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This paper investigates the design and analysis of minimum mean square error (MMSE) turbo decision feedback equalization (DFE), with expectation propagation (EP), for single carrier modulations. Classical non iterative DFE structures have substantial advantages at high data rates, even compared to turbo linear equalizers -interference cancellers (LE-IC), hence making turbo DFE-IC schemes an attractive solution. In this paper, we derive an iterative DFE-IC, capitalizing on the use of soft feedback based on expectation propagation, along with the use of prior information for improved filtering and interference cancellation. This DFE-IC significantly outperforms exact turbo LE-IC, especially at high spectral efficiency, and also exhibits various advantages and performance improvements over existing variants of DFE-IC. The proposed scheme can also be self-iterated, as done in the recent trend on EP-based equalizers, and it is shown to be an attractive alternative to linear self-iterated receivers. For time-varying (TV) filter equalizers, an efficient matrix inversion scheme is also proposed, considerably reducing the computational complexity relative to existing methods. Using finite-length and asymptotic analysis on a severely selective channel, the proposed DFE-IC is shown to achieve higher rates than known alternatives, with better waterfall thresholds and faster convergence, while keeping a similar computational complexity.

An original expectation propagation (EP) based message passing framework is introduced, wherein transmitted symbols are considered to belong to the multivariate white Gaussian distribution family. This approach allows deriving a novel class of single-tap frequency domain (FD) receivers with a quasi-linear computational complexity in block length, thanks to Fast-Fourier transform (FFT) based implementation. This framework is exposed in detail, through the design of a novel double-loop single-carrier frequency domain equalizer (SC-FDE), where self-iterations of the equalizer with the demapper, and turbo iterations with the decoder, provide numerous combinations for the performance and complexity trade-off. Furthermore, the flexibility of this framework is illustrated with the derivation of an overlap FDE, used for time-varying channel equalization, among others, and with the design of a FD multiple-input multiple-output (MIMO) detector, used for spatial multiplexing. Through these different receiver design problems, this framework is shown to improve the mitigation of inter-symbol, inter-block and multi-antenna interferences, compared to alternative singletap FD structures of previous works. Thanks to finite-length and asymptotic analysis, supported by numerical results, the improvement brought by the proposed structures is assessed, and then completed by also accounting for computational costs.

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Today link-to-system (L2S) interfaces are more and more used in order to speed up complete system-level simulations. In this paper a simple extension to generic incremental redundancy (IR) hybrid automatic repeat request (HARQ) strategies is presented for two well-known L2S interfaces: the exponential effective SNR metric (EESM) and the mutual information effective SNR metric (MIESM). Then we focus on the problem of the L2S interface tuning, which is necessary to achieve the highest accuracy of the prediction models. The standard calibration procedure is compared with a new method, based on the average (over channel and noise) physical (PHY) layer performance. The latter, called average calibration procedure, is less time consuming than the standard procedure. Moreover, we show by simulation that the optimal calibration factors, calculated with the two methods, converge to close values thus obtaining equivalent prediction accuracy for the same L2S interface.