MIMO Antenna Receivers with Hybrid Beamforming and Low-Resolution ADCs
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Solution Overview
Problem
MIMO receivers are costly and power-hungry due to high-resolution quantization and hardware complexity, and existing power-efficient methods compromise signal recovery accuracy.
Innovation Solution
A power-efficient MIMO receiver architecture using low-quantization rate ADCs and vector modulators with task-specific optimization, jointly optimizing analog and digital processing to recover desired signals while suppressing interferers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution quantization is used in MIMO receivers, then signal recovery accuracy is improved, but power consumption and hardware complexity increase
Solution Approach 1:
The patent segments the signal processing into two distinct domains: analog beamforming processing and digital quantization processing. The analog domain handles the majority of signal processing tasks (beamforming, spatial filtering) using continuous-time operations, while the digital domain performs only essential quantization with low-resolution ADCs. This segmentation allows the system to achieve high signal recovery accuracy through analog processing while using low-power, low-resolution digital components.
Solution Approach 2:
The patent introduces an analog combiner as an intermediary component between the antenna elements and the ADCs. This analog combiner performs beamforming and spatial signal processing in the continuous-time domain before quantization. By placing this intermediary analog processing stage, the system can achieve high measurement precision through accurate analog signal combination while using low-resolution ADCs, thereby reducing overall power consumption.
2Measurement precision
If high-resolution quantization is used in MIMO receivers, then signal recovery accuracy is improved, but device complexity increases
Solution Approach 1:
The patent divides the receiver architecture into analog and digital processing segments. The analog segment handles complex beamforming operations with continuous-time operations, while the digital segment uses simple low-resolution ADCs. This segmentation reduces hardware complexity by eliminating the need for high-resolution ADCs and their associated complex analog-to-digital conversion circuits, while maintaining signal recovery accuracy through analog processing.
Solution Approach 2:
The analog combiner serves as an intermediary that performs complex signal processing operations (beamforming, spatial filtering) in the analog domain before quantization. This intermediary stage handles the computationally intensive tasks that would otherwise require complex digital signal processing hardware, thereby reducing overall device complexity while maintaining measurement precision.
3Use of energy by moving object
If power-efficient methods are used to reduce power consumption, then power reduction is achieved, but signal recovery accuracy deteriorates
Solution Approach 1:
The patent employs an analog combiner as an intermediary that performs beamforming and spatial signal processing before quantization. This analog processing stage compensates for the limitations of low-resolution ADCs by pre-processing the signals in the continuous-time domain, thereby maintaining signal recovery accuracy even when using power-efficient low-resolution quantization methods.
Solution Approach 2:
The patent changes the processing domain parameters by performing beamforming and spatial filtering in the analog domain (continuous-time) rather than the digital domain (discrete-time). This parameter change allows the system to use low-resolution ADCs while maintaining signal recovery accuracy, as the critical signal processing operations are completed before quantization occurs.
4Device complexity
If task-agnostic beamforming is used, then system simplicity is maintained, but signal recovery performance deteriorates in congested environments
Solution Approach 1:
The patent implements dynamic task-specific optimization where the analog combiner and digital signal processor are jointly optimized based on the specific signal recovery task at hand. The system adapts its beamforming weights and processing parameters according to the actual signals received and the desired recovery objectives, thereby achieving superior performance in congested environments while maintaining reasonable system complexity through automated optimization.
Solution Approach 2:
The patent incorporates feedback mechanisms where the digital signal processor evaluates the quality of signal recovery and feeds this information back to optimize the analog combiner's beamforming weights. This feedback loop enables the system to continuously improve signal recovery performance in congested environments by adapting to changing signal conditions, while maintaining system simplicity through automated closed-loop optimization.
Data Source
AI summary
Some embodiments are directed towards a multiple-input multiple-output (MIMO) receiver system for use with N antennas. The receiver system includes: an analog combiner assembly comprising a matrix of vector modulators applying gain and phase shift to each of N signals being received from the respective antenna and combine said N signals into P corresponding signals, P<N; an array of ADC units, each performing quantization of a respective one of said P corresponding signals with a predetermined bit constrain; and a signal recovery system. The signal recovery system can include a digital signal processor performing task-specific recovery of selected K signals, arriving on the antennas in predetermined input directions, from quantized and filtered digital representation of the N signals being received by the analog combiner assembly; and a control unit. The control unit is adapted to utilize optimized operational data to operate the analog combiner and the digital signal processor.