基于FDM阵列技术的双通道语音增强方法

为了抑制小型语音通信设备中的方向性噪声干扰问题,提出一种双通道的语音增强算法.该方法基于一阶差分麦克风(first-order differential microphone, FDM)阵列,并结合单通道的谱增强技术,可以同时提取语音和噪声估计,并能够实时地修正噪声谱.与现有的双通道语音增强技术相比,该算法可以获得2~6 dB的输出信噪比增益,且计算量减少了2/3.仿真结果表明: 该方法有效地改善了算法的噪声消除性能,且更适用于实时的语音增强系统.     

Particle-Based Iterative Blind Receiver for Orthogonal Frequency- Division Multiplexing with Frequency Offset

Orthogonal frequency-division multiplexing （OFDM） systems are sensitive to carrier frequency offset （CFO） which introduces intercarder interference and significantly degrades system performance. This paper describes an iterative blind receiver consisting of a sequential Monte Carlo detector, a CFO estimator, and a compensator to reduce intercarrier interference. The framework is of low complexity due to the separation of tasks in a joint detection problem. In addition, the CFO estimator utilizes soft output of the sequential Monte Carlo detector, which reduces the information loss caused by hard decisions and can obtain the CFO estimate in only one OFDM symbol. Simulation results demonstrate the effectiveness of the algorithm.     

A Novel Minimum Output Variance Estimator for Carrier Frequency Offset in OFDM Systems

In orthogonal frequency-division multiplexing (OFDM) systems, the carrier frequency offset (CFO) destroys the orthogonality among subcarriers which degrades system performance. Various CFO estimation methods have been developed to compensate for the CFO at the receiver. This paper describes a novel minimum output variance method for OFDM systems with CFO in additive white Gaussian noise channels. This method utilizes the phase and the amplitude of the received signal and reduces the mean square error of the CFO by about 3 dB compared with the original minimum output variance method.