Coordinate Descent Detector for MIMO Systems
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Solution Overview
Problem
Conventional MIMO systems face challenges in meeting increasing demands for higher throughput without expanding communication bandwidth, due to the computational complexity and resource-intensive matrix operations required for large-scale MIMO systems.
Innovation Solution
The implementation of an integrated circuit that uses an optimized coordinate descent method for adaptive data detection and precoding, which computes preprocessed column values and updates an estimation vector through outer-loop iterations, reducing the need for explicit matrix multiplication and inversion, thereby lowering computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional matrix operations (explicit multiplication and inversion of Hermitian-transposed channel matrix) are used for data detection and precoding, then accurate channel estimation can be achieved, but computational complexity and hardware resource requirements increase significantly
Solution Approach 1:
The patent segments the channel matrix into multiple column vectors and processes each column independently through coordinate descent iterations. Instead of computing the full Gram matrix and its inverse, the algorithm divides the problem into smaller sub-problems that can be solved sequentially, reducing the computational burden while maintaining estimation accuracy.
Solution Approach 2:
The patent precomputes the squared column norms of the channel matrix columns and stores them for reuse during the coordinate descent iterations. This preliminary action avoids redundant calculations in each iteration step, significantly reducing the overall computational complexity while preserving the accuracy of channel estimation.
2Reliability
If conventional matrix operations are used for large-scale MIMO systems, then complete data detection functionality is provided, but power consumption and hardware resources increase
Solution Approach 1:
The patent segments the matrix inversion problem into multiple coordinate descent iterations that process individual columns independently. This segmentation allows the system to achieve complete data detection functionality through iterative refinement while using fewer computational resources and lower power consumption compared to direct matrix inversion methods.
Solution Approach 2:
The patent uses a simplified coordinate descent algorithm that copies and reuses precomputed column norm values throughout the iteration process. This approach provides complete data detection functionality without requiring the full computational power of conventional matrix operations, thereby reducing hardware resources and power consumption.
3Productivity
If communication bandwidth is expanded to meet growing throughput demands, then higher throughput can be achieved, but frequency band competition increases and bandwidth resources are consumed
Solution Approach 1:
The patent changes the computational parameters of the MIMO system by implementing an optimized coordinate descent algorithm with precomputed column norms. This parameter change enables the system to achieve higher effective throughput through more efficient signal processing, allowing existing bandwidth to be utilized more effectively without requiring additional frequency spectrum resources.
Data Source
AI summary
A system includes an integrated circuit configured to communicating data in a channel. A channel matrix for the channel including a plurality of columns is received. A preprocessing step is performed, using a preprocessing unit, to compute a plurality of preprocessed column values corresponding to respective columns. An update step is performed, using an update unit, to update an estimation vector using a plurality of outer-loop iterations of an outer loop. Each outer-loop iteration updates the estimation vector using the plurality of preprocessed column values. An access link process is performed using the estimation vector.