Blind Separation of Weak Object Signals Against the Unknown Strong Jamming in Communication Systems

Abstract

To obtain the mixed weak object signal against the super power signal (jamming) is still an challenging task in modern communication systems. In this paper, a novel framework is designed for weak object signal blind separation against the strong interference signal. To extract the strong interference signal,firstly, we separate the mixed signals with the optimized FastICA algorithm, then, an improved Interference Cancellation algorithm is proposed as reference signal based on the separated strong signal. Next, we separate the weak mixed signals by the improved FastICA algorithm again. Finally, we discuss the performance of the proposed method and verify the novel method based on several simulations. The experimental results demonstrate the effectiveness and robustness of the proposed method.

Robust wireless statistic division multiplexing and its performance analysis

“…Assume that the number of sources is same as that of sensors in receiver. The noisy mathematical model of observed mixtures is always represented as 2,4–27…”

“…With regard to the receiver in WSDM, the source signals are retrieved by blind source separation (BSS) based on independent component analysis (ICA, such as Fastica and Infomax). 1–23 However, the conventional ICA model does not take into account the influence of noise, and the robustness of performance is weak.…”

Minimum BER Criterion and Adaptive Moment Estimation Based Enhanced ICA for Wireless Communications

“…In real scientific applications, many of the observed mixed signals are modeled as a suite of sensors output, with receiving different linear combinations of the underlying source signals. Therefore, the interested source signals are expected to be separated or extracted from the observed data directly with the aid of BSS exempting from extra parameter estimation, such as channel state information and synchronization parameters for wireless receiving processing [4], [7], [9], [10], [12]- [14].…”

“…A typical example can be found in wireless communication, which benefits a lot from BSS by helping wireless communication system arrive at requirements of strong anti-interference and high spectral efficiency due to its blind and adaptive features for future green and intelligent communication implementation. In wireless communication systems, a number of receiving models can be constructed as a BSS framework or conceived as a BSS problem, such as DS-CDMA (direct sequencecode division multiple access) [7], [8], OFDM (orthogonal frequency division multiplexing) [9]- [11], MIMO (multiple input multiple output) [12]- [14] and wireless sensor network (WSN) [23]- [25], cognitive radio [26], and so on [4]. In a general way, those received models can be considered as mixtures of independent source and unknown channel condition.…”