Base Station Signal Scaling for Low-Overhead PRB Compression
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Solution Overview
Problem
Current sample compression methods in communication networks, particularly in 5G base stations, are inefficient due to high variability of signals within a PRB, leading to excessive bit usage for quantization noise and unnecessary repetition of carrier scaling factors.
Innovation Solution
Implementing a two-stage block scaling method where a wide block scaling factor is updated every first plurality of data samples and a narrow block scaling factor is updated every second plurality of data samples, with the narrow block scaling factor having a lower total dynamic range, reducing the number of bits required and optimizing signal processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a single scaling factor is used for all data samples in a PRB, then the signaling overhead is reduced, but the signal processing precision deteriorates due to high signal variability within the PRB
Solution Approach 1:
The patent divides the scaling operation into two segments: a wide-block scaling factor applied to all data samples in the PRB, and a narrow-block scaling factor applied to specific subsets of data samples. This segmentation allows the system to use a coarse scaling factor for most samples (reducing signaling overhead) while applying a fine scaling factor to specific samples where high precision is needed (maintaining signal processing precision).
Solution Approach 2:
The patent applies different scaling precision to different parts of the signal data. The narrow-block scaling factor provides local quality enhancement for specific data samples that require higher precision, while the wide-block scaling factor handles the majority of samples with lower precision requirements. This local quality approach optimizes the balance between signaling overhead and processing precision.
2Productivity
If compression methods are applied to reduce bit usage, then the transmission efficiency is improved, but the quantization noise increases leading to loss of signal quality
Solution Approach 1:
The patent employs dynamic scaling factors that are updated at different rates for wide-block and narrow-block processing. The wide-block scaling factor is updated less frequently to reduce signaling overhead, while the narrow-block scaling factor is updated more frequently to maintain signal quality. This dynamic approach allows the system to adapt to changing signal conditions while optimizing transmission efficiency.
Solution Approach 2:
The patent changes the precision parameter of the scaling factor based on the specific data samples being processed. By using a two-stage approach with different precision levels for wide-block and narrow-block scaling, the system optimizes the balance between compression efficiency and signal quality preservation, reducing bit usage while minimizing quantization noise impact.
3Measurement precision
If carrier scaling factors are repeated for every data block, then the signal processing accuracy is maintained, but the computational complexity increases
Solution Approach 1:
The patent merges the scaling operations by applying a wide-block scaling factor to multiple data samples simultaneously, rather than applying separate scaling factors to each small block. This merging reduces the total number of scaling operations required, thereby reducing computational complexity while still maintaining signal processing accuracy through the complementary narrow-block scaling factor applied to specific samples.
Solution Approach 2:
The wide-block scaling factor serves a universal function by being applied to all data samples in the PRB, providing a baseline scaling operation that covers the entire data set. This universal application reduces the need for repeated specific scaling operations, lowering computational complexity while the narrow-block scaling factor provides targeted precision enhancement where needed.
Data Source
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AI summary
One embodiment of the disclosure provides a method performed by a first component part of a base station. The first component part comprises one of a central unit and a radio unit. The base station further comprises a second component part, which comprises the other of the central unit and the radio unit. The method comprises: receiving a user data stream to be transmitted to the second component part, the user data stream comprising a plurality of data samples which are for transmission by the base station over an air interface, or which have been received by the base station over the air interface; applying first and second scaling factors to the data samples to generate a scaled user data stream, wherein the first scaling factor is updateable every first plurality of data samples, wherein the second scaling factor is updateable every second plurality of data samples, and wherein the second plurality of data samples is less than the first plurality of data samples; and transmitting the scaled user data stream and an indication of the first and second scaling factors to the second component part.[Figure 4 to accompany the abstract.]