Abstract

There have been several techniques proposed to excise the interference in spread spectrum communications using time-frequency distributions (TFDs). TFDs localize any interference both in time and frequency domain, and are idealy suited for interference excision. Unfortunately, the commonly used TFDs suffer from a trade-off between time-frequency (TF) resolution and cross-terms suppression. This paper focuses on a new excision technique based on constructing a positive TFD of the received spread spectrum signal using an adaptive signal decomposition technique. By decomposing a signal into components, the interaction between components can be avoided, and the TFD constructed by combining the TFDs of the individual components would be free of cross-terms. Also, by using Gaussian functions as bases for decomposition, a high TF resolution of interference signals can be achieved. Construction of positive TFDs by signal decomposition techniques facilitates automatic denoising, and extraction of marginal and local properties of a signal such as instantaneous energy, power spectral density, instantaneous frequency and group delay. Interference excision is then achieved by suitably thresholding energy values in the TF plane. Initial results with synthetic models have shown successful performance with linear and quadratic chirp interferences. The interference excisions are highly localized in the TF plane with no cross-terms

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