IQ Mismatch Compensation Using Iterative Metric Optimization
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Solution Overview
Problem
Communication systems face performance degradation due to in-phase (I) and quadrature (Q) mismatch (IQMM) in transmitters and receivers, leading to interference and reduced signal-to-interference-plus-noise ratios, which existing technologies have not adequately addressed.
Innovation Solution
An iterative method is employed to optimize IQ mismatch compensator (IQMC) parameter values by generating candidate parameter sets, determining performance metrics such as image rejection ratio (IRR), signal-to-interference-plus-noise ratio (SINR), and signal-to-image ratio (SImR), and updating parameters to maximize these metrics using gradient ascent or descent techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IQ mismatch compensator parameters are set without optimization, then device complexity is reduced, but signal-to-interference-plus-noise ratio deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing optimal IQMC parameter values in a lookup table before actual communication operations. The base station performs iterative optimization during initialization to generate optimal parameter sets for different channel conditions, then directly retrieves pre-determined parameters during data transmission without real-time iteration, eliminating computational complexity while maintaining optimal performance.
Solution Approach 2:
The patent uses copying by creating a lookup table that stores copies of optimal IQMC parameter values derived from iterative optimization. Instead of performing the complex iterative calculation during actual communication, the system copies and retrieves pre-computed parameter sets from the lookup table based on current channel conditions, preserving optimization benefits while avoiding real-time computational burden.
2Reliability
If iterative optimization method is used to maximize performance metrics, then signal quality is improved, but processing time increases
Solution Approach 1:
The patent performs the time-consuming iterative optimization in advance during system initialization or channel condition changes, storing results in a lookup table. During actual data transmission, the system simply retrieves pre-optimized parameters without performing iterative calculations, thus achieving high signal quality without real-time processing delays.
Solution Approach 2:
The patent applies periodic action by performing iterative optimization only when channel conditions change or at predetermined intervals, rather than continuously during data transmission. The lookup table is updated periodically with new optimal parameter sets, allowing the system to maintain high signal quality while minimizing the frequency of computationally intensive operations.
3Reliability
If IQ mismatch compensation is not applied, then device complexity is minimized, but image rejection ratio deteriorates
Solution Approach 1:
The patent pre-computes optimal IQMC parameters for various channel conditions and stores them in a lookup table. The base station retrieves pre-determined parameters based on measured channel conditions without performing real-time iterative optimization, achieving high image rejection ratio while avoiding the complexity of continuous parameter calculation.
Solution Approach 2:
The patent introduces a lookup table as an intermediary between channel condition measurement and IQMC parameter application. The lookup table stores pre-computed optimal parameters and serves as a mediator that translates channel conditions into appropriate compensation parameters without requiring real-time iterative optimization, thus reducing system complexity while maintaining high image rejection performance.
Data Source
AI summary
A method of optimizing at least one IQMC parameter value for an IQMC includes: generating a set of tested IQMC candidate parameter values by performing an iterative method including selecting a first IQMC candidate parameter value for the at least one parameter of the IQMC; determining, using the first IQMC candidate parameter value, a performance metric value that comprises at least one of (i) an image rejection ratio (IRR) value, (ii) a signal-to-interference-plus-noise ratio (SINR) value, or (iii) a signal-to-image ratio (SImR) value; and determining a second IQMC candidate parameter value that is an update to the first IQMC candidate parameter value. The method of optimizing at least one IQMC parameter value for an IQMC further includes determining an IQMC candidate parameter value of the set of tested IQMC candidate parameter values that optimizes the performance metric.