Spread spectrum (SS) communications offers a promising solution to an overcrowded frequency spectrum amid growing demand for mobile and personal communications services. The proposed overlay of spread spectrum signals on existing narrowband users implies strong interference for the SS system. This paper discusses how system performance can be improved by preprocessing to suppress narrowband interference. Linear prediction filters have been proposed since the 1980s for suppression of narrowband interference. In 1991 Vijayan and Poor proposed nonlinear methods of suppressing the narrowband signal with significant increase in the SNR improvement. We derive an enhancement to this nonlinear prediction and achieve further improvement by applying the technique to interpolating filter structures. Finally, we extend results to the case of multiple spread spectrum users and demonstrate how nonlinear filtering can dramatically outperform linear filtering. I. Introduction IEEE Transactions on Com...

Due to the scarcity of frequency allocations for emerging personal communications services, it has been proposed that spread spectrum (SS) signals be used in such services so that they can be overlaid on existing frequency band occupants. Such SS signals would be constrained in power so as not to interfere with pre-existing, narrowband users. In view of this application, suppression of strong narrowband signals that interfere with commercial SS communications systems is being investigated with renewed interest. Previous research has modeled narrowband users as sinusoidal or autoregressive signals, and consequently has advocated use of predictive filtering to suppress such signals. In this paper it is shown that when the narrowband interferer is in fact a digital communications signal these methods are less effective than techniques derived from multiuser communications. In particular, by modeling a narrowband user as a digital signal, optimal and asymptotically (low background noise) o...