Algorithm for AGC index management against crowded radio environment
This addresses interference management in wireless communication systems, but it appears incremental as it builds on existing AGC methods with a predictive approach.
The paper tackles the problem of optimizing receiver gain in crowded radio environments by predicting the best automatic gain control index based on historical operating metrics, resulting in improved immunity to interferers during payload reception while maintaining optimal sensitivity.
This paper describes a receiver that uses an innovative method to predict, according to history of receiver operating metrics (packet lost/well received), the optimum automatic gain control (AGC) index or most appropriate variable gain range to be used for next packet reception, anticipating an interferer appearing during the payload reception. This allows the receiver to have higher immunity to interferers even if they occur during the gain frozen payload reception period whilst still ensuring an optimum sensitivity level. As a result, the method allows setting the receiver gain to get an optimum trade-off between reception sensitivity and random interferer immunity.