Adaptive CPRL Bandwidth Selection for Phase Noise
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In communication systems, achieving signal lock between transmitters and receivers is challenging due to unique oscillator frequency and phase characteristics, leading to frequency and phase variations, and determining an optimal Carrier Phase Recovery Loop (CPRL) bandwidth is crucial for low data rate applications to balance phase noise tracking and thermal noise susceptibility.
Innovation Solution
A method using a Minimum Mean Square Error (MMSE) algorithm to determine the CPRL bandwidth based on the Signal to Noise Ratio (SNR), employing a Phase-Locked Loop (PLL) and an MMSE module to process phase error vectors and select an optimal bandwidth for coded and un-coded transmissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If narrow loop bandwidth is used in CPRL, then thermal noise susceptibility is reduced, but phase noise tracking capability deteriorates
Solution Approach 1:
The patent implements an adaptive CPRL bandwidth selection mechanism that dynamically adjusts the loop bandwidth based on real-time signal conditions. The system calculates the bandwidth optima using phase error statistics and SNR measurements, then selects from multiple predefined bandwidth values (e.g., 0.01, 0.05, 0.1, 0.5, 1.0 times the symbol rate) to optimally balance phase noise tracking and thermal noise rejection for current operating conditions.
Solution Approach 2:
The system changes the CPRL bandwidth parameter adaptively based on measured signal characteristics. By computing optimal bandwidth values as functions of SNR and phase error variance, and selecting from a range of bandwidth parameters, the system transforms the fixed bandwidth parameter into a variable that adapts to changing channel conditions, thereby resolving the contradiction between noise rejection and tracking performance.
2Reliability
If wide loop bandwidth is used in CPRL, then phase noise tracking capability is improved, but thermal noise susceptibility increases
Solution Approach 1:
The adaptive bandwidth selection mechanism allows the system to dynamically widen the loop bandwidth when phase noise tracking is prioritized (e.g., in high SNR conditions or when rapid phase changes are expected), while automatically narrowing it when thermal noise rejection becomes more critical (e.g., in low SNR conditions). This dynamic adjustment resolves the contradiction by making bandwidth a flexible parameter rather than a fixed compromise.
Solution Approach 2:
The system employs parameter change by selecting from multiple bandwidth values based on calculated optima. When phase noise tracking performance is paramount, the system selects larger bandwidth parameters; when thermal noise susceptibility must be minimized, smaller bandwidth parameters are chosen. This parameter adaptation strategy enables optimal performance in both regimes depending on actual operating conditions.
3Device complexity
If fixed CPRL bandwidth is used, then system complexity is reduced, but performance in varying signal conditions deteriorates
Solution Approach 1:
The system introduces dynamic bandwidth adaptation through an automated selection process that monitors signal conditions (SNR, phase error statistics) and adjusts the CPRL bandwidth accordingly. This dynamic approach maintains low implementation complexity by selecting from a finite set of predefined bandwidth values while achieving adaptive performance that responds to varying signal conditions, thus resolving the contradiction between simplicity and performance.
4Reliability
If adaptive CPRL bandwidth selection is implemented, then performance in low data rate applications is improved, but device complexity increases
Solution Approach 1:
The patent segments the bandwidth selection process into discrete, manageable components: (1) measurement of signal parameters (SNR, phase error), (2) calculation of optimal bandwidth based on segmented formulas, and (3) selection from segmented bandwidth options. This segmentation reduces implementation complexity by breaking down the adaptive selection into modular steps while maintaining improved performance in low data rate applications.
Solution Approach 2:
The system manages complexity by changing only one key parameter (bandwidth) based on measured conditions, rather than redesigning the entire CPRL. By deriving bandwidth optima from simple functions of measurable quantities (SNR, phase error variance) and selecting from predefined values, the system achieves adaptive performance with minimal added complexity, resolving the contradiction for low data rate applications.
Data Source
Figure 1~2
Figure 3~4
Figure 5
AI summary
Systems and methods for carrier phase recovery are provided. One method includes providing a reference signal, detecting an input signal and determining a Signal to Noise Ratio (SNR) of the input signal. The method also includes employing a Minimum Mean Square Error (MMSE) algorithm based on the SNR to determine a Carrier Phase Recovery Loop (CPRL) bandwidth.