Analysis of deep learning methods improves signal detection in spatial modulation systems, indicating enhanced performance metrics like spectral efficiency.
Key Points
Signal detection improves with deep learning in spatial modulation systems, addressing inter-channel interference.
Results show advancements in metrics such as bit error rate and time complexity, supporting AI applications in communications.
Analysis includes trade-offs between performance, BER, and time complexity within neural network training.
Future research directions highlight challenges that remain in practical implementations of these methods.