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 ex-tend the state of the art by showing how to decode non-sparse sig-nals, 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 2 × and 4×, 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%