data rate at 164 dB is 0.8 kbps downlink and 0.3 kbps uplink with NB-IoT [1]. The data rate capability needs to be considered from the application development point of view: a low data rate allows sending of only low amounts of data with IoT modules. 14.7 Delay and Capacity High capacity is one of the targets in IoT optimization. The technology should be designed SO that a very large number of IoT modules can be connected to the network. This section illustrates the maximum number of IoT modules that can be supported by the LTE-based IoT solutions. The simulations assume low band LTE deployment at 800 MHz with 10 MHz bandwidth. LTE-M capacity allocation is assumed to be six PRBs and NB-IoT one PRB. A macrocell network is assumed with three different levels of indoor penetration loss: 10, 20, and 30 dB corresponding to close to a window, 14.7 Delay and Capacity UE throughput Downlink LTE-M Downlink NB-IoT Uplink LTE-M Uplink NB-IoT kbps 10 Path loss [dB] Figure 14.14 loT throughput as a function of path loss. average, and deep indoors like a basement. The macrocell network is based on a real operator's network configuration in terms of site location, antenna tilt, and direction. IoT activity is assumed to be one transaction per day. The capacity results can be scaled down if the transmission frequency is higher. Two applications are considered in the evaluation: application 1 with 4 uplink and 4 downlink transmissions and application 2 with 1 uplink transmission and acknowledgment in the downlink. The transmission payload is 128 bytes. First, we estimate the session delay, which is a relevant factor in the system capacity evaluation. Figure 14.15 shows the estimated session delay for the different user Average session delay 10000 Outdoor and road Indoor 10 dB Indoor 20 dB Indoor 30 dB LTE-M, Application 1 LTE-M, Application 2 NB-IoT, Application 1 NB-IoT, Application 2 Figure 14.15 Average loT session delay. 14 Internet of Things Optimization Users per sector 10 000 000 1 000 000 100 000 10 000 1 000 Outdoor and r