5G-NR Multi-Cell PHY Pipeline for GPU-Parallel Processing
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Solution Overview
Problem
The increasing demand for 5G-NR network processing resources due to the ubiquity of wireless communication devices and expanded infrastructure leads to significant memory and time consumption, particularly in multi-cell environments.
Innovation Solution
Implementing a software PHY library that utilizes parallel processing units (PPUs) like GPUs to accelerate physical layer (PHY) operations, with a hierarchical data organization and batching mechanisms to optimize resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If additional users or computing cells are added to a 5G-NR base station, then network capacity and coverage are improved, but memory and time consumption increase significantly
Solution Approach 1:
The patent segments PHY operations into distinct processing stages organized as a pipeline, with each stage handling specific tasks (e.g., FFT, channel estimation, decoding). This segmentation allows parallel processing of multiple users and cells simultaneously, reducing overall memory consumption by processing data in smaller chunks through different pipeline stages rather than loading all data into memory at once.
Solution Approach 2:
The patent introduces a temporal dimension to data processing by implementing a pipeline architecture where data flows through multiple processing stages over time. This transforms the traditional sequential processing model into a multi-dimensional parallel processing system, enabling simultaneous handling of multiple users and cells while optimizing memory usage at each stage.
2Adaptability or versatility
If additional users or computing cells are added to a 5G-NR base station, then network capacity and coverage are improved, but processing time increases
Solution Approach 1:
By dividing PHY operations into segmented pipeline stages, the system can process multiple users and cells in parallel through different stages simultaneously. This segmentation eliminates sequential processing bottlenecks, maintaining constant processing time per user even as network capacity increases.
Solution Approach 2:
The pipeline architecture ensures continuous processing where each stage continuously receives and processes data from the previous stage without idle time. This continuity allows the system to maintain high throughput and constant processing time per operation, even when handling increased network capacity with multiple users and cells.
3Ease of manufacture
If traditional processing methods are used for multi-cell 5G-NR operations, then implementation is simpler, but computational resource demands become excessive
Solution Approach 1:
The patent implements a universal PHY pipeline framework that can handle multiple PHY operations (FFT, IFFT, channel estimation, decoding, etc.) through a single standardized architecture. This universal pipeline reduces implementation complexity by providing a reusable template while optimizing computational resource usage through parallel processing and efficient memory management across all operation types.
Solution Approach 2:
The pipeline architecture allows dynamic adjustment of processing parameters such as batch size, parallelism degree, and memory allocation based on network conditions and available resources. This flexibility enables the system to optimize computational resource demand while maintaining implementation simplicity through a standardized framework that adapts to different scenarios.
Data Source
AI summary
Apparatuses, systems, and techniques to perform multi-cell physical layer (PHY) processing in a fifth generation (5G) new radio (NR) network. In at least one embodiment, a PHY library implementing a PHY pipeline groups multi-user and/or multi-cell 5G-NR PHY operations for parallel execution as a result of one or more function calls to an application programming interface provided by said PHY library.