Turbo Decoder Iteration Control for HARQ Retransmission Efficiency
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Solution Overview
Problem
Conventional turbo decoders face limitations in maximizing iterative decoding performance due to resource constraints and heat emission issues, leading to suboptimal Cyclic Redundancy Check (CRC) decoding efficiency, especially in software modems with limited resources.
Innovation Solution
The method and apparatus dynamically adjust the number of decoding iterations based on Hybrid Automatic Repeat reQuest (HARQ) information, incrementing iterations for retransmission data and considering early stop conditions to optimize decoding efficiency and reduce frame error rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the maximum number of turbo iterations is set to a large number to maximize decoding performance, then CRC decoding performance is maximized, but heat emission increases and receiver resources are exceeded
Solution Approach 1:
The patent applies dynamics by making the maximum number of iterations adjustable rather than fixed. The system dynamically adapts the iteration count based on channel conditions and signal quality metrics, allowing it to increase iterations when performance is needed and reduce them when resources are constrained, thus resolving the contradiction between maximizing decoding performance and controlling heat emission.
Solution Approach 2:
The patent changes the parameter of maximum iterations from a static value to a dynamically adjustable parameter. By monitoring signal quality and channel conditions, the system modifies the iteration count parameter in real-time, enabling optimal balance between decoding performance and resource consumption including heat emission.
2Productivity
If the maximum number of turbo iterations is fixed to account for total system computation volume and memory capacity, then resource constraints are managed, but turbo iteration-based performance cannot be maximized
Solution Approach 1:
The system transitions from a fixed iteration scheme to a dynamic one where the maximum number of iterations is adjusted based on real-time channel conditions and signal quality. This allows the system to maintain resource management while improving performance by allocating more iterations when channel conditions warrant it.
Solution Approach 2:
The patent modifies the iteration parameter from a constant to a variable that changes based on system conditions. By introducing adaptive parameter adjustment, the system can optimize both computation efficiency and decoding performance simultaneously, rather than being constrained by a fixed parameter setting.
3Reliability
If the maximum number of iterations is increased for retransmission data to improve decoding reliability, then frame error rate is reduced, but computation time and resource usage increase
Solution Approach 1:
The patent applies local quality by differentiating the maximum number of iterations based on the specific characteristics of each transmission instance. Instead of applying a uniform iteration count to all data, the system locally adapts the iteration parameter according to whether the data is initial transmission or retransmission, and according to the specific channel conditions experienced.
Solution Approach 2:
The system performs preliminary assessment of channel conditions and signal quality before determining the maximum number of iterations for decoding. This preliminary action allows the system to pre-determine the appropriate iteration count, avoiding unnecessary computation time while ensuring sufficient iterations are allocated when needed for retransmission data.
Data Source
AI summary
A method and apparatus for controlling iterative decoding in a turbo decoder are provided, in which a maximum number of iterations is determined for current data to be decoded based on at least one of current HARQ information necessary for a HARQ operation of the current data, previous HARQ information about previous data, and early stop information indicating whether iterative decoding of the previous data was early stopped. A turbo decoder iteratively decodes the current data within the maximum number of iterations.