Based on the polynomial phase-modulating sequences algorithm, this paper presents two schemes for the application of CDMA with polynomial phase signals to improve the signal separation performance. Simulation results...Based on the polynomial phase-modulating sequences algorithm, this paper presents two schemes for the application of CDMA with polynomial phase signals to improve the signal separation performance. Simulation results illustrate the proposed approach have 1～3?dB improvement about signal-to-interference and noise ratio in most environment, compared with the PPS algorithm.展开更多
Blind source extraction （BSE） is particularly at- tractive to solve blind signal mixture problems where only a few source signals are desired. Many existing BSE methods do not take into account the existence of nois...Blind source extraction （BSE） is particularly at- tractive to solve blind signal mixture problems where only a few source signals are desired. Many existing BSE methods do not take into account the existence of noise and can only work well in noise-free environments. In practice, the desired signal is often contaminated by additional noise. Therefore, we try to tackle the problem of noisy component extraction. The reference signal carries enough prior information to dis- tinguish the desired signal from signal mixtures. According to the useful properties of Gaussian moments, we incorporate the reference signal into a negentropy objective function so as to guide the extraction process and develop an improved BSE method. Extensive computer simulations demonstrate its validity in the process of revealing the underlying desired signal.展开更多
文摘Based on the polynomial phase-modulating sequences algorithm, this paper presents two schemes for the application of CDMA with polynomial phase signals to improve the signal separation performance. Simulation results illustrate the proposed approach have 1～3?dB improvement about signal-to-interference and noise ratio in most environment, compared with the PPS algorithm.
文摘Blind source extraction （BSE） is particularly at- tractive to solve blind signal mixture problems where only a few source signals are desired. Many existing BSE methods do not take into account the existence of noise and can only work well in noise-free environments. In practice, the desired signal is often contaminated by additional noise. Therefore, we try to tackle the problem of noisy component extraction. The reference signal carries enough prior information to dis- tinguish the desired signal from signal mixtures. According to the useful properties of Gaussian moments, we incorporate the reference signal into a negentropy objective function so as to guide the extraction process and develop an improved BSE method. Extensive computer simulations demonstrate its validity in the process of revealing the underlying desired signal.
