with a data prioritization relating to transmission via the air interface. The set of packets may include information of a time-frequency resource element array. The device may reconstruct a set of time-frequency resource elements of the time-frequency resource element array based on the data prioritization of the set of packets. The device may transmit, via the air interface, the time-frequency resource element array.