Propagation measurements for device-to-device communication in forest terrain

Hejselbak, Johannes; Nielsen, Jesper Ødum; Drewes, Christian; Fan, Wei; Pedersen, Gert Frølund

doi:10.1049/cp.2018.0389

Cited by 10 publications

(10 citation statements)

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“…Definitively, this will also play a significant role in accomplishing data sending/receiving with lower power consumption [ 28 ]. D2D communication is applicable to IoT, mainly when the power budget of embedded devices prohibits direct communications with the cellular network infrastructure [ 31 ].…”

Section: Overview Of D2d Communications In Cellular Networkmentioning

confidence: 99%

“…These small gadgets exchange small amounts of data/information but consume significant power for communications, compared to data gathering and processing. Therefore, a D2D NB-IoT communication framework seems a viable solution to the problem [ 31 ].…”

Section: Overview Of D2d Communications In Cellular Networkmentioning

confidence: 99%

“…First, the path loss between CH and BS (i.e., long range transmission), which was simulated based on [ 17 , 19 , 20 , 37 , 38 ]. Second, the path loss between NB-IoT D2D nodes (i.e., short range transmission between the CH and the respective associated cluster nodes), that was simulated based on [ 24 , 31 , 33 , 39 , 40 ]. The MAC layer verifies whether frames have been received correctly.…”

Section: Nb-iot D2d Framework Model and Simulationmentioning

confidence: 99%

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Narrowband-Internet of Things Device-to-Device Simulation: An Open-Sourced Framework

Althobaiti

Dohler

2021

Sensors

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Narrowband-Internet of Things (NB-IoT) displays high-quality connectivity underpinned by fifth-generation (5G) networks to cover a wide array of IoT applications. The devices’ development and integration into different smart systems require permanent control, supervision, and the study of power consumption models to determine the performance of the network topology and allow for the measurement of the efficiency of the network topology’s application. This paper reports on an architecture and open-sourced simulation that was developed to study NB-IoT in Device-to-Device (D2D) mode, which includes the Physical (PHY), network, and application layers, as well as a queuing model, the model for uplink and downlink delays, the throughput, the overall NB-IoT D2D network performance, and the energy consumption based on the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Our results prove that the suggested framework contributes to a reduction in power consumption, a minimization of queuing delays, a decrease in communication cost, a reduction in inter-cluster collisions, and the prevention of attacks from malicious nodes. Consequently, the framework manages the battery’s State of Charge (SOC), improves the battery’s State of Health (SOH), and maximizes the whole network lifetime. The proposed framework, the code of which has been open-sourced, can be effectively used for scientific research and development purposes to evaluate different parameters and improve the planning of NB-IoT networks.

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Section: Overview Of D2d Communications In Cellular Networkmentioning

confidence: 99%

Section: Overview Of D2d Communications In Cellular Networkmentioning

confidence: 99%

Section: Nb-iot D2d Framework Model and Simulationmentioning

confidence: 99%

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Narrowband-Internet of Things Device-to-Device Simulation: An Open-Sourced Framework

Althobaiti

Dohler

2021

Sensors

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“…where μ 2 (L ex | dB ) is the mean, σ 2 2 is the variance of the XPR model; α 2 = −0.6, β 2 = 35 and σ 2 = 4 are used [13]. The excess loss L ex | dB of the MPC is defined as…”

Section: B Running the Ray-tracermentioning

confidence: 99%

“…Mathematical models and tools to predict losses due to radio propagation have been studied in the previous years extensively, e.g., [1]. In contrast, possible gains or losses attributed to antennas implemented on mobile phone devices have received less attention, particularly under the presence of fingers and human bodies of mobile users [2]- [6]. This paper therefore sheds lights on gains of practical mobile phone antennas operating at higher frequencies than 6 GHz, particularly at millimeter-waves (mm-waves).…”

Section: Introductionmentioning

confidence: 99%

Total Array Gains of Polarized Millimeter-Wave Mobile Phone Antennas

Haneda

Heino

Järveläinen

2018

2018 European Conference on Networks and Communications (EuCNC)

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This paper studies a gain of an antenna array implemented on a mobile device operating at a millimeter-wave radio frequency. Assuming that mobile phones at millimeterwave range operate with a single transceiver chain and analog beamforming like phased arrays, its total array gain is attributed to average gains of antenna elements and signal precoding or combining gains in excess to received power from a single-element dual-polarized omni-directional antenna. The total array gain circumvents the ambiguity of conventional array gain which cannot be uniquely defined as there are multiple choices of a reference single-element antenna in an array. Different polarized 8-element patch antenna arrays implemented on a mobile phone chassis, i.e., uniform linear array (ULA) and distributed array (DA) operating at 60 GHz, are studied. The antenna elements are placed so that they cover vertical, slanted or horizontal polarizations. The gain is evaluated for different orientations of the chassis along with effects of a body torso and a finger of a person operating the phone. The gain in a small-cell scenario shows that DA achieves higher gains than ULA regardless of polarization states of antenna elements at the base and mobile stations, and of the existence of line-of-sight in the links. Antenna polarizations do not make much impact on the total array gain as random orientation of a mobile phone and finger shadowing modifies the polarization states. The results show that antenna array geometry is more influential design aspect than polarization when a single transceiver chain is considered.

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