MSB-LSB Interleaving for Lower-Complexity Gbps Viterbi Decoding
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Solution Overview
Problem
Current wireless communication systems face challenges in achieving high data rates exceeding Gigabytes per second due to the complexity and hardware requirements of Viterbi decoders, which increase hardware complexity and cost when trying to process billions of sequential Add-Compare-Select operations in real-time.
Innovation Solution
The method involves multi-level coding, where data is partitioned between two encoders for Most Significant Bits (MSBs) and Least Significant Bits (LSBs, with interleaving that simplifies branch metric selection during Viterbi decoding and allows parallel de-interleaving, reducing decoder complexity and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If multiple Viterbi decoders are used in parallel to achieve Gbps data rates, then data transmission speed is improved, but hardware complexity and cost increase significantly
Solution Approach 1:
The patent segments the data stream into multiple parallel channels, each processed by a simplified Viterbi decoder. Instead of using one complex decoder for all data, the system divides the high-rate data stream into lower-rate substreams that can be handled by less complex decoder units operating in parallel, thereby reducing individual decoder complexity while maintaining overall Gbps throughput
Solution Approach 2:
The patent introduces parallel processing dimension by deploying multiple decoder instances simultaneously. Rather than increasing the complexity of a single sequential decoder, the system adds temporal and spatial dimensions through parallel decoder operations, allowing Gbps data rates to be achieved through concurrent processing of multiple data streams
2Reliability
If traditional convolutional encoding with Viterbi decoding is used for Gbps rates, then reliable transmission is achieved, but the processing time exceeds real-time constraints
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing metric values in lookup tables before actual decoding operations. During real-time decoding, the system retrieves pre-computed metrics rather than calculating them on-the-fly, significantly reducing processing time while maintaining the reliability of Viterbi decoding for achieving Gbps data rates within real-time constraints
Data Source
AI summary
A method and apparatus for encoding data for wireless transmission. The invention includes multi-level coding in which data is partitioned between two encoders, one for encoding Most Significant Bits (MSBs) and the other for encoding Least Significant Bits (LSBs). By partition bits separately for the MSBs and LSBs, the complexity of the decoder may be reduced. The MSBs and LSBs are interleaved such that each MSB is a function of just one LSB, simplifying branch metric selection during Viterbi decoding. This also allows parallel de-interleaving by the receiver, which reduces the interleaving latency of the receiver. A block interleaver jointly optimizes the symbol hamming distance of the symbols and the bit hamming distance of each constituent encoder for the MSBs and LSBs.