Principles of Mobile Communication
Principles of Mobile Communication
Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
Wireless Communications
Multipath fading in wireless sensor networks: measurements and interpretation
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Reactive sink mobility in wireless sensor networks
Proceedings of the 1st international MobiSys workshop on Mobile opportunistic networking
Maintaining network connectivity and performance in robot teams: Research Articles
Journal of Field Robotics - Special Issue on Search and Rescue Robots
Decentralized Communication-Aware Motion Planning in Mobile Networks: An Information-Gain Approach
Journal of Intelligent and Robotic Systems
Multirobot rendezvous with visibility sensors in nonconvex environments
IEEE Transactions on Robotics
Maintaining Optimal Communication Chains in Robotic Sensor Networks using Mobility Control
Mobile Networks and Applications
Using robot mobility to exploit multipath fading
IEEE Wireless Communications
RF-mobility gain: concept, measurement campaign, and exploitation
IEEE Wireless Communications
Distributed Coordination Control of Multiagent Systems While Preserving Connectedness
IEEE Transactions on Robotics
An efficient approach to multivariate Nakagami-m distribution using Green's matrix approximation
IEEE Transactions on Wireless Communications
The capacity of wireless networks
IEEE Transactions on Information Theory
Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
Antenna Packing in Low-Power Systems: Communication Limits and Array Design
IEEE Transactions on Information Theory
Mitigating multi-path fading in a mobile mesh network
Ad Hoc Networks
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In indoor or urban applications, a moving robot with wireless communications will experience multipath fading. This causes rapid signal strength variations due to interfering reflections of the radio signal. By making short stops at positions with high signal-to-noise ratio (SNR), the robot can trade trajectory tracking accuracy for increased link quality. This represents a type of opportunistic communication-aware motion planning. We propose two novel strategies for improving the link capacity or throughput when either the robot has full knowledge of how the SNR varies along the trajectory, or when only the SNR distribution is known or can be estimated. In the latter case, this leads to an optimal stopping problem over a finite horizon. Both cases are analyzed for independent as well as correlated SNR samples, and a bounded maximum trajectory tracking error. We derive the resulting SNR distributions for the proposed strategies and use them to show how the expected capacity and throughput vary with the allowed tracking error. The results are confirmed by simulations and experiments. Experiments in six different locations validate the communication model and show that the proposed motion planning is robust to non-static fading and can yield throughput improvements of more than 100%.