Exclusive-Region-Map-Based Medium Access Control in Mobile Networks With Directional Antennas Through Deep Interference Learning

The medium access control (MAC) design in mobile networks with directional antennas is challenging due to the difficulty of defining the exact RF interference range between two neighboring directional links and the frequent changes of interference range due to node mobility. This research targets directional data reception (Rx) and transmission (Tx) coordination issues based on the computation of directional interference ranges from nearby directional links. An innovative MAC mechanism is designed with three features: (1) ER-map , i.e., the spatial expression of exclusive region (ER) model in the format of a heatmap. The ER-map helps to determine the directional interference range in typical communication scenarios. Different ER-map cases are analyzed based on the spatial layout differences for two nearby directional links. (2) Spatio-temporal ER-map evolution prediction: a Spatio-Temporal Residual Network (ST-ResNet+) model is used to describe the spatial correlations (for the ERs among neighboring links) and temporal correlations (for the ERs across different time instants) as well as the ER map evolution patterns. Such a Deep ST-ResNet+ model is used to predict the next-time ER map’s snapshot. (3) Optimized directional MAC protocol based on ER map predictions : The ST-ResNet+ prediction results are used to determine the MAC operations, such as Tx/Rx schedule arrangement in the one-hop area, sending rate adjustments, etc. Comprehensive simulations are conducted to validate the throughput efficiency for the proposed directional MAC scheme.