The present invention incorporates reinforcement learning into a beam sweeping framework to select the appropriate set of beams to transmit reference signals in a predefined time interval for covering an angular region. More specifically, a network node starts a learning process to determine the most appropriate subset of beams from a large set of available beams (codebook) to communicate with an associated network node over a radio channel. The transmitter node acquires knowledge from its interaction with other nodes of the wireless network to perform beam sweeping with reduced signaling overhead and latency. More specifically, other advantages, the invention improves the beam management in higher carrier frequencies.