5G NR Channel Equalization With Parallel MMSE for MIMO Latency
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Solution Overview
Problem
Existing technologies face challenges in efficiently processing 5G New Radio signals due to signal impairments such as time-selective and frequency-selective artifacts, noise, and interference, particularly in MIMO communication systems, which require improved signal processing techniques.
Innovation Solution
Utilizing graphics processing units (GPUs) or parallel processing units (PPUs) for channel equalization of 5G New Radio signals, employing minimum mean squared estimation (MMSE) algorithms adapted for parallel processing, and performing slot-level or sub-slot-level equalization through techniques like Cholesky or LU factorization to minimize transmission errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional sequential processing is used for channel equalization, then processing accuracy can be maintained, but processing speed and latency increase
Solution Approach 1:
The patent divides the channel equalization process into independent parallel tasks that can be executed simultaneously on multiple processing units. The received signal matrix is partitioned across multiple GPU/PPU cores, with each core processing a subset of the data independently, thereby achieving speedup while maintaining manageable complexity through modular design
Solution Approach 2:
The patent transitions from sequential one-dimensional processing to parallel multi-dimensional processing by utilizing the spatial dimension of GPU/PPU architectures. Multiple processing cores operate simultaneously on different portions of the signal matrix, effectively adding a parallelism dimension to the processing architecture
2Productivity
If parallel processing is implemented for channel equalization, then processing speed improves, but computational complexity and resource requirements increase
Solution Approach 1:
The patent extracts the computationally intensive matrix operations from the main processing flow and delegates them to specialized GPU/PPU hardware accelerators. By separating the parallel computation tasks from the control logic, the system achieves high throughput while keeping the overall system complexity manageable through dedicated hardware modules
Solution Approach 2:
The patent utilizes the redundant processing cores inherent in GPU/PPU architectures to create multiple copies of the equalization computation engine. Each core performs identical operations on different data partitions, achieving linear scalability in throughput while the complexity of individual processing units remains constant
3Productivity
If MIMO communication is used to increase data rate, then communication capacity improves, but signal processing challenges and interference increase
Solution Approach 1:
The patent implements minimum mean squared error (MMSE) equalization that uses feedback from channel state information to optimally suppress interference. The equalizer coefficients are computed based on feedback from channel estimates, allowing the system to adaptively cancel out multi-user and multi-antenna interference while maintaining high data rates
Solution Approach 2:
The patent transforms the complex MIMO signal processing problem into a series of simpler parallel computations by changing the processing parameters - specifically by working with pre-computed channel correlation matrices and using eigen-decomposition to diagonalize the interference covariance matrix, thereby simplifying the interference suppression task
Data Source
AI summary
Apparatuses, systems, and techniques to perform signal processing operations in a fifth generation (“5G”) radio signal. In at least one embodiment, one or more processors equalize, in parallel, one or more 5G radio signals.