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In this paper we study the performance of source matching technique for an optical code division multiple access (OCDMA) system in the presence of source coherence effects and square law detection process. We use a binary-asymmetric channel (BAC) model for an OCDMA system employing an all-optical passive correlator receiver. Source coherence effects lead to relative-intensity-noise (RIN) and phase-induced-intensity-noise (PIIN), which are included in our analysis. Previous studies only considered multiple access interference (MAI) noise, resulting in a Z-channel (where errors only occur for the transmission of data bit zero) model, and neglected RIN and PIIN. The presence of RIN and PIIN leads to errors occurring for both transmitted data bits one and zero, thus a BAC model. We show that source matching gain depends on the normalized source coherence time, defined as the ratio of the optical source coherence time to the bit duration. Our analysis shows that, while MAI limited analysis predicts that increasing the number of users increases the source matching gain, when taking into account RIN and PIIN, source matching gain is both bit rate and source type dependent, and tends to zero for very high numbers of users. Index Terms--Optical code division multiple access (OCDMA), multiple access interference (MAI), source coherency, relative-intensity-noise (RIN), phase-induced-intensity-noise (PIIN), binary asymmetric channel (BAC), optimal source distribution, capacity, source matching.

In this paper we address the problem of suppression of a digital narrow-band interferer in direct-sequence spread spectrum (DSSS) communications. We focus on the adaptive suppression method proposed by Honig, Madhow, and Verdu [1] for wide-band interference, applying it to a narrow-band interferer. We identify the eigenspaces of the system dynamics to analyze the convergence of the adaptive version of the minimum mean square error (MMSE) algorithm for this application. Using this subspace approach we are able to: 1) significantly decrease convergence times via a new constraint on step size in adaptation; 2) introduce a simple parameterization of the mean output energy (MOE) and signal-to-interference ratio (SIR) to compare performance of various receivers; and 3) identify modes of operation where the algorithm will cease to effectively cancel interference. We propose a new adaptive receiver that avoids the convergence anomalies identified, while capitalizing on the new step size for faster convergence. Simulation results to support theoretical results are presented. Index Terms - Blind adaptation, CDMA, direct-sequence spread spectrum communication, multiuser detection, narrowband interference suppression, subspace analysis.

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) optimal linear algorithms for the recovery of the SS bit stream are developed. This technique represents not only a promising new approach to narrowband interference suppression, but also a new application for multiuser detection theory.

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.