Baseband Signal Compression for BTS Serial Link Capacity
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Solution Overview
Problem
Current transceiver systems in wireless communication networks face challenges in managing increasing data volumes and evolving standards, leading to the need for costly hardware upgrades, particularly in terms of serial data link capacity and resource conservation, without compliance with existing standards like OBSAI and CPRI which do not support signal sample compression.
Innovation Solution
A method for compressing and decompressing signal samples in base transceiver systems, involving the use of compressors and decompressors at both the RF unit and baseband processor, formatted for compatibility with serial data link protocols, to increase data transfer capacity while conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If signal samples are transmitted uncompressed over serial data links, then data transfer capacity is maintained at current levels, but hardware upgrades become necessary more frequently to handle increasing data volumes
Solution Approach 1:
The patent applies asymmetric treatment to signal samples by identifying and exploiting the statistical asymmetry in signal distribution. By analyzing the probability density function of signal samples and applying compression based on their statistical characteristics (where most samples cluster around mean values), the system achieves efficient compression without requiring symmetric handling of all data points. This allows increased data volume to be managed within existing capacity constraints.
Solution Approach 2:
The patent changes the parameter representation of signal samples by transforming them from raw amplitude values to compressed representations based on statistical parameters (mean, variance, and probability density). This parameter transformation enables the same information to be conveyed using fewer bits, effectively increasing data transfer capacity without hardware upgrades while accommodating growing data volumes from evolving standards.
2Productivity
If hardware upgrades are performed to increase serial data link capacity, then data transfer capacity increases, but system cost increases
Solution Approach 1:
Instead of upgrading hardware parameters (data link capacity), the patent changes the information parameters by compressing signal representations. This software-based parameter transformation achieves the same effective data transfer capacity improvement without the cost of hardware upgrades, making the system more cost-effective while handling increasing data volumes from new services and standards.
Solution Approach 2:
The patent creates a compressed copy of the signal data that retains essential information while occupying less bandwidth. This virtual copy approach allows existing hardware to handle effectively doubled or tripled data volumes through algorithmic compression, avoiding the need for expensive physical hardware upgrades and reducing system cost while maintaining productivity.
3Productivity
If compression is applied to signal samples, then data transfer capacity increases, but signal processing complexity increases
Solution Approach 1:
The patent performs preliminary statistical analysis of signal samples to determine compression parameters (mean, variance, probability density function) before actual compression. This preliminary action characterizes the signal distribution once per signal type or configuration, and then reuses these parameters for compressing multiple samples, reducing per-sample processing complexity while achieving high compression ratios and increasing effective data transfer capacity.
Solution Approach 2:
The compression algorithm uses the signal's own statistical properties (its probability density function and distribution characteristics) to perform self-compression. The signal effectively compresses itself by exploiting its inherent redundancy and statistical regularities, minimizing the need for external complex processing while maximizing data transfer capacity through intelligent, adaptive compression.
4Adaptability or versatility
If existing standards like OBSAI and CPRI are followed, then system compatibility is maintained, but signal sample compression is not supported
Solution Approach 1:
The patent creates a universal compression framework that can be applied across multiple existing standards (OBSAI, CPRI, and future standards). The compression algorithm is designed to be standard-agnostic, working with the statistical properties of signals regardless of which standard governs the system. This multi-functional approach enables data transfer capacity improvement while maintaining compatibility with existing standards through the use of standardized compression control parameters and decompression procedures.
Data Source
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AI summary
A signal compression method and apparatus for a base transceiver system (BTS) in a wireless communication network provides efficient transfer of compressed signal samples over serial data links in the system. For the uplink, an RF unit of the BTS compresses baseband signal samples resulting from analog to digital conversion of a received analog signal followed by digital downconversion. The compressed signal samples are transferred over the serial data link to the baseband processor then decompressed prior to normal signal processing. For the downlink, the baseband processor compresses baseband signal samples and transfers the compressed signal samples to the RF unit. The RF unit decompresses the compressed samples prior to digital upconversion and digital to analog conversion to form an analog signal for transmission over an antenna. Compression and decompression can be incorporated into operations of conventional base stations and distributed antenna systems, including OBSAI or CPRI compliant systems.