A systematic analysis is proposed to predict the performance of a typical feedforward single channel ANC headset in terms of the delay, especially the non-causal delay caused by different noise coming directions. First, the performance of a non-causal feedforward system for a band-limited noise is analyzed by using a simplified pure delay model, where it is found that the noise reduction bandwidth is narrowed and the maximum noise reduction is decreased with the increase of the non-causal delay. Second, a systematic method is developed, which can be used to predict the system performance with measured primary and secondary path transfer functions in most practical sound fields and to study the effects of the control filter length and the path delay on the performance. Then, the causality of a typical feedforward active noise control headset with the primary source at 0° and 90° positions in an anechoic chamber is analyzed, and the performance for the two locations predicted by the systematic analysis is shown in good agreements with the experiment results. Finally, an experiment of a typical feedforward active noise control headset in a reverberation chamber is carried out, which shows the validity of the proposed systematic analysis for other more practical sound fields.Active noise control (ANC) headsets apply active control technique to reduce low frequency noise in headsets [1], where many methods have been used, such as analogue feedback controller [2], digital feedforward controller [3], and the hybrid controller combining the digital feedforward technique with feedback technique [4]. This paper is focused on a typical feedforward active headset composed by an external reference microphone, an internal error microphone and a secondary source in the earmuff [3], where the reference microphone senses the reference signal, the filtered-x least mean square (FXLMS) algorithm is used to adapt the digital filter driving the secondary source to minimize the mean square of the noise at the error microphone.The FXLMS algorithm is a popular ANC algorithm due to its robust performance, low computational complexity and ease of implementation. However, the performance depends on many factors, such as the degree of the coherence between the reference signal and the noise signal [5-7], acoustic feedback [7-8], the time-varying property of the primary noise [4,9], the estimation error between the modeling and practical secondary path [10], and the causality caused by the system delay [5]. For feedforward ANC systems, the primary path contains the acoustic delay from the reference microphone to the error microphone, and the secondary path contains the same kind of acoustic delay from the secondary source to the error microphone and the total electrical system delay from the antialiasing filter, analog to digital (AD) converter, digital to analog (DA) converter, reconstruction filter, and one sampling period for processing etc.. The primary path delay should be larger than the total secondary path delay to guarantee a feedfor...