MIMO Receiver Signal Detection Without Square Root Calculation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The complexity of calculations in Multiple Input Multiple Output (MIMO) systems increases with the number of antennas, making it difficult to implement efficient signal detection due to the need for frequent pseudo-inverse matrix calculations in techniques like Successive Interference Cancellation (SIC).
Innovation Solution
The use of Zero Forcing-Sorted QR Decomposition (ZF-SQRD) and Minimum Mean Square Error-SQRD (MMSE-SQRD) methods transforms orthonormal matrices into orthogonal matrices using a diagonalized normalization matrix, eliminating the need for square root calculations and simplifying the detection process by performing Successive Interference Cancellation (SIC) with orthogonal matrices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Successive Interference Cancellation (SIC) is used to detect transmission signals in MIMO systems, then signal detection capability is improved, but calculation complexity increases due to repeated pseudo-inverse matrix calculations
Solution Approach 1:
The patent changes the mathematical parameters by transforming the channel matrix into an upper triangular form through QR decomposition, which converts the pseudo-inverse calculation into simpler operations. By changing the representation of the channel matrix from general form to triangular form, the complexity of calculating pseudo-inverses multiple times is eliminated while maintaining SIC functionality.
Solution Approach 2:
The patent replaces the mechanical system of repeated pseudo-inverse matrix calculations with a more efficient mathematical approach using QR decomposition. Instead of computing pseudo-inverses multiple times, the system performs a single QR decomposition followed by simpler triangular matrix operations, substituting a complex computational process with a simpler one.
2Productivity
If the number of antennas is increased to improve data transmission capacity, then spatial multiplexing gain is improved, but calculation complexity increases making implementation difficult
Solution Approach 1:
The patent changes the mathematical parameters by using QR decomposition to transform the channel matrix into an upper triangular form. This parameter transformation allows the system to handle increased numbers of antennas efficiently, as the triangular structure enables simpler and faster calculations compared to general matrix operations, thus maintaining implementation feasibility even as antenna count increases.
Solution Approach 2:
The patent segments the matrix decomposition process into distinct steps: QR decomposition into orthogonal and upper triangular matrices, followed by separate operations on these matrices. This segmentation allows for more efficient computation and easier implementation when dealing with larger antenna configurations, as each segment can be optimized independently.
Data Source
AI summary
A Multiple Input Multiple Output (MIMO) receiver and a signal detection method thereof are provided. Since no square root calculation needs to be performed when a calculation for detecting a transmission signal is performed using a Zero Forcing-Sorted QR Decomposition (ZF-SQRD) algorithm and a Minimum Mean Square Error-Sorted QR Decomposition (MMSE-SQRD) algorithm, the complexity of a calculation for detecting a transmission signal under a MIMO channel environment can be reduced.