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IEEE GLOBECOM Workshops (GC Wkshps) (2022. Rio deJaneiro, Brazil), Integrating Terrestrial Networks (TN) and Non-Terrestrial Networks (NTN) is crucial to providing fifth generation (5G) ubiquitous coverage and exploiting the potential of connectivity-based solutions. This article presents an initial empirical evaluation of both broadband satellite and terrestrial cellular connectivity solutions. End-to-end latency, Packet Error Rate (PER), and uplink (UL) and downlink (DL) throughput statistics are obtained using a SpaceX Starlink satellite antenna terminal connected to the Starlink satellite network and a multiband 5G New Radio (NR) modem connected over a public 5G Non-Standalone (NSA) network. Furthermore, we study how the maximum end-to-end latency can be reduced by using multi-connectivity between terrestrial and LEO satellite networks. Results suggest that the integration of terrestrial and NTN is a competitive solution to fill the existing coverage gaps and provide seamless service to low-latency and high throughput requiring applications., This research has received funding from the European Union’s Horizon Europe Research and Innovation Programme, and is conducted as part of the HE COMMECT project, with grant agreement No. 101060881. This work was also partially supported by the Spanish Ministry of Science and Innovation under Ramon y Cajal Fellowship number RYC-2020-030676-I.

In this contribution, a recently conducted measurementcampaign in a suburban scenario for the Unmanned AerialVehicle (UAV) Air-to-Ground (A2G) radio channel is introduced.The downlink signals in an in-service Long Term Evolution(LTE) network were collected and utilized to extract the ChannelImpulse Responses (CIRs). A high-resolution parameterestimation algorithm derived based on the Space-AlternatingGeneralized Expectation-maximization (SAGE) principle is appliedto estimate the delays, Doppler frequencies and complexamplitudes of MultiPath Components (MPCs) from the CIRs.Based on the MPC estimation results, fast fading characteristicsof the A2G channels are investigated. It is found that theRician distribution models the fast fading the best comparedto Nakagami, Lognormal and Rayleigh distributions. Rician Kfactorsare also calculated for the A2G channels.

The need for continuous safety improvements and increased operational efficiency is driving the mining industry through a transition towards large-scale automation of operations, i.e., “intelligent mines”. The technology promises to remove human operators from harsh or dangerous conditions and increase productivity, from extraction all the way to the delivery of a processed product to the customer. In this context, one of the key enablers is wireless connectivity since it allows mining equipment to be remotely monitored and controlled. Simply put, dependable wireless connectivity is essential for unmanned mine operations. Although voice and narrowband data radios have been used for years to support several types of mining activities, such as fleet management (dispatch) and telemetry, the use of automated equipment introduces a new set of connectivity requirements and poses a set of challenges in terms of network planning, management and optimization. For example, the data rates required to support unmanned equipment, e.g. a teleoperated bulldozer, shift from a few kilobits/second to megabits/second due to live video feeds. This traffic volume is well beyond the capabilities of Professional Mobile Radio narrowband systems and mandates the deployment of broadband systems. Furthermore, the (data) traffic requirements of a mine also vary in time as the fleet expands. Additionally, wireless networks are planned according to the characteristics of the scenario in which they will be deployed, but mines change by definition on a daily-basis. Therefore, a careful and continuous effort must be made to ensure the wireless network keeps up with the topographic and operational changes in order to provide the necessary network availability, reliability, capacity and coverage needed to support a new mining paradigm. By means of simulations, we analyze the effects on the wireless network along 7 years of constant topographic changes in an open-pit mine coupled with much higher data requirements. The authors also present a new network topology that is able to partially meet the requirements posed by mining automation and discuss the consequences of not providing connectivity for all applications. The work also discusses how the careful positioning of the heavy communications infrastructure (tall towers) from the early stages of the mine site project can make the provision of incremental capacity and coverage simpler.

Upcoming applications, such as autonomous vehicles, will pose strict requirements on the vehicular networks. In order to provide these new services reliably, an accurate understanding of propagation in the vehicular scenarios is needed. In this context, this paper presents a measurement-based evaluation of large vehicle shadowing at 5.8 GHz in V2X scenarios. The receiver antenna height is fixed to average vehicular height (1.5 m), while the transmitter antennas are located at different heights (1.5, 5, and 7 m) in order to investigate both V2V and V2I scenarios. A truck was used to obstruct the LOS between transmitter and receiver, and a large number of geometrical combinations of the scenario were explored. The statistical analysis of the measurement shows how in the V2V case, the experienced shadow levels are approximately 5 dB higher than in the V2I scenarios, where the shadow levels depend on the transmitter antenna height, reaching maximum values of 21-23 dB. The statistical analysis also shows that the differences in shadow level due to the non-symmetries of the obstacle truck are in the order of approximately 2 dB. A simple 3D ray-tracing simulation is validated against the measurements, showing a good match with a RMSE of 4.1 dB. Based on both measurements and ray-tracing data, a simple deterministic shadowing model, useful for implementation in system level simulators, is presented, as a first step towards a more dynamic and scalable shadowing model.

Full duplex communication promises a 100% throughput gain by enabling simultaneous transmission and reception. However, such simultaneous communication leads to a corresponding increase in the network interference. In addition, full duplex communication can only be exploited when traffic is available in both uplink and downlink directions; while, cellular network traffic tend to be downlink heavy in practice. The potential throughput gains of full duplex communication over conventional half duplex transmission in a small cell network with asymmetric traffic conditions are investigated in this contribution using network analysis tools from stochastic geometry. The analytical findings are further confirmed through computer-based Monte-Carlo simulations. Asymmetric downlink/uplink traffic pattern and the increased network interference stemming from full duplex transmissions are found to limit its potential performance to well below the promised 100% throughput gain.

Smartphone users struggle with short battery life, and this affects their device satisfaction level and usage of the network. To evaluate how chipset manufacturers and mobile network operators can improve the battery life, we propose a Long Term Evolution (LTE) smartphone power model. The idea is to provide a model that makes it possible to evaluate the effect of different terminal and network settings to the overall user equipment energy consumption. It is primarily intended as an instrument for the network engineers in deciding on optimal network settings, but could also be beneficial for chipset manufacturers to identify main power consumers when taking actual operating characteristics into account. The smartphone power consumption model includes the main power consumers in the cellular subsystem as a function of receive and transmit power and data rate, and is fitted to empirical power consumption measurements made on state-of-the-art LTE smartphones. Discontinuous Reception (DRX) sleep mode is also modeled, because it is one of the most effective methods to improve smartphone battery life.Energy efficiency has generally improved with each Radio Access Technology (RAT) generation, and to see this evolution, we compare the energy efficiency of the latest LTE devices with devices based on Enhanced Data rates for GSM Evolution (EDGE), High Speed Packet Access (HSPA), and Wi-Fi*. With further generations of RAT systems we expect further improvements. To this end, we discuss the new LTE features, Carrier Aggregation (CA) and Enhanced Physical Downlink Control Channel (EPDCCH), from an energy consumption perspective.Not surprisingly, the conclusion is that having the cellular subsystem ON, and in addition, transmit powers above 10 dBm, have the largest effect on UE power consumption, and that the combination of high data rates and long sleep periods is the optimal combination from a user equipment energy-saving perspective.

In this paper, we focus on ultra-dense network modelingwhere both the Base Stations (BSs) and Mobile Terminals(MTs) are UAVs. In this case, two communication nodes canbe very close to each other. However, existing cellular networkanalyses typically use the standard unbounded path loss modelwhere received power decays like r^beta over a distance r. Thisstandard model is a good approximation for the path-loss inwireless communications over large values of r but is not validfor small values of r due to the singularity at 0. This model is oftenused along with a random uniform node distribution, even thoughin a group of uniformly distributed nodes some may be arbitrarilyclose to one another, thus, it will lose accuracy and may benot applicable for UAV-to-UAV communications. To tackle thisproblem, by using mathematical tool behind stochastic geometry,we propose tractable analytical frameworks of coverage and ratebased on the novel unbounded path-loss model with a constantdistance factor r_0 for analyzing the UAV-to-UAV communications.