Resource allocation for mobile sensing in wireless networks

Mobile sensing, which uses mobile sensors to monitor spatially correlated physical fields, is a promising technique to enhance the flexibility and coverage of wireless sensing systems. However, the position errors of mobile sensors can deteriorate the estimation accuracy of the physical fields. Thus, to optimize the estimation performance, it calls for a trade-off between the resource allocated to localization and communication. In this paper, we first derive the minimum estimation error for the single-sensor case and show how the estimation error is related to localization accuracy and communication rate. Based on the relationship, we then formulate the resource allocation problems and demonstrate that they can be solved by convex optimization. Finally, we extend the single-sensor case into general sensing networks. Numerical results show that the estimation errors can be effectively reduced through optimal resource allocation between localization and communication.