Relay Precoder Selection for Two-Way MIMO Relay Systems
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Solution Overview
Problem
Current two-way relay systems face challenges in designing low-complexity relay precoders that deliver sufficient performance, particularly in environments with a large number of antennas, as existing methods either fail to meet performance standards or are limited in their applicability.
Innovation Solution
A relay precoder selection method that constructs a candidate set based on two-way MIMO channel information and selects the best-performing precoder from this set, reducing computational complexity while achieving performance comparable to iterative algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If iterative methods are used to design relay precoders, then performance is optimized, but design complexity increases significantly
Solution Approach 1:
The patent segments the relay precoder design into two parts: a structured candidate precoder set generated using GSVD decomposition, and a selection mechanism that evaluates candidates based on performance criteria. This segmentation avoids the need for complex iterative optimization while maintaining good performance through the structured approach.
Solution Approach 2:
The patent changes the design parameter from iterative optimization variables to a finite set of candidate precoders generated by GSVD. By transforming the continuous optimization problem into a discrete selection problem among structured candidates, the complexity is reduced while performance is preserved through careful candidate generation.
2Device complexity
If low-complexity methods like GSVD or Gram-Schmidt orthogonalization are used, then design complexity is reduced, but performance or antenna adaptability is insufficient
Solution Approach 1:
The patent makes the precoder design adaptive by dynamically selecting the best candidate from the GSVD-generated set based on current channel conditions and performance criteria. This dynamic selection mechanism allows the system to adapt to different antenna configurations and channel states without increasing the fundamental complexity of the generation method.
Solution Approach 2:
The patent introduces an intermediary selection mechanism that bridges the simple GSVD generation method and the performance requirement. The selection process acts as an intermediary that evaluates multiple GSVD-generated candidates and chooses the one that best meets performance criteria, thereby compensating for the limitations of the simple generation method.
3Device complexity
If low-complexity methods like GSVD or Gram-Schmidt orthogonalization are used, then design complexity is reduced, but antenna configuration flexibility is limited
Solution Approach 1:
The patent creates a universal precoder design framework based on GSVD that can handle different antenna configurations. The GSVD-based candidate generation and performance-based selection mechanism works universally across various MIMO relay system configurations, making the design adaptable to different numbers of antennas at terminals and relay without requiring method changes.
Data Source
AI summary
This invention provides a relay precoder selection method for two-way amplify-and-forward multiple-input multiple-output (MIMO) relay systems and communication devices using the selection method or the selected relay precoder. According to the relationship between a relay precoder and the singular values of the effective MIMO channels, a set of candidate relay precoders are constructed based on the singular vector subspaces of cascaded MIMO channels, and one of them is selected for meeting a specific design criterion, such as the minimum sum of mean-squared errors, the maximum sum of channel capacities, and the minimum or maximum sum of condition numbers, where the condition number is defined as the ratio of the largest to the smallest singular value of a MIMO channel. As compared with the iterative design methods with the best performance, this invention achieves close performance while requiring much lower computational complexity.