SRS Data Compression for Low-Latency 5G Fronthaul Transmission
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Solution Overview
Problem
The existing Eigenmode Based Beamforming (EBB) solution for 5G TDD systems faces challenges in efficiently transmitting SRS data due to limited fronthaul bandwidth, leading to increased latency and potential feature loss in uplink SRS channel processing.
Innovation Solution
A dual-periodic configuration for SRS data transmission is implemented, where raw SRS data is transmitted during a long period, and compression information is determined by the baseband unit to compress the data in the radio frequency unit during a short period, reducing latency without additional complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If raw SRS data is transmitted during a long period without compression, then transmission bandwidth requirements are reduced, but transmission latency increases
Solution Approach 1:
The baseband unit performs preliminary analysis on the first SRS data to determine compression information before the second SRS data transmission. This pre-computation of compression parameters (such as spatial domain filtering coefficients or frequency domain compression ratios) enables the radio frequency unit to quickly compress the second SRS data, reducing transmission latency while maintaining bandwidth efficiency.
Solution Approach 2:
The system dynamically adjusts the compression strategy based on channel conditions. The baseband unit analyzes the first SRS data to determine appropriate compression information, which is then applied to the second SRS data transmission. This dynamic adaptation allows the system to optimize the balance between bandwidth usage and transmission latency according to actual channel characteristics.
2Loss of time
If SRS data is compressed in the radio frequency unit, then transmission latency is reduced, but device complexity increases
Solution Approach 1:
The baseband unit acts as an intermediary that performs the complex analysis and determines compression information based on the first SRS data. The radio frequency unit then applies this pre-determined compression information to the second SRS data, which is a simpler operation. This division of labor reduces the complexity burden on the radio frequency unit while still achieving compression latency reduction.
Solution Approach 2:
The complex compression parameters are determined in advance by the baseband unit during the first period. This preliminary determination of compression information (such as spatial filters or compression ratios) simplifies the actual compression operation performed by the radio frequency unit during the second period, reducing both computational complexity and transmission latency.
3Measurement precision
If compression information is determined based on first SRS data, then channel reconstruction accuracy is maintained, but processing time increases
Solution Approach 1:
The system applies compression based on analysis of only the first SRS data, rather than processing all SRS data equally. This partial action approach maintains channel reconstruction accuracy for the second SRS data transmission by using representative compression information derived from the first period's channel characteristics, while avoiding the time cost of analyzing every data point.
Data Source
AI summary
Embodiments of the present disclosure relate to methods, apparatuses and computer readable storage media for SRS data transmission. In example embodiments, a method is provided. According to the method, an apparatus forwards, during a first period, first SRS data received from a terminal device to a further apparatus. The further apparatus determines, based on the first SRS data, compression information for compressing SRS data, and transmits the compression information to the apparatus. Thereby, the apparatus compresses, during a second period, second SRS data received from the terminal device based on the compression information, and transmits, during the second period, the compressed second SRS data to the further apparatus. In this way, the SRS data can be effectively compressed, thus reducing the latency of the SRS data transmission.