Uplink Grant Detection Using Probability Metrics and CRC
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Solution Overview
Problem
Current wireless communication systems face issues with incorrect interruption of uplink transmissions due to high probabilities of wrong grant detection, leading to collisions and inefficiencies in scheduling, particularly in the context of the Enhanced Dedicated Channel (E-AGCH) used in wireless devices.
Innovation Solution
A method is introduced that involves decoding a sequence of bits from a received signal to determine a log-likelihood probability metric, comparing it to a threshold, and performing a cyclic redundancy code (CRC) check to differentiate between a grant sequence intended for the wireless device and noise, thereby reducing the likelihood of incorrect interruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional grant detection methods are used on the E-AGCH channel, then the system can maintain simple signaling and basic scheduling functionality, but the probability of wrong grant detection remains high leading to incorrect interruption of uplink transmissions
Solution Approach 1:
The patent applies preliminary action by performing preliminary decoding and probability metric calculation on the received grant sequence before making the final grant detection decision. The wireless device calculates log-likelihood ratios for each bit position and determines a probability metric indicating whether the sequence corresponds to a grant or noise, before proceeding with CRC verification. This preliminary assessment reduces the probability of wrong detection by filtering out noise sequences early in the detection process.
Solution Approach 2:
The patent replaces conventional hard decision decoding with soft decision decoding based on probability metrics. Instead of directly determining whether a received sequence is a grant or noise using traditional methods, the system uses log-likelihood ratio calculations and probability metric comparisons to assess the likelihood of grant presence. This substitution of mechanical detection with probabilistic analysis significantly improves detection reliability while managing complexity through efficient mathematical operations.
2Reliability
If the system uses simple CRC verification alone for grant detection, then the processing is fast and simple, but the probability of wrong grant detection remains high causing collisions and transmission interruptions
Solution Approach 1:
The patent applies segmentation by dividing the grant detection process into distinct stages: preliminary decoding to calculate probability metrics, probability threshold comparison, and final CRC verification. By segmenting the detection process, the system can perform probability-based filtering first to eliminate obvious noise sequences, then apply CRC verification only to promising candidates. This reduces wrong detection probability while managing processing time through staged verification.
Solution Approach 2:
The patent performs preliminary probability metric calculation and threshold comparison before final CRC verification. This preliminary action filters out sequences that are unlikely to be grants based on their probability metrics, reducing the number of sequences requiring full CRC verification. The approach balances reliability improvement with time management by applying computationally intensive probability analysis only when necessary.
Data Source
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AI summary
A method and system to reduce a probability of incorrect interruption of an uplink transmission of a wireless device are disclosed. According to one aspect, decoding of a sequence of bits obtained from a signal received by the wireless device is performed without knowing whether the sequence corresponds to one of a grant for uplink transmission and noise. Decoding of the sequence of bits is performed to determine a probability metric associated with a first m bits of the sequence, where m is an integer greater than 1. The probability metric is compared to a threshold. The received signal is interpreted as having a grant sequence if the probability metric is greater than the threshold. The received signal is interpreted as noise if the probability metric is not greater than the threshold.