Soft-Decision Generation for Lattice Reduction MIMO Receivers
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Solution Overview
Problem
MIMO receivers based on lattice reduction struggle to generate soft decision information at the symbol level, limiting their deployment in practical scenarios despite their robust detection performance, as they are constrained to hard-decision outputs, which leads to inferior performance compared to soft-output detectors.
Innovation Solution
A method that performs Lattice Reduction linear detection followed by iterative interference cancellation and error compensation to generate soft-decision information, enabling the computation of bit-wise Log-Likelihood Ratios for improved receiver performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Lattice Reduction linear detection is used, then detection performance is improved and complexity is reduced, but the ability to generate soft decision information is lost
Solution Approach 1:
The detection process is divided into two independent stages: first, Lattice Reduction linear detection generates initial symbol estimates; second, iterative interference cancellation refines these estimates to produce soft decision information. This segmentation allows each stage to specialize - the first for robust detection, the second for soft decision generation - thereby resolving the contradiction between detection performance and soft decision capability.
Solution Approach 2:
The patent introduces an intermediary iterative interference cancellation process between the Lattice Reduction detector and the final soft decision output. This intermediary takes the hard decisions from the LR detector, uses them to cancel interference, and generates refined soft decision information, thus bridging the gap between the hard-decision nature of LR detection and the soft decision requirements of practical systems.
2Measurement precision
If iterative interference cancellation is performed, then soft decision information quality is improved, but computational complexity increases
Solution Approach 1:
The iterative interference cancellation is performed for a limited number of iterations rather than exhaustively, providing sufficient soft decision quality improvement without incurring excessive computational complexity. This partial action approach achieves the necessary precision enhancement while controlling the complexity increase within acceptable limits for practical deployment.
Data Source
AI summary
Embodiments of the present disclosure relate to a method, an apparatus and a computer readable storage medium for generating soft-decision information for a receiver. In example embodiments, a method is provided. The method includes receiving, at a first device, a signal from a second device, the signal corresponding to a group of symbols transmitted from the second device; determining, by performing Lattice Reduction linear detection on the signal, a first group of estimated symbols for the group of symbols; determining, by performing iterative interference cancellation on the first group of estimated symbols, a second group of estimated symbols for the group of symbols; and generating, based on the second group of estimated symbols, soft-decision information about the group of symbols for use by a decoder at the first device. Embodiments of the present disclosure can improve the receiver performance with reduced complexity.