Improving the Coverage and Spectral Efficiency of Millimeter-Wave Cellular Networks Using Device-to-Device Relays

Wu, Shuanshuan; Atat, Rachad; Mastronarde, Nicholas; Liu, Lingjia

doi:10.1109/tcomm.2017.2787990

Cited by 91 publications

(72 citation statements)

References 35 publications

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“…However, this creates a set of challenges for cellular network providers [72], such as the inability to handle MTC traffic on networks optimized for human communications, excessive congestions due to signaling overhead, packet scheduling problems due to MTC traffic requiring a number of radio resources below the minimum allocated to a cellular device;, and the large interferences generated from MTC devices [73]. Different relevant works, such as [74]- [77], suggested offloading the MTC traffic onto device-to-device (D2D) communications links. As a matter of fact, Google OnHub router can support direct D2D communications, as well as WiFi, BTL and 802.15.4 using Brillo as a stripped OS version of Android.…”

Section: B Big Data Communications For Cpsmentioning

confidence: 99%

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

et al. 2018

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The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world via creating new services and applications in a variety of sectors such as environmental monitoring, mobilehealth systems, intelligent transportation systems and so on. The information and communication technology (ICT) sector is experiencing a significant growth in data traffic, driven by the widespread usage of smartphones, tablets and video streaming, along with the significant growth of sensors deployments that are anticipated in the near future. It is expected to outstandingly increase the growth rate of raw sensed data. In this paper, we present the CPS taxonomy via providing a broad overview of data collection, storage, access, processing and analysis. Compared with other survey papers, this is the first panoramic survey on big data for CPS, where our objective is to provide a panoramic summary of different CPS aspects. Furthermore, CPS require cybersecurity to protect them against malicious attacks and unauthorized intrusion, which become a challenge with the enormous amount of data that is continuously being generated in the network. Thus, we also provide an overview of the different security solutions proposed for CPS big data storage, access and analytics. We also discuss big data meeting green challenges in the contexts of CPS.

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Section: B Big Data Communications For Cpsmentioning

confidence: 99%

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

et al. 2018

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“…It is shown in (7) that the power consumption of D2D relaying access is highly related to the position of relaying UE i. In the following section, we introduce a power-efficient relay selection criteria to guarantee the power gain saved by D2D relaying access.…”

Section: Figurementioning

confidence: 99%

Power‐efficient D2D relaying cellular network access

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Huang

et al. 2019

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Device‐to‐device (D2D) communications are exploited in this paper to assist remote user equipments (UEs) access the cellular network with reduced energy consumption. A power‐efficient relay selection criterion is proposed to guarantee that the power saved by D2D relaying access exceeds a given threshold. Then, the relay selection criterion is equivalently transformed into a region constraint, based on which the success probability of D2D relaying access is derived. Furthermore, the power consumption of D2D relaying access is analyzed in two stages: the stage from the remote UE to the relaying UE and the stage from the relaying UE to the base station. The calculation of the average power consumption requires a double integral over the plane, and the closed‐form expression is derived by applying the Green's theorem and proper variable substitutions. Finally, simulation results validate the analytical derivations and present the impacts of system parameters on the performance of D2D relaying access in terms of the success probability and power consumption.

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“…Although this would optimize the city wide Line-of-Sight (LoS) coverage rate [13], it would not provide Quality-of-Service (QoS) assurances. In fact, a dense network of mmWave base stations can degrade the QoS of users due to interfering base station transmissions [14], [15]. An alternative solution to overcoming blockage and improve coverage is through relaying [4], [8], [16], a concept that has been included in the currently applied LTE-Advanced standard [17].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Beamforming With Predictive Relay Selection for Urban mmWave Communications

2019

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While millimeter wave (mmWave) communications promise high data rates, their sensitivity to blockage and severe signal attenuation presents challenges in their deployment in urban settings. To overcome these effects, we consider a distributed cooperative beamforming system, which relies on static relays deployed in clusters with similar channel characteristics, and where, at every time instance, only one relay from each cluster is selected to participate in beamforming to the destination. To meet the quality-of-service guarantees of the network, a key prerequisite for beamforming is relay selection. However, as the channels change with time, relay selection becomes a resource demanding task. Indeed, estimation of channel state information for all candidate relays, essential for relay selection, is a process that takes up bandwidth, wastes power and introduces latency and interference in the network. We instead propose a unique, predictive scheme for resource efficient relay selection, which exploits the special propagation patterns of the mmWave medium, and can be executed distributively across clusters, and in parallel to optimal beamforming-based communication. The proposed predictive scheme efficiently exploits spatiotemporal channel correlations with current and past networkwide Received Signal Strength (RSS), the latter being invariant to relay cluster size, measured sequentially during the operation of the system. Our numerical results confirm that our proposed relay selection strategy outperforms any randomized selection policy that does not exploit channel correlations, whereas, at the same time, it performs very close to an ideal scheme that uses complete, cluster size dependent RSS, and offers significant savings in terms of channel estimation overhead, providing substantially better network utilization, especially in dense topologies, typical in mmWave networks.Index Terms-mmWave, cooperative relay beamforming, relay selection, 2-hop relaying, mmWave channel modeling, Vehicle-to-Infrastructure.

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Improving the Coverage and Spectral Efficiency of Millimeter-Wave Cellular Networks Using Device-to-Device Relays

Cited by 91 publications

References 35 publications

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Power‐efficient D2D relaying cellular network access

Cooperative Beamforming With Predictive Relay Selection for Urban mmWave Communications

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