Distributed Digital Beamforming for Scalable Phased Arrays
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Solution Overview
Problem
Adaptive beamformers face scalability issues due to computational complexity and the need for centralized processing and calibration across sub-arrays, especially with increasing numbers of antenna elements, leading to inefficiencies in digital beamforming.
Innovation Solution
A digital beamformer system with distributed element processing hardware that performs iterative beamforming using global and local feedback, eliminating the need for centralized processing and calibration, and allowing for scalable operation with large numbers of antenna elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If traditional adaptive beamforming algorithms (e.g., MUSIC) are used with centralized processing, then beamforming gain is achieved, but computational complexity increases by the number of elements cubed as the number of elements increases
Solution Approach 1:
The patent divides the large antenna array into multiple sub-arrays, with each sub-array processed by independent element processing hardware. This segmentation allows parallel processing of sub-array signals without requiring centralized computation across all elements, reducing overall computational complexity from O(N³) to O(M×n³) where M is the number of sub-arrays and n is the number of elements per sub-array.
Solution Approach 2:
The patent transitions from purely digital beamforming to a hybrid analog-digital approach by introducing an analog combiner stage. Signals are combined in the analog domain after element-level processing, reducing the dimensionality of digital signal processing requirements and enabling scalable implementation with large numbers of antenna elements.
2Power
If the number of antenna elements is increased to achieve higher beamforming gain, then beamforming performance improves, but the need for calibration and phase synchronization across sub-arrays increases system complexity
Solution Approach 1:
Each element processing hardware unit independently performs calibration of its own sub-array using local reference signals and adaptive algorithms. This self-service calibration approach eliminates the need for centralized phase synchronization across all sub-arrays, as each unit autonomously corrects its own phase errors without requiring inter-sub-array coordination.
3Measurement precision
If all signals are made available for correlation with all other signals, then accurate beamforming is achieved, but a common processor is required which limits scalability
Solution Approach 1:
The patent segments the signal processing function across multiple independent element processing hardware units, each handling a specific sub-array. Each unit performs local signal correlation and beamforming operations independently, eliminating the need for a single common processor to handle all signals simultaneously and enabling scalable system architecture.
Solution Approach 2:
The patent merges the outputs of multiple independent element processing hardware units through an analog combiner. This combining operation integrates the results of distributed signal correlation and beamforming operations, achieving the equivalent of centralized processing without requiring a single common processor to handle all signals.
Data Source
AI summary
A radio system is used for adaptive digital beamforming in a phased antenna-array. The radio system scales with large numbers of antenna elements in a phased array. The radio system uses a distributed computing method that is inherently scalable with large numbers of the antenna elements. The radio system includes a digital beamformer. The digital beamformer is an analog combiner, digital beamformer. The digital beamformer includes element processing hardware (EPH) which perform the distributed computing.