We present a method for more uniformly distributing the energy burden across a wireless ground-based sensor network communicating with an overhead unmanned aerial vehicle (UAV). A subset of sensor nodes, termed a transmit cluster, receives and aggregates data gathered by the entire network, and forms a distributed antenna array, concentrating the radiated transmission into a narrow beam aimed towards the UAV. Because these duties are power-intensive, the role of transmit cluster must be shifted to different nodes as time progresses. We present an algorithm to reassign the transmit cluster, specifying the time that should elapse between reassignments and the number of hops that should be placed between successive transmit clusters in order to achieve three competing goals: first, we wish to better and more broadly spread the energy load across the sensor network while, second, minimizing the energy expended in moving the transmit cluster, all the while, third, reducing to the extent practicable the time to bring the UAV and the sensor network's beam into alignment. The algorithm thus extends the lifetime of the sensor network while meeting system-level performance objectives

Studies sequential acquisition schemes of m-sequences, based on the sequential probability ratio test (SPRT) and a truncated SPRT (TSPRT), with noncoherent demodulation. Most reported results on sequential acquisition schemes assume that independent samples are available for the decision process. The assumption of independent and identically distributed (i.i.d.) samples requires the integrator in the receiver to be reset periodically. This introduces loss in the effective signal-to-noise ratio, degrading the performance. In the present paper, on the contrary, the authors' two sequential schemes use continuous integration. It can be shown that the likelihood ratio is monotonic; consequently, the tests can be easily implemented in realtime. Methods are proposed for designing the decision thresholds to achieve the desired false-alarm and miss probabilities. Performances of the proposed schemes are obtained and they suggest that the TSPRT is more desirable. The effect of slowly-varying channel fading is also investigated. Results show that fading does not affect the false alarm probabilities, but it can drastically reduce the probability of detecting the alignment of the two PN sequences, especially when the fading is severe.>