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1 Introduction; References; 2 Optimal Power Allocation for Kalman Filtering over Fading Channels; 2.1 Optimal Power Allocation for Remote State Estimation; 2.1.1 System Model; 2.1.2 Optimal Power Allocation; 2.1.3 Suboptimal Power Allocation Policies; 2.1.4 Numerical Studies; 2.2 Optimal Power Allocation with Energy Harvesting; 2.2.1 Optimal Energy Allocation Problems; 2.2.2 Solutions to the Optimal Energy Allocation Problems; 2.2.3 Structural Results on the Optimal Energy Allocation Policies; 2.2.4 Numerical Studies; 2.3 Conclusion; References.
3 Optimal Transmission Scheduling for Event-Triggered Estimation with Packet Drops3.1 Transmission Scheduling over a Packet Dropping Channel; 3.1.1 System Model; 3.1.2 Optimization of Transmission Scheduling; 3.1.3 Structural Properties of Optimal Transmission Scheduling; 3.1.4 Transmission of Measurements; 3.1.5 Numerical Studies; 3.2 Transmission Scheduling with Energy Harvesting; 3.2.1 System Model; 3.2.2 Optimization of Transmission Scheduling; 3.2.3 Structural Properties of Optimal Transmission Scheduling; 3.2.4 Numerical Studies; 3.3 Conclusion; References.
4 Optimal Transmission Strategies for Remote State Estimation4.1 System Model; 4.1.1 Process Dynamics and Sensor Measurements; 4.1.2 Local Kalman Filter at the Smart Sensor; 4.1.3 Coding Alternatives at the Smart Sensor; 4.1.4 Communication Channel; 4.2 Analysis of the System Model; 4.2.1 Augmented State Space Model at the Receiver; 4.2.2 Kalman Filter at the Receiver; 4.3 Optimal Transmission Policy Problem; 4.4 Structural Results on Optimal Transmission Policies for Scalar Systems; 4.5 Numerical Studies; 4.6 Conclusion; References; 5 Remote State Estimation in Multi-hop Networks.
5.1 Kalman Filtering over Fading Channels with Relays5.1.1 Background; 5.1.2 System Model; 5.1.3 Kalman Filter with Packet Drops and Relays; 5.1.4 Performance of the Kalman Filter with Relays; 5.1.5 Relay Configuration Selection; 5.1.6 Relay Configuration Selection and Power Control; 5.1.7 Numerical Studies; 5.2 Network Topology Reconfiguration for Remote State Estimation; 5.2.1 Background; 5.2.2 System Model; 5.2.3 Optimal Network Reconfiguration; 5.2.4 Suboptimal Network Reconfiguration; 5.2.5 An Illustrative Example; 5.2.6 Numerical Studies; 5.2.7 Conclusion.
3 Optimal Transmission Scheduling for Event-Triggered Estimation with Packet Drops3.1 Transmission Scheduling over a Packet Dropping Channel; 3.1.1 System Model; 3.1.2 Optimization of Transmission Scheduling; 3.1.3 Structural Properties of Optimal Transmission Scheduling; 3.1.4 Transmission of Measurements; 3.1.5 Numerical Studies; 3.2 Transmission Scheduling with Energy Harvesting; 3.2.1 System Model; 3.2.2 Optimization of Transmission Scheduling; 3.2.3 Structural Properties of Optimal Transmission Scheduling; 3.2.4 Numerical Studies; 3.3 Conclusion; References.
4 Optimal Transmission Strategies for Remote State Estimation4.1 System Model; 4.1.1 Process Dynamics and Sensor Measurements; 4.1.2 Local Kalman Filter at the Smart Sensor; 4.1.3 Coding Alternatives at the Smart Sensor; 4.1.4 Communication Channel; 4.2 Analysis of the System Model; 4.2.1 Augmented State Space Model at the Receiver; 4.2.2 Kalman Filter at the Receiver; 4.3 Optimal Transmission Policy Problem; 4.4 Structural Results on Optimal Transmission Policies for Scalar Systems; 4.5 Numerical Studies; 4.6 Conclusion; References; 5 Remote State Estimation in Multi-hop Networks.
5.1 Kalman Filtering over Fading Channels with Relays5.1.1 Background; 5.1.2 System Model; 5.1.3 Kalman Filter with Packet Drops and Relays; 5.1.4 Performance of the Kalman Filter with Relays; 5.1.5 Relay Configuration Selection; 5.1.6 Relay Configuration Selection and Power Control; 5.1.7 Numerical Studies; 5.2 Network Topology Reconfiguration for Remote State Estimation; 5.2.1 Background; 5.2.2 System Model; 5.2.3 Optimal Network Reconfiguration; 5.2.4 Suboptimal Network Reconfiguration; 5.2.5 An Illustrative Example; 5.2.6 Numerical Studies; 5.2.7 Conclusion.