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A flexible mathematical framework for adaptive wireless communication waveform design is of importance for the implement of the cognitive radio-based software defined radio (CR-based SDR). As one of the popular models, the &#x201C;spectrally modulated spectrally encoded&#x201D; (SMSE) was proposed to tackle this problem but it cannot be trivially applied to the (massive) multiple input multiple output (MIMO) systems. In this paper, we extend the useful SMSE model into MIMO systems. Inspired by the tensor technique in signal processing and machine learning, we reformulate the desired waveforms as a higher-order tensors, of which the modes correspond to various modulation parameters such as coding chips, frequency and antennas. Beside the waveform design model, we further propose a new semi-blind receiver for the new model. Due the uniqueness of the applied tensor decomposition, we proved that the proposed receiver can jointly estimate the user symbols and channel state information without the aid of pilot sequences. Experimental results demonstrate the effectiveness of the proposed model in various communication scenes and outperforms the baseline systems. approximately 3 dB compared with the ideal receiver.

Tensor Communication Waveform Design With Semi-Blind Receiver in the MIMO System