Compressed Beamforming Coefficients for Cloud RAN Fronthaul
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Solution Overview
Problem
Next-generation wireless communication networks face challenges in transporting digital samples and control information for massive MIMO systems due to high throughput requirements, leading to increased costs and complexity in deploying centralized radio access networks.
Innovation Solution
The implementation of a split radio access network that compresses beamforming coefficients for fronthaul links, allowing for digital beamforming at remote radio units and reducing the number of bits required to describe the beamforming matrix, thereby easing throughput requirements and deployment costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital beamforming is implemented at centralized baseband units for massive MIMO systems, then beamforming performance is improved, but fronthaul throughput requirements and deployment costs increase
Solution Approach 1:
The patent divides the radio access network into centralized baseband units and distributed remote radio units. The beamforming coefficient determination and compression functions are segmented and placed at the centralized baseband unit, while only the compressed coefficient data needs to be transmitted over the fronthaul to the remote radio units for actual beamforming execution.
Solution Approach 2:
The patent extracts the computationally intensive beamforming coefficient calculation and compression algorithms from the remote radio units and centralizes them at the baseband unit. This extraction allows the remote units to perform simpler operations using the compressed data, reducing fronthaul throughput requirements while maintaining beamforming performance.
2Measurement precision
If full beamforming coefficient data is transmitted over fronthaul links, then beamforming accuracy is maintained, but the number of bits required and transmission costs increase
Solution Approach 1:
The patent applies compression algorithms that transform the beamforming coefficient data into a more compact representation. By changing the parameter representation (from full-precision coefficients to compressed index or reduced-precision data), the system maintains adequate beamforming accuracy while significantly reducing the number of bits that need to be transmitted over the fronthaul.
Data Source
AI summary
A split radio access network is provided that efficiently transmits beamforming coefficients from a distributed baseband unit device to a remote radio unit device to facilitate beamforming at the remote radio unit. The beamforming coefficients can be determined at the baseband unit device and transmitted along with the IQ data (data to be beamformed) to the remote radio unit device. Due to the large number of antenna ports however, there can still be a very large number of coefficients to transmit, and the disclosure provides for a compressed set of coefficients that reduces the overhead signaling requirements. Instead of sending coefficients for every kth antenna port, the system can select a subset of the coefficients corresponding to a set of k antenna ports which can be used by the remote radio unit to approximate the full set of beamforming coefficients.