Viterbi Decoder Path Metric Screening for LTE Blind Decoding
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Solution Overview
Problem
The blind decoding process in LTE systems is inefficient due to numerous incorrect decoding attempts, leading to significant time wastage and battery power consumption, as the number of blind decoding attempts is high and many yield useless results due to incorrectly assumed parameters.
Innovation Solution
A method and apparatus that utilize a Viterbi decoder to receive TBCC-encoded data, select candidates, determine final path metric values, and determine early termination of decoding based on PM-related values, thereby reducing unnecessary decoding attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blind decoding is performed for all possible candidates with various aggregation levels and CCE numbers, then the probability of finding the correct control information increases, but the decoding time and power consumption increase significantly
Solution Approach 1:
The patent performs preliminary path metric calculations during the training section before completing the full decoding process. By calculating path metrics for all possible states at intermediate steps and comparing them against threshold values, the system can early-terminate decoding for candidates that are unlikely to be correct, thus reducing overall decoding time while maintaining reliability for promising candidates
Solution Approach 2:
The patent dynamically adjusts the decoding process by changing the evaluation parameter from completing full decoding for all candidates to using path metric values as a filtering criterion. This parameter change allows the system to identify and eliminate incorrect candidates based on their path metric characteristics during the training section, reducing the number of full decoding operations needed
2Reliability
If blind decoding is performed for all possible candidates with various aggregation levels and CCE numbers, then the probability of finding the correct control information increases, but the power consumption increases significantly
Solution Approach 1:
The patent performs preliminary path metric calculations during the training section before completing the full decoding process. By calculating path metrics for all possible states at intermediate steps and comparing them against threshold values, the system can early-terminate decoding for candidates that are unlikely to be correct, thus reducing overall power consumption while maintaining reliability for promising candidates
Solution Approach 2:
The patent dynamically adjusts the decoding process by changing the evaluation parameter from completing full decoding for all candidates to using path metric values as a filtering criterion. This parameter change allows the system to identify and eliminate incorrect candidates based on their path metric characteristics during the training section, reducing the number of full decoding operations needed and thereby reducing power consumption
3Reliability
If the Viterbi decoder completes full decoding for all candidates, then decoding accuracy is maintained, but unnecessary decoding operations waste time and power
Solution Approach 1:
The patent performs preliminary path metric calculations during the training section before completing the full decoding process. By calculating path metrics for all possible states at intermediate steps and comparing them against threshold values, the system can early-terminate decoding for candidates that are unlikely to be correct, thus reducing overall decoding time while maintaining reliability for promising candidates
Solution Approach 2:
The patent extracts the path metric calculation and evaluation as a separate preliminary step from the full decoding process. By separating this evaluation function and performing it during the training section, the system can identify and eliminate incorrect candidates before investing resources in complete decoding operations, thereby improving decoding efficiency
Data Source
AI summary
A mobile device includes a display, a mobile-communication modem including a Viterbi decoder (VD) configured to decode a tail biting convolutional code (TBCC)-encoded data, a memory coupled to the mobile-communication modem, and a wireless antenna coupled to the mobile-communication modem and to receive a Physical Downlink Control Channel (PDCCH). The VD is configured to: receive data encoded by TBCC; select a candidate to initiate a training section; determine final path metric (PM) values of possible states at a last step of the training section; determine a PM-related value based on the final PM values of the possible states; and determine an early termination of a decoding for the candidate based on the PM-related value.


