Multi-Mode FFT Architecture for Low Power Wireless Processing
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Solution Overview
Problem
Conventional wireless devices face challenges in achieving broadband performance with low power consumption and multi-mode communication capabilities, as existing ASIC and DSP architectures are inflexible and power-intensive, leading to short battery life and high costs.
Innovation Solution
A method and system for performing Fast Fourier Transforms (FFTs) in a multi-mode wireless processing system, utilizing a Radix-4 FFT engine, Twiddle factor manipulation, and efficient buffer management to reduce power consumption and silicon cost, while supporting multiple networking standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional ASIC or DSP architectures are used to achieve broadband performance, then data rate capability is improved, but power consumption increases and battery life decreases
Solution Approach 1:
The patent implements dynamic operation modes that allow the wireless device to switch between different processing states (active, idle, sleep) based on traffic conditions. The system dynamically adjusts its operational characteristics to match actual demand, enabling broadband capability when needed while conserving power during low-activity periods. This dynamic adaptation resolves the contradiction by making the system flexible rather than statically power-intensive.
Solution Approach 2:
The invention changes operational parameters such as clock frequency, processing mode, and buffer management strategies to optimize the balance between data rate and power consumption. By adjusting these parameters dynamically based on traffic conditions, the system can achieve broadband performance when required while operating at lower power levels during normal conditions, thus resolving the contradiction between speed and energy use.
2Adaptability or versatility
If multiple wireless networking technologies are supported in a single device, then adaptability is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent implements a universal processing architecture that can handle multiple wireless standards (802.11, Bluetooth, UWB, WiMax, 3G/4G) through a single multi-mode wireless processing system. Rather than implementing separate dedicated circuits for each standard, the system uses a unified processor that can be dynamically configured to support different protocols, thereby reducing overall device complexity while maintaining multi-mode capability.
Solution Approach 2:
The system employs dynamic reconfiguration capabilities that allow the processing circuitry to adapt its structure and behavior based on which wireless standard is currently being used. This dynamic approach enables a single device to provide multiple wireless capabilities without permanently incorporating all possible processing circuits, thus reducing complexity while maintaining versatility.
3Productivity
If conventional FFT implementation is used, then processing capability is achieved, but power consumption and silicon cost increase
Solution Approach 1:
The patent segments the FFT processing into multiple stages with different levels of computational intensity. By dividing the overall transform into sequential stages that can be executed with varying resource allocation, the system achieves necessary processing capability while minimizing peak power consumption and reducing the silicon area required for the complete FFT implementation.
Solution Approach 2:
The invention implements partial FFT processing where only the necessary portion of the full transform is computed based on actual traffic conditions and buffer states. Rather than always performing complete FFT operations, the system computes only what is needed at any given moment, thereby reducing power consumption and silicon cost while maintaining adequate processing capability for broadband performance.
Data Source
AI summary
A system and method Fast Fourier Transform (FFT) method in a multi-mode wireless processing system. The method can include loading an input vector into an input buffer, initializing a second counter and a variable N, where N=log2 (input vector size), and s is the value of the second counter, performing an FFT stage, and comparing s to N and performing additional FFT stages until s=N. Performing the FFT stage can include performing vector operations on data in the input buffer and sending results to an output buffer, the data in the input buffer comprising a plurality of segments, advancing the value of the second counter; and switching roles of the input and output buffers. The vector operations can include performing Radix-4 FFT vector operations on the four input data at a time and multiplying the resulting output vectors with a Twiddle factor.