Enfold: downclocking OFDM in WiFi

Dynamic voltage and frequency scaling (DVFS) has long been used as a technique to save power in a variety of computing domains but typically not in communications devices. A fundamental limit that prevents decreasing the clock frequency is the Nyquist(-Shannon) sampling theorem, which states that the sampling rate must be twice the signal bandwidth. Recently, researchers have leveraged compressive sensing to demonstrate the possibility of decoding a sparse signal below Nyquist rate. In this work, we dramatically extend the state of the art by showing how to decode non-sparse signals, in particular, OFDM systems at sub-Nyquist rates. We exploit the aliasing that results from under-sampling and observe that there exists well-defined structure in terms of how OFDM signals are "folded up" under aliasing. Based on our observations, we present Enfold, which allows existing WiFi chipsets to decode standards-compliant WiFi frames while operating at 50% and 25% of their rated clock rate. Our design is able to attain greater than 96% and 83% raw packet reception rates for moderate SNR while reducing the clock rate by 2x and 4x, respectively. Moreover, our approach can be easily applied to other communication systems based on OFDM modulation. When evaluated on popular smartphone app traces, Enfold reduces energy consumption by up to 34%.