The invention discloses a
deep learning assisted waveform index modulation single carrier communication method, and belongs to the technical field of
wireless communication. According to the method, the
frequency spectrum efficiency and the
system performance are improved by fully utilizing the waveform freedom degree of the single-
carrier system. Cooperative transmission of index information and symbol information is realized by jointly optimizing a
constellation mapping set, a shaping
filter bank and a Bi-LSTM detection network of a receiving end. Specifically, a sending end divides information bits into symbol bits and index bits, the index bits dynamically select a
constellation mapping set and a shaping filter, and the symbol bits generate a
time domain waveform through the selected
constellation and filter. And after a receiving end adopts
frequency domain equalization and matched filtering, joint detection of indexes and symbols is completed through a Bi-LSTM network. According to the method, bit
mutual information can be achieved through end-to-end training optimization, the
signal power and the spectrum template are constrained at the same time, a high-performance and low-
complexity index modulation implementation method is provided for a single-
carrier system, and the method is suitable for a future high-spectrum-efficiency communication scene.