Emulating Synchronized Cooperative Broadcast in the Anglova Scenario and EMANE

Marcus, Kelvin; Nilsson, Josef; Suri, Niranjan; Hansson, Anders; Breedy, Maggie; Fronteddu, Roberto; Cramer, Eelco

doi:10.1109/milcis49828.2020.9282377

Cited by 6 publications

(2 citation statements)

References 8 publications

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“…There are many recent works in this area such as [79][80][81], where various ML-based algorithms are used for relay selection in different environments. However, their applicability in OLA networks is an interesting aspect to investigate further [49,50].…”

Section: Machine Learning and Deep Learning-based Relay Selections In Ola Cooperative Networkmentioning

confidence: 99%

“…We note that the finite-density models, which are extensively discussed in this paper, can provide better guidelines on the OLA protocol design and operation in practice. The OLA techniques presented in this paper can be exploited in wireless sensor networks, IoT, communications and signal processing [49][50][51][52][53][54][55], which are representative topics covered in Sensors. Furthermore, the OLA protocols can be employed in small sensors to improve their energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

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Opportunistic Large Array Propagation Models: A Comprehensive Survey

Nawaz

Kumar

Hassan

et al. 2021

Sensors

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Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

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