Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these "actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the "qualityâ of such equilibria.

Standard LoRaWANs leverage pure ALOHA at the medium access control layer which is proved to be a performance bottleneck as the network size scales up. Stimulated by this fact, this work studies the applicability and the performance of Listen Before Talk (LBT) medium access schemes in the context of LoRaWANs; we consider two different implementations of LBT: physical layer LBT based on energy detection only, and MAC layer LBT based on layer-2 frame decoding, and we propose a Markovian framework to evaluate the performance of LoRaWANs under such setting in terms of Data Extraction Rate and average delay experienced by transmitted uplink messages. The proposed framework is also leveraged to assess the performance of “mixed” LoRaWAN scenarios where some devices access the channel according to the standard-compliant ALOHA protocol, while other devices transmit according to LBT.