Link calibration and property estimation in self-managed wireless back-haul networks

Rural areas often lack affordable broadband Internet connectivity, mainly due to the CAPEX and especially the OPEX of traditional wireless carrier equipment, the vast and sparsely populated areas and, notably, the lack of trained personal. Addressing these issues we have developed a self-managed heterogeneous Wireless Back-Haul (WiBACK) architecture which may be deployed to complement or even replace traditional operator equipment. To optimally utilize fixed wireless point-to-point connectivity, its configuration is to be adjusted properly to the characteristics of the wireless channel. Due to lack of trained personal, time constraints during rapid temporary deployments or run-time network reconfigurations, this task must be automated. Some technologies already provide built-in ranging mechanisms, while others require external, often manual configuration. Such mechanisms should optimally exploit the individual PHY and MAC configuration options. The resulting link properties, such as capacity and latency, are utilized to optimally allocate resources for QoS-aware Pipes. Accordingly, in this paper, we present the AI Radio CalibrateLink primitive, discuss its crucial architectural role in separating spectrum from capacity management and present evaluation results of our resource model for IEEE 802.11a links.