Auto-Correlation Bank for Multi-Standard Signal Classification
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Solution Overview
Problem
Conventional signal processing techniques for low power wireless signals, such as Bluetooth Low Energy (BLE) and ZigBee, face challenges in distinguishing and synchronizing with various packet formats in interfering environments, particularly due to limited carrier frequency offset estimation range and susceptibility to continuous wave interference, leading to increased power consumption and complexity in multi-standard radio systems.
Innovation Solution
An adaptive multi-standard signal classification and synchronization system utilizing an auto-correlation bank with different delays and a signal classifier to efficiently distinguish between wireless protocols, including BLE and ZigBee, while compensating for interference sources, and dynamically scaling hardware resources for reduced power consumption and improved reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If auto-correlation technique is used for signal detection, then power consumption is reduced, but carrier frequency offset estimation range is limited and susceptibility to continuous wave interference increases
Solution Approach 1:
The patent segments the signal detection process into two distinct stages: a first stage using auto-correlation for initial signal detection and coarse frequency offset estimation, and a second stage using cross-correlation for refined synchronization and accurate frequency offset estimation. This segmentation allows the system to benefit from the low power consumption of auto-correlation while ultimately achieving the reliable frequency offset estimation range required by the standards.
Solution Approach 2:
The auto-correlation technique is used as a preliminary action to detect the presence of a signal and provide an initial frequency offset estimate before the more computationally intensive cross-correlation process is initiated. This preliminary detection enables the system to avoid performing full cross-correlation when no signal is present, thereby reducing overall power consumption while ensuring accurate frequency offset estimation when signals are detected.
2Measurement precision
If cross-correlation technique is used for signal detection, then synchronization accuracy is improved, but hardware complexity and power consumption increase
Solution Approach 1:
The patent divides the signal processing functionality into two sequential processing paths: a first processing path implementing auto-correlation for initial detection, and a second processing path implementing cross-correlation for refined synchronization. By segmenting the processing into these two paths executed in sequence rather than simultaneously, the patent achieves high synchronization accuracy while controlling hardware complexity through resource reuse and conditional execution.
Solution Approach 2:
The patent designs the signal processing system with universal components that can perform multiple functions. The same correlation processing units are used in both the first auto-correlation path and the second cross-correlation path, depending on which processing stage is active. This multi-functionality reduces hardware complexity by eliminating the need for separate dedicated hardware for each correlation type, while still providing the synchronization accuracy benefits of cross-correlation when needed.
3Reliability
If multiple parallel correlators are used to monitor multiple standards, then signal detection reliability is improved, but power consumption and device area increase
Solution Approach 1:
The patent segments the multi-standard detection process into hierarchical stages: a first stage using auto-correlation that can detect multiple signal types with different preamble structures, and a second stage using cross-correlation that is selectively applied to confirmed signals for standard-specific identification. This segmentation allows reliable multi-standard detection while avoiding the need to run full cross-correlation for all possible standards simultaneously, thereby reducing power consumption.
Solution Approach 2:
The auto-correlation processing serves as a preliminary action that prepares the system for more specific standard identification. By first detecting potential signals across multiple standards using the computationally efficient auto-correlation method, the system can then apply the more power-intensive cross-correlation only to those specific signal candidates that pass the initial detection threshold, significantly reducing overall power consumption while maintaining reliable multi-standard detection capability.
Data Source
AI summary
Adaptive multi-standard signal classification and synchronization is disclosed. Devices, systems and methods include an auto-correlation bank and a signal classifier to efficiently and reliably distinguish signals of wireless protocols, such as Bluetooth, 1 megabit-per-second (Mbps) Bluetooth low energy (BLE), 2 Mbps BLE, long range (LR) BLE, ZigBee (ZB), high-rate ZB, and so on. The auto-correlation bank includes a set of auto-correlators with different delays, which facilitate distinguishing between the different wireless protocols. Exemplary aspects can further distinguish and/or compensate for interference sources, such as WiFi, constant wave (CW) clock sources, and so on. In some examples, a frequency offset of an incoming signal can be output for further signal processing. In a parallel path, a cross-correlation circuit facilitates synchronization to the incoming signal based on a signal type identified by the signal classifier.