1. 2002 MURI Minisymposium Cooperative Control of Distributed Autonomous Vehicles in Adversarial Environments 2002 MURI Minisymposium Ameesh Pandya Prof. Greg Pottie

2. 2002 MURI Minisymposium Overview Fault tolerant communication network supporting hierarchical distributed communication network. Robust network algorithm for highly dynamic mobile nodes (say, UAVs). Providing minimum communications between mobile nodes to minimize the probability of jamming. Working closely with Prof. Speyer’s group to develop the communication model according to control traffic.

3. 2002 MURI Minisymposium Wireless Communication Model Application Layer Transport layer IP Network Link Layer MAC Layer Radio Channel

4. 2002 MURI Minisymposium Our Concentration Application Layer Transport layer IP Network Link Layer MAC Layer Radio Channel Area of Concentration

5. 2002 MURI Minisymposium QoS Constraints for Control Traffic Data Rate for the control traffic : 2 Mbps –This could be considered as the upper bound. –Achieved by using 2 Mbps modem. Latency for control traffic: 0 – 100 ms –Worst latency is 100ms for control traffic.

6. 2002 MURI Minisymposium Channel Capacity Capacity constraint for the control traffic. Channel capacity in terms of received and transmitted power, jamming power, spread factor, bit rate. Goal is to know the reliable transmitting distance between the nodes at 2Mbps for the given parameters.

7. 2002 MURI Minisymposium Channel Capacity Assumptions: –Isotropic antenna –Spread spectrum modulation. –For Low probability of intercept (LPI), P r /W s N 0 = 0.1, where P r is the received power and W s is the band width of spread spectrum signal.

8. 2002 MURI Minisymposium Channel Capacity Shannon’s Equation: where, P r is the received power, W is the channel bandwidth. For isotropic antenna, where P t is the transmitted power Spread factor, f = W s /R, where W s is the band width of the spread spectrum signal and R is the information rate in bps.

9. 2002 MURI Minisymposium Channel Capacity If we do not consider broadband jammer, then In presence of broadband jammer capacity becomes: where, is the average jamming power at distance r from the receiver If we use CDMA, then in presence of jammer for N u simultaneous users, channel capacity is given by (assuming identical signal power):

10. 2002 MURI Minisymposium Simulation Result Achievable transmitting distance at 2 Mbps for different values of transmitting power. Here, the transmitting power is assumed to be 1 Watt and 2 Watts. Assuming available channel bandwidth to be 100Mbps. Simulation carried out with the assumption of ideality i.e. no jammer and propagation loss.

11. 2002 MURI Minisymposium MAC Layer Clustering Considering n nodes (UAVs). Selecting clusters (cluster heads). Each cluster having back bone node. Using optimal cluster algorithm.

12. 2002 MURI Minisymposium Future Objectives Developing clustering algorithms for mobile nodes in dynamic environment. Clustering algorithms: –UAV - UAV –UAV - UGV Obtaining simulation results on the performance and robustness of the algorithm.

13. 2002 MURI Minisymposium Insight The solution to the communication network model for this particular problem “may” be very close to IPv6. Looking into this possibility.