# Energy Efficiency in Short and Wide-Area IoT Technologies--A Survey
## 3 Energy Efficiency and Consumption Metrics and Models
### Cellular IoT
The average total energy consumption is measured as the sum of the energy consumption of all three cycles weighted by their probabilities. The proposed model was tested by introducing the PSM in the NS3-based NB-IoT simulator provided in [93], which is an adaptation of the LTE physical layer to NB-IoT. Results show a high accuracy in estimating the energy consumption, with the analytical model providing energy consumption estimates that closely match simulation results. A NB-IoT power consumption model was also proposed in [94], aiming at estimating device battery lifetime. A traffic profile that resembles the behavior of sensor devices was applied, leading to data transmitted periodically within a predefined interval. The model estimates the energy consumption during four phases:  
* Phase 1: the UE wakes up and establishes the connection;* Phase 2: Uplink data transmission;
* Phase 3: the UE disconnects and returns to Idle mode;
* Phase 4: the UE is in Idle mode until the next transmission period begins. The device power consumption was estimated according to the model as a function of system parameters including transmit power, uplink and downlink data rates, under several test cases involving PSM and Idle-eDRX (I-eDRX), where the device monitors the paging signal for 1 ms only per discontinuous reception (DRX) period (more details are given in Section 4.2.2). Results showed that, compared to 3 GPP consumption estimates [64], the model provides more accurate vs. less accurate estimates for PSM vs. I-eDRX. An additional model was proposed in [95] in order to evaluate the impact on energy consumption of collisions between transmissions in uplink NB-IoT transmissions. In the model, the Connected mode is divided into random access (RACH) and transmission states. These latter states, together with PSM and Idle states, are used to formulate a semi-Markov chain to model the behavior of periodic transmissions. In particular, the model accounts for the following operations:  
* During PSM, the device is unreachable until a corresponding timer, denoted as \(T_{PSM}\), expires;
* During RACH, the device periodically transmits random access requests to the base station. The device transmits a request for each cycle \(T_{r}\), monitoring the downlink channel for the base station reply;
* During Transmission, the device periodically transfers data to the base station in cycles of duration \(T_{ACK}\), and monitors the narrowband physical downlink shared channel (NPDSCH) to receive a reply, for a maximum of \(N_{max}\) transmissions. The device switches to PSM if a data acknowledgement (ACK) is received from the base station within a cycle, otherwise it goes to Idle;
* During Idle, the device releases its allocated resources, while starting an Idle timer \(T_{IDLE}\) and monitoring the NPDSCH channel for an ACK response. If it receives the ACK during this timer, it switches to PSM, otherwise it switches back to a RACH state. The total energy consumed when a transmission occurs for a duration \(L\) can be evaluated as follows:  
\[E(L)=E_{ACT}(i)+E_{PSM}(L) \tag{12}\]  
where \(E_{ACT}(i)\) is the power consumption during the active period of one transmission for state \(i\), \(L\) is specific duration during which a transmission has occurred, and \(E_{PSM}\) is the power consumption during the PSM state. Simulation results show that the energy consumption decreases by increasing the \(T_{IDLE}\), along with an increase of the communication delays. No experimental validation was however provided for these models.