GPU Channelized Receiver Using OpenCL for Portable Wideband Processing
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Solution Overview
Problem
Existing wideband digital channelized receivers implemented on DSP and FPGA platforms are non-portable and have high development costs, limiting their practicality and efficiency.
Innovation Solution
An embedded GPU-based wideband parallel channelized receiving method is developed using the OpenCL platform, which decimates wideband signals into multiple channels, performs polyphase DFT filtering, and applies FFT to achieve efficient channelization, supporting primary, secondary, and tertiary processing, and is capable of running on various operating systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If DSP and FPGA platforms are used for wideband digital channelized receivers, then processing efficiency is improved, but portability deteriorates and development cost increases
Solution Approach 1:
The patent applies universality by implementing the channelized receiver on GPU platforms that can run across multiple operating systems (Windows, Linux, Android, iOS) through the OpenCL framework. This allows the same hardware to serve multiple functions and platforms, achieving portability while maintaining high processing efficiency through parallel computing capabilities.
Solution Approach 2:
The patent substitutes traditional DSP/FPGA mechanical systems with a software-based OpenCL implementation on GPU hardware. This replacement transitions from dedicated hardware systems to a more flexible software-hardware combination, improving portability while leveraging GPU parallel processing for maintained or enhanced processing efficiency.
2Productivity
If DSP and FPGA platforms are used for wideband digital channelized receivers, then processing efficiency is improved, but development cost increases
Solution Approach 1:
By using OpenCL which is supported by major GPU manufacturers (NVIDIA, AMD, Intel) across multiple operating systems, the patent creates a universal platform that reduces development costs. Developers write once and run anywhere, eliminating the need for separate development teams for different platforms while maintaining high processing efficiency through GPU parallel computing.
Solution Approach 2:
The patent adopts a software-based approach using OpenCL that can be quickly developed, deployed, and modified compared to expensive FPGA/DSP hardware development cycles. This reduces development costs by using more accessible tools and platforms while leveraging the powerful parallel processing of modern GPUs.
3Reliability
If traditional channelized structures are implemented, then signal processing capability is improved, but portability across operating systems deteriorates
Solution Approach 1:
The patent implements universal signal processing capability through OpenCL, which provides consistent performance across Windows, Linux, Android, and iOS platforms. The same channelized processing algorithms run portably on all these systems, maintaining signal processing reliability while achieving cross-platform portability that traditional implementations cannot provide.
Data Source
AI summary
An embedded GPU-based wideband parallel channelized receiving method includes: constructing an OpenCL platform; decimating a wideband signal read in the OpenCL platform at an interval indicated by the number of channels; assigning data in each row to one of multiple work groups for processing; filtering data on each of channels based on a coefficient of a polyphase filter on a branch; multiplying the filtered data by a factor; and performing an FFT on the formed two-dimensional matrix by columns to obtain data outputted from each of the channels.