Abstract
A well-known receiver strategy for direct-sequence code-division multiple-access (DS-CDMA) transmission is iterative soft decision interference cancellation. For calculation of soft estimates used for cancellation, the distribution of residual interference is commonly assumed to be Gaussian. In this paper, we analyze matched filter-based iterative soft decision interference cancellation (MF ISDIC) when utilizing an approximation of the actual probability density function (pdf) of residual interference. In addition, a hybrid scheme is proposed, which reduces computational complexity by considering the strongest residual interferers according to their pdf while the Gaussian assumption is applied to the weak residual interferers. It turns out that the bit error ratio decreases already noticeably when only a small number of residual interferers is regarded according to their pdf. For the considered DS-CDMA transmission the bit error ratio decreases by 80% for high signal-to-noise ratios when modeling all residual interferers but the strongest three to be Gaussian distributed.
Highlights
The demands on the data rates provided by future mobile communications systems are further increasing especially for the downlink
To reduce complexity we propose a hybrid scheme, where the approximation of the pdf is simplified by considering only the strongest t residual interferers according to their pdf and applying the Gaussian assumption to the weak residual interferers
MF iterative soft decision interference cancellation (ISDIC) employing the common Gaussian assumption and hybrid MF ISDIC as introduced in Sections 3.1 and 3.4, respectively, are compared in the following by means of simulations
Summary
The demands on the data rates provided by future mobile communications systems are further increasing especially for the downlink. For calculation of soft decisions, the distribution of residual interference is commonly assumed to be Gaussian This assumption is accurate according to the central limit theorem [8], when a successive interference cancellation algorithm starts and the number of noteworthy residual interferers is high. Approximating the pdf of interference with a Gaussian mixture is proposed in [14], where the approximation is fixed for the entire transmission In contrast to these approaches we derive an approximation of the pdf of interference based on probabilities of interfering symbols calculated in the receiver.
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