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• Built an active noise control window on the top- hung window frame in a real dormitory room. • Investigate how the noise control performance of this ANC system is affected by controllable system variations. • Figure out the optimal system setup. • Investigate the sensitivity of the ANC window system over the secondary path variation caused by varying window opening status. Urban noise mitigation experiment through active noise control window is not commonly carried out in in situ urban setting. This paper outlines our experimental settings of performing active noise control across the open aperture of the top-hung window frame in a dormitory room. A multi-channel adaptive filtered-x least mean square method is implemented in real-time. Experiments and analyses are carried out to investigate how the noise reduction performance of this active noise control window system is affected by the number of reference microphones, the distance between reference microphones and secondary sources, and the distributions of error microphones under practical restrictions of the real system implementation. Variation of the secondary path estimation is another important consideration in active noise control system design. Real-time experiments are carried out to investigate the sensitivity of the ANC window system over the secondary path variation caused by varying window opening status, and whether a generalised secondary path measured in one window opening setting can be applied to other window opening conditions. [ABSTRACT FROM AUTHOR]

• Block coordinate descent notably reduces complexity without degrading performance. • Momentum integration into block coordinate descent greatly improves convergence rate. • Block coordinate descent attains similar noise reduction to McFXLMS in real-time. Multichannel active noise control (MCANC) is widely regarded as an effective solution to achieve a significantly large noise-cancellation area in a complicated acoustic field. However, the computational complexity of MCANC algorithms, such as the multichannel filter-x least mean square (McFxLMS) algorithm, grows exponentially with an increased channel count. Many modified algorithms have been proposed to alleviate the complexity but at the expense of noise reduction performance. Till now, the trade-off between computational complexity and noise reduction performance has limited the practical implementation of MCANC. The block coordinate descent McFxLMS (BCD McFxLMS) algorithm proposed in this paper substantially reduces the computation cost of an MCANC system, while maintaining the same noise reduction performance as the conventional McFxLMS algorithm. Furthermore, a momentum mechanism is integrated into the BCD McFxLMS in practice to improve the convergence speed. The simulation and experimental results validate the effectiveness of proposed algorithms when dealing with noise in a realistic environment. [ABSTRACT FROM AUTHOR]