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—This paper presents a turbo equalization (TEQ) scheme, which employs a radial basis function (RBF)-based equalizer instead of the conventional trellis-based equalizer of Douillard et al. Structural, computational complexity, and performance comparisons of the RBF-based and trellis-based TEQs are provided. The decision feedback-assisted RBF TEQ is capable(More)
Radial Basis Function Network aided Multiuser Detection (RBFN-MUD) schemes are capable of detecting the received signal of all users, even if the channel output states are linearly non-separable. However, their complexity may become excessive which renders their real implementation irrealistic, except when the number of users is low. In this contribution a(More)
—The performance of the proposed radial basis function (RBF) assisted turbo-coded adaptive modulation scheme is characterized in a wideband channel scenario. We commence by introducing the novel concept of the Jacobian RBF equalizer, which is a reduced-complexity version of the conventional RBF equalizer. Specifically, the Jacobian logarithmic RBF equalizer(More)
—The performance of radial basis function-based decision feedback equalized (RBF DFE) burst-by-burst adaptive quadrature amplitude modulation (AQAM) is presented for transmissions over dispersive wide-band mobile channels. This scheme is shown to give a significant improvement in terms of the mean bit error rate (BER) and bits per symbol (BPS) performance(More)
In this contribution a reduced-complexity radial basis function (RBF) aided neural-network based turbo equalization (TEQ) scheme is proposed for employment in a serially concatenated convolutional coded and systematic space time trellis coded (CC-SSTTC) arrangement. A two-path Rayleigh fading channel having a normalised Doppler frequency of 3.3615 x lob5(More)
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