Noise estimation in DSL systems using linear regression

The Digital Subscriber Line (DSL) systems performance tightly depends on noise interference. The users (lines) in the binder create mutual interference (crosstalk), therefore decreasing the rates of all users. Crosstalk noise is more predominant in DSL and its major performance bottleneck is to limit high-speed data rate. This study proposes a new real-time monitoring methodology for noise estimation based on Management Information Base (MIB) metrics. Linear regression is used for fitting, in which input parameters are MIBs and the output is the estimated noise power. The results confirm the possibility of estimating noise with a general equation. Moreover, it is showing the result improvement if a Loop Topology Identification tool is used as prior knowledge.