increasing efficiency of resource allocation for d2d communication in nb iot context

Abstract Internet of things (IoT) and device to device (D2D) communications are among the novel promising technologies in the current releases of 4G and they will play a fundamental role in the next generation 5G as well. In this paper, it is investigated the impact of allocation strategies that take into account the mutual interference in D2D Narrow-Band IoT terminals and cellular terminals transmitting in the same resource block. In a multi-cellular downlink context, the proposed approach and the analysis can serve also as an efficient criterion for selecting the target SINR, useful for managing the power control in the uplink. The rate improvement, measured with the proposed approach, is between 10% and 15% w.r.t. conventional techniques

Rotated Rectangular Slots And Mirrored Inversed Cantor-sets On Ultrawideband Antipodal Vivaldi Antenna

Variants of antipodal Vivaldi antenna (AVA) design suitable for access point working on 0.5 – 6.0 GHz are proposed in this paper. The novel designs were produced by employing three novel techniques to conventional AVA: (i) rotated-slot pattern to shift down the frequency cutoff and enhancing bandwidth, (ii) curve design to miniaturize rotated-slot-inserted antipodal Vivaldi, and (iii) fractal-director (Cantor set) to increase the gain of antipodal Vivaldi. Using FR4 (relative permittivity of 4.4) with an overall dimension of 300 mm x 143 mm x 1.6 mm the antenna designs are able to work at a frequency of 0.472 GHz to higher than 6 GHz with a maximum gain of 11.9 dBi

Special Issue on Next-Generation Cold Supply Chain Management: Research, Applications and Challenges

A cold supply chain, also called a temperature-controlled supply chain, is a logistics and supply system that provides a series of facilities for maintaining ideal conditions for goods within a given temperature range, from the point of origin to the point of consumption. Cold supply chains are particularly used for food products. Typically, such supply chains face greater risks and uncertainties owing to issues such as product perishability, the wide variety of products delivered, multiple suppliers of raw materials, short shelf lives, stringent traceability and regulatory requirements, and greater supply chain distances – and thus more handling points and larger networks. This, in turn, creates higher risks of food waste and increases costs; there are also often health risks if spoiled goods end up on the market

A Wearable Fall Detection System based on LoRa LPWAN Technology

Several technological solutions now available in the market offer the possibility of increasing the independent life of people who by age or pathologies otherwise need assistance. In particular, internet-connected wearable solutions are of considerable interest, as they allow continuous monitoring of the user. However, their use poses different challenges, from the real usability of a device that must still be worn to the performance achievable in terms of radio connectivity and battery life. The acceptability of a technology solution, by a user who would still benefit from its use, is in fact often conditioned by practical problems that impact the person’s normal lifestyle. The technological choices adopted in fact strongly determine the success of the proposed solution, as they may imply limitations both to the person who uses it and to the achievable performance. In this document, targeting the case of a fall detection sensor based on a pair of sensorized shoes, the effectiveness of a real implementation of an Internet of Things technology is examined. It is shown how alarming events, generated in a metropolitan context, are effectively sent to a supervision system through Low Power Wide Area Network technology without the need for a portable gateway. The experimental results demonstrate the effectiveness of the chosen technology, which allows the user to take advantage of the support of a wearable sensor without being forced to substantially change his lifestyle

Reliability optimization in narrowband device-to-device communication for 5G and beyond-5G networks

The 5G and beyond-5G (B5G) is expected to be a key enabler for Internet-of-Everything (IoE). The narrowband Internet of Things (NB-IoT) is a low-power wide-area enabling technology introduced by the 3rd Generation Partnership in 5G. The objective of the NB-IoT is to enhance the mobile coverage area by increasing the number of repetitions of control and data packets between user equipment (UE) and the base station/evolved NodeB (BS/eNB). While these repetitions improve data delivery for delay-sensitive applications, they degrade the efficiency of the already resource-constrained IoT system by increasing the system overhead and energy consumption. Moreover, NB-IoT devices in the edge region of the cellular coverage area require more repetitions, which augment energy consumption. In this study, we investigate device-to-device (D2D) communication for NB-IoT delay-sensitive applications, such as healthcare-IoT services, to use two-hop communication instead of using a direct uplink. An optimization problem is formulated to achieve an optimal end-to-end delivery ratio (EDR). In addition, this study incorporates Q-Learning-based reinforcement learning (RL) for the selection of an optimal cellular relay, which assists NB-IoT UE in uploading sensitive data to BS/eNB. The proposed RL-intelligent-D2D (RL-ID2D) communication methodology selects the optimum relay with a maximum EDR, which ultimately augments energy efficiency

NB-IoT for D2D-enhanced content uploading with social trustworthiness in 5G systems

Future fifth-generation (5G) cellular systems are set to give a strong boost to the large-scale deployment of Internet of things (IoT). In the view of a future converged 5G-IoT infrastructure, cellular IoT solutions such as narrowband IoT (NB-IoT) and device-to-device (D2D) communications are key technologies for supporting IoT scenarios and applications. However, some open issues still need careful investigation. An example is the risk of threats to privacy and security when IoT mobile services rely on D2D communications. To guarantee efficient and secure connections to IoT services involving exchange of sensitive data, reputation-based mechanisms to identify and avoid malicious devices are fast gaining ground. In order to tackle the presence of malicious nodes in the network, this paper introduces reliability and reputation notions to model the level of trust among devices engaged in an opportunistic hop-by-hop D2D-based content uploading scheme. To this end, social awareness of devices is considered as a means to enhance the identification of trustworthy nodes. A performance evaluation study shows that the negative effects due to malicious nodes can be drastically reduced by adopting the proposed solution. The performance metrics that proved to benefit from the proposed solution are data loss, energy consumption, and content uploading time. © 2017 by the authors

NB-IoT for D2D-enhanced content uploading with social trustworthiness in 5G systems

Future fifth-generation (5G) cellular systems are set to give a strong boost to the large-scale deployment of Internet of things (IoT). In the view of a future converged 5G-IoT infrastructure, cellular IoT solutions such as narrowband IoT (NB-IoT) and device-to-device (D2D) communications are key technologies for supporting IoT scenarios and applications. However, some open issues still need careful investigation. An example is the risk of threats to privacy and security when IoT mobile services rely on D2D communications. To guarantee efficient and secure connections to IoT services involving exchange of sensitive data, reputation-based mechanisms to identify and avoid malicious devices are fast gaining ground. In order to tackle the presence of malicious nodes in the network, this paper introduces reliability and reputation notions to model the level of trust among devices engaged in an opportunistic hop-by-hop D2D-based content uploading scheme. To this end, social awareness of devices is considered as a means to enhance the identification of trustworthy nodes. A performance evaluation study shows that the negative effects due to malicious nodes can be drastically reduced by adopting the proposed solution. The performance metrics that proved to benefit from the proposed solution are data loss, energy consumption, and content uploading time.publishedVersionPeer reviewe

NB-IoT for D2D-enhanced content uploading with social trustworthiness in 5G systems

Future fifth-generation (5G) cellular systems are set to give a strong boost to the large-scale deployment of Internet of things (IoT). In the view of a future converged 5G-IoT infrastructure, cellular IoT solutions such as narrowband IoT (NB-IoT) and device-to-device (D2D) communications are key technologies for supporting IoT scenarios and applications. However, some open issues still need careful investigation. An example is the risk of threats to privacy and security when IoT mobile services rely on D2D communications. To guarantee efficient and secure connections to IoT services involving exchange of sensitive data, reputation-based mechanisms to identify and avoid malicious devices are fast gaining ground. In order to tackle the presence of malicious nodes in the network, this paper introduces reliability and reputation notions to model the level of trust among devices engaged in an opportunistic hop-by-hop D2D-based content uploading scheme. To this end, social awareness of devices is considered as a means to enhance the identification of trustworthy nodes. A performance evaluation study shows that the negative effects due to malicious nodes can be drastically reduced by adopting the proposed solution. The performance metrics that proved to benefit from the proposed solution are data loss, energy consumption, and content uploading time. © 2017 by the authors

Performance assessment of Narrowband IoT for Intelligent Cargo Transportation

Narrow Band Internet of Things (NB-IoT) is the most advanced technology standard for short message services, such as sensor data, developed by 3GPP Release 13 and beyond. The NB-IoT is deployed over Long Term Evolution (LTE) Advanced Pro infrastructure and theoretically, it offers extended coverage up to 40 km from the base station. The objective of this thesis is to analyze the performance of NB-IoT technology in cargo shipment tracking using LTE cellular networks across the coastal line. Currently, about fifty thousand cargo ships use onboard Satellite communication system for all sorts of information exchange with the onshore data centers. The Satellite communication will continue to exist, even after deployment of NB-IoT. Apart from the machine critical data of the cargo ships, the non-emergency periodic short messages for polling meteorological and container metadata such as temperature, humidity, gaseous detection, etc. will be crucial for the quality of the shipment and the traceability. In this thesis, we analyze deployment of NB-IoT sensors for cargo container to track and provide metadata about the condition of goods. We evaluate three implementation methods of NB-IoT for cargo ships, optimize the coverage and enhance the battery life of the sensor equipment. The main idea is to offload non-critical information that would otherwise use expensive Satellite links, thus embrace the NB-IoT technology at offshore and reduce the financial stress on the cargo shipments. In the first method, all the sensors transfer the periodic data directly to the coastal LTE network when the ships sail in close proximity to the shore. In the second method, the sensors transfer data to an LTE base station installed locally on the ship and then accumulated information will be relayed to onshore LTE network over NB-IoT channel. In the third method, an Unmanned Aerial Vehicle (UAV/ Drone) base station will collect the data from the onboard sensors; it then relays the information to the onshore LTE network. For all methods, when there is no LTE coverage, the accumulated data will be sent over the Satellite link, which will be available onboard. The assessment confirms the hypothesis that the packet loss probability reduces when the base station is located close to the sensor, where the number of retransmissions will be reduced, and more uplink resources will be available. For direct access scenario, a large number of users contend for Random Access Channel (RACH) simultaneously after entering into the LTE coverage. The packet will be dropped after reaching the maximum number of attempts for the RACH resources. As per the simulated results, mean lifespan of a sensor is greatly affected by the LTE network availability and random access procedure, during which the sensor spends most of the energy for transmissions. The mean transmit delay will be higher with second and third methods where the ship BS, UAV BS accumulate packets until they find the LTE network or relays the data to the Satellite link if the LTE outage is longer. This performance assessment provides technical insights for the maritime industry to embrace the NB-IoT for tracking and condition monitoring of shipment