MSK Equalizer State Segmentation for Lower-Complexity MLSE
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Solution Overview
Problem
Existing MLSE equalizers in wireless communication systems, such as those used in MSK receivers, have limited processing power and memory resources, and fail to exploit all redundancies in the equalization computation, leading to inefficiencies and increased complexity.
Innovation Solution
The Viterbi algorithm is optimized by exploiting the properties of MSK modulation, where symbols can take four possible values, reducing computational complexity by dividing states into real and imaginary hypotheses, pre-computing ISI terms, and advancing the trellis in both forward and backward directions to reuse pre-computed terms, thereby reducing memory requirements and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the Viterbi algorithm is implemented as a state machine with 2^L states to accurately estimate maximum likelihood sequences, then the equalization accuracy is improved, but the computational complexity and memory requirements increase significantly
Solution Approach 1:
The patent segments the 2^L Viterbi states into two separate sets of 2^(L-1) states by exploiting the MSK modulation property where symbols alternately take real or imaginary values. This segmentation reduces the computational complexity at each stage while maintaining the overall equalization accuracy through the two-set state machine architecture.
2Reliability
If all 2^L Viterbi states are processed at each stage to ensure complete sequence estimation, then the reliability of symbol detection is improved, but the processing time and power consumption increase
Solution Approach 1:
The patent divides the processing of Viterbi states into two separate sets, where only 2^(L-1) states are processed at each stage instead of all 2^L states. This segmentation maintains symbol detection reliability through the two-set architecture while doubling the processing speed and reducing power consumption.
3Measurement precision
If the complete Viterbi trellis is advanced at each stage to determine surviving paths for all states, then the accuracy of maximum likelihood sequence estimation is improved, but the memory requirements for storing path metrics increase
Solution Approach 1:
The patent segments the Viterbi trellis into two separate trellises corresponding to two sets of states. This segmentation reduces the memory requirements for storing path metrics by half at each stage, as only 2^(L-1) states need to be stored in each trellis set, while maintaining sequence estimation accuracy through the combined two-set architecture.
4Measurement precision
If pre-computation of ISI terms is performed for all Viterbi states to improve equalization accuracy, then the measurement precision is improved, but the initial computational burden and memory usage increase
Solution Approach 1:
The patent segments the pre-computation of ISI terms into two separate sets corresponding to the two sets of Viterbi states. This segmentation reduces the memory usage for storing pre-computed ISI terms by half, as only ISI terms for 2^(L-1) states in each set need to be stored, while maintaining equalization accuracy through the combined architecture.
Data Source
AI summary
The disclosed invention provides a method, a system and a computer program product for the maximum likelihood sequence estimation of transmitted MSK symbols. The disclosed invention provides a set of optimizations of the Viterbi algorithm for equalizing MSK symbols. The transmitted MSK symbols are alternately real and imaginary. Therefore, based on whether the transmitted MSK symbol is real or imaginary, the disclosed invention divides the set of Viterbi states into two sets of states. The disclosed invention obtains the surviving path only for the first set of states at stages corresponding to real transmitted symbols. A real hypothesis is used to obtain the surviving paths for the first set of states. The disclosed invention also obtains the surviving path only for the second set of states at stages corresponding to imaginary transmitted symbols. An imaginary hypothesis is used to obtain the surviving paths of the second set of states. Therefore, the Viterbi trellis is advanced by considering only half the number of Viterbi states at each stage, leading to computational efficiency.