Channel Quality Indicator Calculation Using Parameterized Capacity
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Solution Overview
Problem
Current channel quality indicator (CQI) methods in mobile communication systems, such as HSDPA, fail to optimally map actual propagation parameters and transmission size to transmission parameters like transport block size and modulation scheme, and cannot maintain a predetermined block error rate effectively due to linear dependency issues and lack of consideration for resource unit size.
Innovation Solution
A method that uses a parameterized capacity curve, generalizing the Shannon capacity formula, to estimate signal to interference ratio and determine optimal transmission parameters, including transport block size, modulation scheme, and code rate, while maintaining a desired block error rate by adjusting the signal to interference ratio based on resource units and error rate feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a simple linear mapping is used to determine CQI from SIR, then the mapping process is simple and fast, but the transmission parameters cannot be optimally adapted to non-linear SIR dependencies and resource unit sizes
Solution Approach 1:
The patent transforms the CQI determination from a simple linear mapping to a parameter-based calculation using the Shannon capacity formula. Key parameters including SIR, resource unit size, and target block error rate are integrated to compute CQI values that reflect non-linear relationships. This allows optimal adaptation of transmission parameters while maintaining computational feasibility through structured parameterization.
2Device complexity
If CQI mapping does not consider resource unit size, then the mapping process is simpler, but the transmission error rate cannot be optimized for different transmission sizes
Solution Approach 1:
The patent incorporates resource unit size as a critical parameter in the CQI calculation alongside SIR and target block error rate. The Shannon capacity formula is adapted to include resource unit dimensions, enabling the system to optimize transmission parameters specifically for each transmission size. This ensures reliable error rate performance across varying resource allocations while maintaining a systematic approach to mapping.
3Ease of operation
If a fixed SIR step is used between consecutive CQIs, then the mapping is uniform and simple, but it cannot accommodate non-linear SIR dependencies in different communication systems
Solution Approach 1:
The patent replaces fixed SIR steps with a dynamic parameter-based calculation using the Shannon capacity formula. The CQI determination adapts to non-linear SIR dependencies by computing values based on actual SIR measurements, resource unit sizes, and target error rates. This provides system flexibility while maintaining operational simplicity through a standardized calculation framework that automatically adjusts to different conditions.
Data Source
AI summary
Measures for obtaining channel quality indicator (CQI) in a communication system. Such measures may comprise receiving a first transmission, acquiring a number indicative of a size of a subsequent second transmission, estimating a signal to interference ratio based on said received first transmission, and determining transmission parameter information including at least one of a transport block size indicating a number of bits per packet, a modulation scheme and a code rate based on said signal to interference ratio and said number.