Signal Subspace Interface for Distributed Base Station Data Rate Reduction
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Solution Overview
Problem
Current antenna array architectures for OFDM systems face challenges in reducing complexity and data rate requirements, particularly when dealing with a large number of antennas, as existing interfaces like CPRI and OBSAI struggle to efficiently transmit user-specific beamforming data without compromising latency or increasing DSP processing demands.
Innovation Solution
The implementation of a signal subspace-based post-FFT interface that selects and transmits M streams of post-fast-Fourier-transform data, allowing for reduced data rates and independent stream numbers from antenna design, by selecting a user-specific signal subspace that adapts to fading conditions or long-term signal properties, enabling efficient data transfer across different frequency bins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional interfaces (CPRI, OBSAI) are used to transmit antenna array data, then complete signal data can be transmitted, but data rate requirements and interface complexity increase significantly
Solution Approach 1:
The patent extracts only the essential signal subspace components (M dominant eigenvectors) from the complete antenna signal data, transmitting only these reduced-dimensional representations through the interface. This extraction principle reduces data rate requirements while preserving the most important signal information needed for user-specific beamforming, directly resolving the contradiction between data completeness and interface complexity.
Solution Approach 2:
The patent changes the parameter of signal representation from full-dimensional antenna data to reduced-dimensional subspace data characterized by eigenvalues and eigenvectors. By transforming the data into this compact parametric form, the interface complexity and data rate requirements are significantly reduced while maintaining the essential signal characteristics needed for reliable communication.
2Reliability
If the number of antenna elements is increased to improve system performance, then beamforming capability improves, but the number of data streams and processing complexity increase
Solution Approach 1:
The patent applies eigenvalue decomposition to extract only the M dominant signal subspace components from the N-dimensional antenna data, where M is much smaller than N. This extraction allows the system to maintain high beamforming performance with large antenna arrays while reducing the processing complexity and data stream count to manageable levels by focusing only on the most significant signal components.
Solution Approach 2:
The patent transforms the high-dimensional antenna array data into a compact parametric representation using eigenvalues and eigenvectors. This parameter transformation enables the system to handle large numbers of antenna elements efficiently by working with the reduced set of dominant subspace parameters rather than processing all raw antenna data, thus improving beamforming capability without proportionally increasing complexity.
3Reliability
If user-specific beamforming data is transmitted for each user, then communication quality improves, but data rate requirements and latency increase
Solution Approach 1:
The patent extracts the essential signal subspace characteristics (M dominant eigenvectors per user) that capture the most important beamforming information. By transmitting only these extracted subspace parameters rather than complete user-specific beamforming data, the system maintains communication quality while reducing data rate requirements and processing latency, directly addressing the time-loss contradiction.
4Device complexity
If post-FFT array processing is used to reduce complexity, then the number of antennas can be reduced, but performance may be compromised
Solution Approach 1:
The patent extracts the dominant signal subspace components after FFT processing, allowing the system to maintain high performance with fewer effective antenna elements. This extraction principle enables post-FFT array processing to achieve the desired performance level with reduced antenna count and corresponding complexity reduction, resolving the contradiction between complexity reduction and performance maintenance.
Data Source
AI summary
A method and apparatus are disclosed for determining a signal subspace in a communications system. A remote apparatus obtains signal streams from antenna elements or signal streams from antenna beams. Based on the obtained signal streams, the apparatus selects a signal subspace for a user, the signal subspace having a dimension M. Based on the selected signal subspace, the apparatus transmits, via an interface to a central apparatus, M streams of post-fast-Fourier-transform data, the interface being capable of transmitting a different subspace for different frequency bins.