The invention discloses a two-dimensional vacant code index modulation method based on 
machine learning. The two-dimensional vacant code index modulation method mainly comprises the following steps of1) carrying out serial-parallel conversion on the sending information bits u of a transmitting end; 2) establishing an optimal antenna subset based on an SVM, and constructing a 
label and antenna combination mapping table; 3) carrying out symbol modulation and index modulation on the sending information bit u after serial-parallel conversion, thereby determining a transmitting antenna, a modulation symbol and a 
spread spectrum PN code; 4) performing 
spread spectrum on the modulation symbol, and transmitting the 
spread spectrum to a receiving end; and 5) using the receiving end to receive thespread spectrum 
signal and perform the correlation characteristic detection on the spread spectrum 
signal; 6) performing 
estimation detection on the despread 
signal by using the CNN; and 7) demodulating and demapping the estimated 
demodulation symbol and antenna with the PN code index value so as to restore the source information bit. According to the method, the advantages of a spread spectrum technology in 
spatial modulation and code index modulation are combined, the multi-antenna channel link resources are utilized, and due to the fact that the spread spectrum technology is used, the method has certain anti-interference and anti-multipath capacity.