Reduced Complexity Soft Demapper for Multi-Antenna Systems
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Solution Overview
Problem
Current soft demapper solutions for multi-antenna communication systems face high computational complexity, particularly in maximum likelihood (ML) and iterative ML (iML) demapping, which increases power consumption and latency, especially with higher modulation orders like 4096 QAM.
Innovation Solution
The proposed solution employs an approximate ML criterion for symbol detection, using a reduced candidate set and iterative strategies to achieve near MAP performance with significantly reduced computational complexity, focusing on a subset of constellation points and leveraging lookup tables to derive bit likelihood values, thereby maintaining low complexity even with larger modulation orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full maximum likelihood (ML) or iterative ML (iML) demapping algorithms are used, then detection accuracy and reliability are improved, but computational complexity increases significantly
Solution Approach 1:
The patent segments the constellation points into multiple groups based on their distance from the received signal. Instead of evaluating all N constellation points, the algorithm divides them into groups and only performs detailed evaluation on the most likely group, significantly reducing the number of computations while maintaining detection accuracy.
Solution Approach 2:
The patent applies local quality by assigning different processing levels to different constellation points. Points closer to the received signal (more likely candidates) receive full ML evaluation, while points farther away use simplified evaluation or are discarded, optimizing the trade-off between accuracy and complexity.
2Productivity
If higher modulation orders (e.g., 4096 QAM) are employed, then data transmission rate is improved, but computational complexity and power consumption increase
Solution Approach 1:
For high-order modulations like 4096 QAM, the patent segments the 4096 constellation points into multiple groups based on distance metrics. The algorithm only evaluates a small subset of the most likely candidate points, reducing computational complexity from O(N) to O(log N) or O(1) while maintaining the high data rate benefits of the high-order modulation.
Solution Approach 2:
The patent applies partial action by performing full ML evaluation only on a small subset of constellation points that are most likely to be the transmitted symbol. The remaining points receive simplified or no evaluation, achieving near-ML performance with significantly reduced computational burden suitable for high-order modulations.
3Reliability
If iterative ML (iML) demapping is used to achieve near MAP performance, then detection reliability is improved, but latency and computational burden increase
Solution Approach 1:
The patent segments the iterative demapping process into a limited number of iterations with early termination conditions. By dividing the computation into discrete stages and stopping when convergence criteria are met, the algorithm achieves near MAP performance without the excessive latency of full iterative processing.
Solution Approach 2:
The patent performs partial iterative processing by executing a fixed small number of iterations (e.g., 1-3 iterations) or using early termination when convergence is detected. This provides near MAP performance with significantly reduced latency compared to exhaustive iterative ML demapping.
Data Source
AI summary
An apparatus includes a demapper to receive a number of bit streams received by multiple radio-frequency (RF) antennas. The demapper can compute a first reliability metric associated with a first stream and a second reliability metric associated with a second stream. A channel decoder processes the first and the second reliability metrics to recover decoded data. The demapper is a reduced complexity demapper and uses a symbol subset of the first stream to compute, by employing look-up tables, the second reliability metric for the second stream.