A Novel Intelligent Scenario Identification Algorithm and Channel Characteristics Analysis for 6G Urban Wireless Communications

Urban areas serve as one of the most important scenarios in sixth generation (6G) wireless communications, necessitating comprehensive and in-depth wireless channel characteristics studies. The wireless channels in various 6G urban communication scenarios usually show different characteristics. To provide robust identification across a wide range of 6G urban communication scenarios, we propose a novel intelligent scenario identification algorithm. The proposed algorithm leverages an enhanced multi-layer perceptron (MLP) and autoencoder, utilizing easily accessible environmental physical features as inputs. To enhance identification performance, we employ a series of data pre-processing methods and hyperparameter optimization algorithm. Subsequently, experimental results demonstrate the superior performance of our proposed algorithm compared to the benchmark algorithm. Ultimately, the channel characteristics in all domains, including spatial, temporal, frequency, angle, Doppler, and delay, are studied for these scenarios.