Cross-layer optimization for next-generation WiFi systems

摘要

Systems, methods, and apparatus are described that that increase throughput of a WiFi network. A first method is provided wherein access points monitor and keep track of their states on each resource block (frequency channel and antenna pattern) associated therewith and dynamically select the resource blocks that increase network throughput based on the instantaneous states of the access points. A second method is provided comprising employing Q-learning to determine one or more modifications of operating parameters of a network node based on observed throughput of the network and implementing the one or more modifications at the node. A third method is also provided which combines the first and second methods so as to increase network throughput at both the physical layer and the MAC layer.

主权项

1. A method, comprising:
receiving, by a computing device comprising a processor, samples of performance parameters associated with respective access point devices under different resource assignment configurations, wherein the performance parameters comprise a noise level parameter, a channel utilization parameter, a packet error probability and a busy time ratio; classifying, by the computing device, the respective access point devices as normal, interfered, or heavily loaded, under the different resource assignment configurations, based on the samples of performance parameters; identifying, by the computing device, a resource assignment configuration of the different resource assignment configurations that increases a percentage of the respective access point devices having a classification of normal; and assigning, by the computing device, resources to the respective access point devices based on the resource assignment configuration.