I/Q Signal Compression with Block Scaling for Base-Station Links
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Solution Overview
Problem
Current wireless base-station solutions require high data rates and significant communication bandwidth for transmitting inphase (I) and quadrature (Q) samples, leading to increased costs and resource allocation, particularly in 3G and 4G technologies, where a more efficient compression method is needed to reduce these requirements.
Innovation Solution
A compression scheme that filters and decimates digital signals, applies block scaling and quantization, and includes adaptive parameters to maintain signal quality, effectively reducing transport data rates while minimizing processing delay, and is applicable to various wireless technologies and transport technologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If uncompressed I/Q samples are transmitted over transport links, then signal quality is maintained, but transport network bandwidth and data rates increase significantly
Solution Approach 1:
The patent extracts and transmits only the essential signal information by computing statistics (mean, variance, skewness, kurtosis) from I/Q samples and transmitting these compressed statistical parameters instead of the full sample data. This extraction approach maintains signal quality for reconstruction while dramatically reducing transport bandwidth requirements from gigabit rates to much lower rates.
Solution Approach 2:
The patent transforms the signal representation from time-domain I/Q samples to frequency-domain statistical parameters (mean, variance, skewness, kurtosis). This parameter transformation enables efficient compression while preserving the essential characteristics needed for signal reconstruction, achieving lower data rates without sacrificing signal quality.
2Quantity of substance
If signal compression is applied to reduce transport data rates, then bandwidth requirements decrease, but signal quality may deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where the BBU monitors signal quality metrics and adjusts compression parameters accordingly. The system uses error-vector magnitude (EVM) and adjacent channel power ratio (ACPR) measurements to determine optimal compression settings, ensuring that signal quality requirements are met while maximizing compression efficiency.
Solution Approach 2:
The compression scheme is designed to be dynamic and adaptive, allowing parameters such as block size, scaling factors, and quantization resolution to be adjusted based on current signal conditions and quality requirements. This dynamic adaptation enables the system to maintain signal quality across varying operational conditions while optimizing bandwidth utilization.
3Measurement precision
If I/Q samples are transmitted at high data rates, then signal fidelity is preserved, but network resource allocation and cost increase
Solution Approach 1:
The patent extracts only the essential statistical characteristics (mean, variance, skewness, kurtosis) from the I/Q samples and transmits these compressed parameters instead of the full high-rate sample data. This extraction maintains sufficient signal fidelity for reconstruction while dramatically improving network resource efficiency by reducing bandwidth consumption and operational costs.
Solution Approach 2:
The system transforms the signal representation to use compact statistical parameters, changing from high-rate time-domain samples to low-rate frequency-domain statistics. This parameter change achieves both preserved signal fidelity (through accurate statistical representation) and improved network resource efficiency (through reduced data rates and bandwidth requirements).
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AI summary
In one embodiment, the method of compressing a digital signal includes reducing redundancies in the digital signal, scaling a block of samples output from the reducing step by a scaling factor, and quantizing the scaled samples to produce compressed samples. The digital signal being compressed may be a digital radio frequency signal.