Design of a Noise-Cancelling Headphone System Using Digital Signal Processing on an ARM Cortex-M4 Microcontroller

Noise pollution in Nigerian urban environments, particularly in Lagos and Kano, adversely affects workers' concentration and health, and affordable active noise cancellation headphone systems remain expensive for most Nigerian consumers. This project designed a digital active noise cancellation system implemented on an STM32F407 ARM Cortex-M4 microcontroller targeting a headphone form factor. The feedforward adaptive noise cancellation algorithm was implemented using the Least Mean Squares adaptive filter with 32 taps, running on the microcontroller's hardware floating-point unit at 168 MHz. A MEMS microphone captured the reference noise signal from the external environment, while a second MEMS microphone at the ear canal captured the residual error signal for LMS adaptation. The anti-noise signal was generated via a DAC and played through the headphone driver in real time. The system was evaluated in a controlled acoustic chamber with broadband noise at 75 dB SPL. Noise reduction performance measured 18.3 dB attenuation in the 100 to 1000 Hz frequency range, where most industrial and traffic noise energy is concentrated. Latency from reference microphone capture to anti-noise output was 1.2 milliseconds, below the 2 millisecond threshold required for effective cancellation. Total processing load on the Cortex-M4 was 62 percent, leaving headroom for additional DSP tasks. The study recommends incorporating a secondary feedback microphone path to improve performance for tonal noise sources such as fan noise and to evaluate the system in an outdoor Lagos traffic environment.

Keywords: active noise cancellation, DSP, ARM Cortex-M4, LMS algorithm, headphone design