Spectrally efficient FDM (SEFDM) was proposed as a spectrally efficient scheme. An iterative fast Fourier transform (FFT) detector jointly operating with a channel decoder was also proposed for coded SEFDM. Unfortunately, the iterative FFT detector requires relatively high complexity for some bandwidth compression factors. A new detection scheme for the coded SEFDM is proposed. In the proposed scheme, the inter-carrier interference is iteratively estimated and cancelled in frequency domain. The proposed scheme not only offers virtually identical performance but also requires less complexity compared with the iterative FFT detector.
A faster-than-Nyquist (FTN) transmission scheme has been attracting great attention as a spectral efficient transmission scheme. In the FTN transmission scheme, modulated symbols are transmitted at a rate higher than Nyquist rate and thus, a performance loss due to the inter-symbol interference (ISI) is unavoidable. To minimize the performance loss in the FTN transmission scheme, parameters should be carefully optimized. Unfortunately, simulation-based parameter optimization requires significant amount of time and computing power, especially for 2-dimensional FTN systems. In this paper, we propose a 2-dimensional FTN transmission scheme using the optimized parameters based on numerical analysis and simulation results on the ISI. Compared with the conventional Nyquist system, the proposed 2-dimensional FTN transmission scheme not only offers virtually identical bit error performance but also offers higher spectral efficiency.
In this paper, we propose an inter-symbol interference (ISI) estimation scheme based on the maximum a posteriori (MAP) algorithm for faster-than-Nyquist (FTN) systems. Unfortunately, the ISI estimator based on the MAP algorithm requires relatively high computational complexity. To reduce the complexity of the MAP based ISI estimator, we propose a hybrid ISI estimation scheme based on the MAP and successive interference cancellation (SIC) algorithms. The proposed scheme not only offers good ISI estimation performances but also requires reasonably low complexity.
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