Optimization based energy-efficient control inmobile communication networks

In this work we consider how best to control mobility and transmission for the purpose of datatransfer and aggregation in a network of mobile autonomous agents. In particular we considernetworks containing unmanned aerial vehicles (UAVs). We first consider a single link betweena mobile transmitter-receiver pair, and show that the total amount of transmittable data isbounded. For certain special, but not overly restrictive cases, we can determine closed-formexpressions for this bound, as a function of relevant mobility and communication parameters.We then use nonlinear model predictive control (NMPC) to jointly optimize mobility and trans-mission schemes of all networked nodes for the purpose of minimizing the energy expenditureof the network. This yields a novel nonlinear optimal control problem for arbitrary networksof autonomous agents, which we solve with state-of-the-art nonlinear solvers. Numerical re-sults demonstrate increased network capacity and significant communication energy savingscompared to more na ̈ıve policies. All energy expenditure of an autonomous agent is due tocommunication, computation, or mobility and the actual computation of the NMPC solutionmay be a significant cost in both time and computational resources. Furthermore, frequentbroadcasting of control policies throughout the network can require significant transmit andreceive energies. Motivated by this, we develop an event-triggering scheme which accounts forthe accuracy of the optimal control solution, and provides guarantees of the minimum timebetween successive control updates. Solution accuracy should be accounted for in any triggeredNMPC scheme where the system may be run in open loop for extended times based on pos-sibly inaccurate state predictions. We use this analysis to trade-off the cost of updating ourtransmission and locomotion policies, with the frequency by which they must be updated. Thisgives a method to trade-off the computation, communication and mobility related energies ofthe mobile autonomous network.Open Acces