Perturbed Decoder for MIMO Signal Interference Reduction
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Solution Overview
Problem
MIMO wireless systems face challenges in achieving a reasonable trade-off between complexity and performance due to the exponential growth of maximum-likelihood decoder complexity with the number of transmit antennas and symbol constellation size, and existing decoders like space-time chase and list-sphere decoding are limited in multi-user scenarios and dependent on search radius.
Innovation Solution
The introduction of perturbed decoders that pre-process or post-process received signals using randomly generated perturbation vectors to improve the performance of linear decoders such as ZF and MMSE, creating a list of possible transmit symbol vector candidates for hard or soft decision decoding, and utilizing outer channel codes for enhanced performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maximum-likelihood decoding is used to achieve optimal performance in MIMO systems, then decoding performance is improved, but decoder complexity grows exponentially with the number of transmit antennas and symbol constellation size
Solution Approach 1:
The patent segments the decoding process into two stages: first, a linear decoder (ZF or MMSE) provides an initial estimate of the transmit symbol vector; second, a perturbed decoder generates multiple candidate vectors by adding perturbation vectors to the initial estimate. This segmentation reduces complexity compared to exhaustive ML search while maintaining performance through the candidate generation step.
Solution Approach 2:
The patent applies preliminary action by using the linear decoder to provide an initial estimate before the perturbation step. This preliminary estimate serves as the foundation for generating candidate vectors, avoiding the need to search the entire possibility space from scratch and thus reducing overall complexity.
2Device complexity
If list-sphere decoding is used to reduce complexity, then decoder complexity is reduced, but performance becomes dependent on search radius and does not scale well in multi-user scenarios
Solution Approach 1:
The patent uses dynamic perturbation vectors that are randomly generated based on the initial estimate from the linear decoder. Unlike fixed search radius methods, the perturbation magnitude and direction adapt to the specific signal conditions, allowing the decoder to effectively search for candidates without being constrained by a predetermined radius that may not account for multi-user interference variations.
Solution Approach 2:
The patent changes the search parameter from a fixed spherical radius to random perturbation vectors added to the initial estimate. This parameter transformation allows the search space to dynamically adapt to different signal conditions while maintaining a manageable list size for further processing.
3Reliability
If space-time chase decoding is used to improve performance, then decoding performance is improved, but the approach is limited in multi-user scenarios
Solution Approach 1:
The patent creates a universal decoder structure that can handle both single-user and multi-user scenarios. The perturbed decoder generates candidate vectors that can be used for hard decision decoding in single-user modes and soft decision decoding in multi-user modes, making the same basic structure adaptable to different operational contexts without requiring separate specialized decoders.
Solution Approach 2:
The patent incorporates feedback mechanisms where the decoder can select from multiple candidate vectors generated through perturbation. The system uses feedback information about signal conditions and decoding results to determine the best candidate, enabling adaptive performance across different user scenarios while maintaining a unified decoder architecture.
Data Source
Figure 1
AI summary
A decoder adopted to receive a signal transmitted in a communication system, includes one or more of a module adopted to pre-process a received signal to reduce the effect of interference-plus-noise on the received signal before filtering the received signal, and a module adopted to post-process the result of filtering the received signal.