Optimization of Precoded FTN Signaling with MMSE-Based Turbo Equalization.

Faster-than-Nyquist signaling (FTNs) is capable of improving the signaling rate of communication system, while yielding the inter-symbol interference (ISI) complicating the receiver design. However, due to the unavoidable detection performance degradation when compression factor τ drops considerably below the Mazo limit, the achievable gain is limited. In this paper, preceding the FTN modulation, a precoding based data spreading is utilized to introduce an artificial interference, which aims to support a smaller τ that corresponds to achieving a higher capacity, at the cost of detection complexity. Further, we optimize the precoder by minimizing the mean square error (MSE) of the equalizer's output. Meanwhile, the problem is transformed and reformulated as a non-convex quadratically constrained and quadratic programming with one constraint (QCQP-1), where the consensus-alternating directions method of multipliers (ADMM) algorithm is utilized to iteratively pursue the solution. Simulation results justify the proposed scheme, where the capacity of 64-, 128-, and even 256-QAM Nyquist signaling can be achieved by precoding the 16-QAM FTNs, even without SNR loss at bit error rate (BER) of 10⁻⁵.