Sensor-assisted multiple access protocols for wireless networks

This paper describes a neural network-based system for stabilizing Aloha random access networks. A grid of sensors is used to gather energy measurements for the neural network. The neural network has been trained to estimate the number of colliding users in a given slot. This information is used to set the parameters of the backoff algorithm so as to stabilize the network. This information can also be used in conjunction with steerable beam antennas to develop geographically-determined Aloha subchannels, further increasing the throughput of the system.