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Collaborative beamforming for distributed wireless ad hoc sensor networks

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TLDR
The performance of collaborative beamforming is analyzed using the theory of random arrays and it is shown that with N sensor nodes uniformly distributed over a disk, the directivity can approach N, provided that the nodes are located sparsely enough.
Abstract
The performance of collaborative beamforming is analyzed using the theory of random arrays. The statistical average and distribution of the beampattern of randomly generated phased arrays is derived in the framework of wireless ad hoc sensor networks. Each sensor node is assumed to have a single isotropic antenna and nodes in the cluster collaboratively transmit the signal such that the signal in the target direction is coherently added in the far-field region. It is shown that with N sensor nodes uniformly distributed over a disk, the directivity can approach N, provided that the nodes are located sparsely enough. The distribution of the maximum sidelobe peak is also studied. With the application to ad hoc networks in mind, two scenarios (closed-loop and open-loop) are considered. Associated with these scenarios, the effects of phase jitter and location estimation errors on the average beampattern are also analyzed.

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Distributed transmit beamforming: challenges and recent progress

TL;DR: Promising recent results in architectures, algorithms, and working prototypes indicate that challenges of distributed beamforming can be surmounted, and directions for future research needed to translate the potential of distributedbeamforming into practice are discussed.
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On the Feasibility of Distributed Beamforming in Wireless Networks

TL;DR: It is shown that a large fraction of the beamforming gains can be realised even with imperfect synchronization corresponding to phase errors with moderately large variance, and a stochastic analysis is presented that demonstrates the robustness ofbeamforming gains with imperfect synchronized synchronization.
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References
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Book

Antenna Theory: Analysis and Design

TL;DR: The most up-to-date resource available on antenna theory and design as mentioned in this paper provides an extended coverage of ABET design procedures and equations making meeting ABET requirements easy and preparing readers for authentic situations in industry.
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Mathematical analysis of random noise

TL;DR: In this paper, the authors used the representations of the noise currents given in Section 2.8 to derive some statistical properties of I(t) and its zeros and maxima.
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