Low Complexity MLD Decoder for High-Order QAM Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The complexity of maximum likelihood decoding (MLD) in MIMO systems increases significantly with higher MIMO orders and constellation orders, making it difficult to decode signals efficiently in wireless communications.
Innovation Solution
A system and method that utilizes a lower-order QAM decoder for decoding higher-order QAM signals by dividing the constellation diagram into regions of equal size to the lower-order QAM, performing sorted QR decomposition, and offsetting the received signal to center the constellation map, followed by merging bits using a lower-order QAM decoder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full maximum likelihood decoding is used for high-order QAM constellations, then decoding accuracy is improved, but computational complexity increases exponentially
Solution Approach 1:
The patent divides the high-order QAM constellation diagram into multiple non-overlapping sub-constellation regions, each corresponding to a lower-order QAM decoder. By segmenting the decoding task across multiple specialized decoders rather than using one full-complexity decoder, the system achieves accurate decoding while distributing computational load.
Solution Approach 2:
The patent performs preliminary determination of which sub-constellation region the received signal falls into before decoding. This preliminary action allows the system to select the appropriate lower-order QAM decoder in advance, avoiding the need to run all possible decoders and significantly reducing computational complexity while maintaining decoding accuracy.
2Productivity
If higher MIMO orders and constellation orders are used, then data transmission rate is improved, but decoding complexity increases
Solution Approach 1:
The patent segments the high-order QAM constellation into multiple lower-order sub-constellations, allowing the system to use simpler decoders for each segment. This enables the system to support high data rates through high-order QAM while keeping individual decoder complexity manageable through the segmentation approach.
Solution Approach 2:
The patent changes the effective constellation order parameter by mapping high-order QAM signals into multiple lower-order sub-constellations. Each lower-order QAM decoder operates with a reduced constellation order parameter, which exponentially reduces computational complexity while the overall system maintains high data transmission capability.
3Measurement precision
If full MLD calculations are performed, then signal decoding accuracy is improved, but power consumption increases
Solution Approach 1:
The patent performs preliminary determination of the signal's sub-constellation region before initiating full decoding calculations. This preliminary action enables the system to activate only the specific lower-order QAM decoder needed for that region, avoiding power consumption from running all possible decoders while maintaining accurate decoding through the selected decoder.
Solution Approach 2:
By segmenting the decoding function into multiple specialized lower-order QAM decoders, the system activates only one decoder at a time based on the received signal's region. This segmentation approach maintains decoding accuracy while significantly reducing power consumption compared to running full MLD calculations across all possible constellation points.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method and system for performing quadrature amplitude modulation (QAM) decoding of a received signal includes finding for each layer a region in a first constellation diagram of the received signal, the region including a portion of the first constellation diagram, the portion having the same size of a second constellation diagram, and a first constellation order of the received signal is higher than a second constellation order of the second constellation diagram; and, for each layer: finding a first portion of bits based on bits that are constant among constellation points located in the region of the layer; decoding the received signal using a QAM decoder having the second constellation order to obtain a second portion of bits; adjusting the second portion of bits based on the region of the layer; and merging the first portion of bits with the second portion of bits to obtain a decoded symbol.