Can LTE-A Support Real-Time Smart Meter Traffic in the Smart Grid?

The chapter investigates the scheduling load added on a long-term evolution (LTE) and/or LTE-Advanced (LTEA) network when automatic meter reading (AMR) in advanced metering infrastructures (AMI) is performed using internet of things (IoT) deployments of smart meters in the smart grid. First, radio resource management algorithms to perform dynamic scheduling of the meter transmissions are proposed and shown to allow the accommodation of a large number of smart meters within a limited coverage area. Then, potential techniques for reducing the signaling load between the meters and base stations are proposed and analyzed. Afterwards, advanced concepts from LTE-A, namely carrier aggregation (CA) and relay stations (RSs) are investigated in conjunction with the proposed algorithms in order to accommodate a larger number of smart meters without disturbing cellular communications.

Diffusion Analysis for Techno-commercial Predictions in 5G HetNet Deployment Scenarios

Fifth-generation (5G) mobile services entail network densification, having Massive MIMO air interfaces operating at millimeter-wave (mmWave) frequencies. Techno-economic analysis for such a complex heterogeneous network (HetNet) is challenging due to uncertain future demand and technical hurdles for ensuring seamless nationwide coverage and capacity. We show in this work how a Logistic diffusion model may be used to forecast 5G adoption in a country and then utilize those forecasts to perform a techno-economic assessment of 5G deployment. The complete analysis is showcased for a European nation, namely France, for the period 2020-2030. We find that, theoretically, both the Capex and the total cost of ownership (TCO) for the considered 5G HetNets is cheaper (1/7th) than that for 4G LTE-Advanced (LTE-A) networks, also translating into higher returns. The sensitivity analysis predicts the Average Revenue from Users (ARPU), spectrum acquisition costs, and spectrum bandwidth as the most influential variables for profitability.