Abstract: Accurate channel models are essential to evaluate mobile communication system performance and optimize coverage for existing deployments. The introduction of various transmission frequencies for 5G imposes new challenges for accurate radio performance prediction. This paper compares traditional channel models to a channel model obtained using Deep Learning (DL)-techniques utilizing satellite images aided by a simple path loss model. Experimental measurements are gathered and compose the training and test set. This paper considers path loss modelling techniques offered by state-of-the-art stochastic models and a ray-tracing model for comparison and evaluation. The results show that 1) the satellite images offer an increase in predictive performance by ≈ 0.8 dB, 2) The model-aided technique offers an improvement of ≈ 1 dB, and 3) that the proposed DL model is capable of improving path loss prediction at unseen locations for 811 MHz with ≈ 1 dB and ≈ 4.7 dB for 2630 MHz.

Abstract: Although various linear log-distance path loss models have been developed for wireless sensor networks, advanced models are required to more accurately and flexibly represent the path loss for complex environments. This paper proposes a machine learning framework for modeling path loss using a combination of three key techniques: artificial neural network (ANN)-based multi-dimensional regression, Gaussian process-based variance analysis, and principle component analysis (PCA)-aided feature selection. In general, the measured path loss dataset comprises multiple features such as distance, antenna height, etc. First, PCA is adopted to reduce the number of features of the dataset and simplify the learning model accordingly. ANN then learns the path loss structure from the dataset with reduced dimension, and Gaussian process learns the shadowing effect. Path loss data measured in a suburban area in Korea are employed. We observe that the proposed combined path loss and shadowing model is more accurate and flexible compared to the conventional linear path loss plus log-normal shadowing model.

Abstract: In this paper, a full-duplex unmanned aerial vehicle (FD-UAV) relay is employed to increase the communication capacity of millimeter-wave (mmWave) networks. Large antenna arrays are equipped at the source node (SN), destination node (DN), and FD-UAV relay to overcome the high path loss of mmWave channels and to help mitigate the self-interference at the FD-UAV relay. Specifically, we formulate a problem for maximization of the achievable rate from the SN to the DN, where the UAV position, analog beamforming, and power control are jointly optimized. Since the problem is highly non-convex and involves high-dimensional, highly coupled variable vectors, we first obtain the conditional optimal position of the FD-UAV relay for maximization of an approximate upper bound on the achievable rate in closed form, under the assumption of a line-of-sight (LoS) environment and ideal beamforming. Then, the UAV is deployed to the position which is closest to the conditional optimal position and yields LoS paths for both air-to-ground links. Subsequently, we propose an alternating interference suppression (AIS) algorithm for the joint design of the beamforming vectors and the power control variables. In each iteration, the beamforming vectors are optimized for maximization of the beamforming gains of the target signals and the successive reduction of the interference, where the optimal power control variables are obtained in closed form. Our simulation results confirm the superiority of the proposed positioning, beamforming, and power control method compared to three benchmark schemes. Furthermore, our results show that the proposed solution closely approaches a performance upper bound for mmWave FD-UAV systems.

Abstract: Millimeter wave (mmWave) bands have been utilized for the fifth generation (5G) communication systems and will no doubt continue to be deployed for beyond 5G (B5G). However, the underlying channels are not fully investigated at multi-frequency bands and in multi-scenarios by using the same channel sounder, especially for the outdoor, multiple-input multiple-output (MIMO), and vehicle-to-vehicle (V2V) conditions. In this paper, we conduct multi-frequency multi-scenario mmWave MIMO channel measurements with 4 × 4 antennas at 28, 32, and 39 GHz bands for three cases, i.e., the human body and vehicle blockage measurements, outdoor path loss measurements, and V2V measurements. The channel characteristics, including blockage effect, path loss and coverage range, and non-stationarity and spatial consistency, are thoroughly studied. The blockage model, path loss model, and time-varying channel model are proposed for mmWave MIMO channels. The channel measurement and modeling results will be of great importance for further mmWave communication system deployments in indoor hotspot, outdoor, and vehicular network scenarios for B5G.

Abstract: Millimeter-wave (mm-wave) communication is a key technology for future wireless networks. To combat significant path loss and exploit the abundant mm-wave spectrum, effective beamforming is crucial. Nevertheless, conventional fully digital beamforming techniques are inapplicable, as they demand a separate radio frequency (RF) chain for each antenna element, which is costly and consumes too much energy. Hybrid beamforming is a cost-effective alternative, which can significantly reduce the hardware cost and power consumption by employing a small number of RF chains. This paper presents a holistic view on hybrid beamforming for 5G and beyond mm-wave systems, based on a new taxonomy for different hardware structures. We take a pragmatic approach and compare different proposals from three key aspects: 1) hardware efficiency, i.e., the required hardware components; 2) computational efficiency of the associated beamforming algorithm; and 3) achievable spectral efficiency, a main performance indicator. Through systematic comparisons, the interplay and trade-off among these three design aspects are demonstrated, and promising candidates for hybrid beamforming in future wireless networks are identified.

Abstract: Unmanned aerial vehicle (UAV) has been widely used in many fields and is arousing global attention. As the resolution of the equipped sensors in the UAV becomes higher and the tasks become more complicated, much higher data rate and longer communication range are required in the foreseeable future. As the millimeter-wave (mmWave) band can provide more abundant frequency resources than the microwave band, much higher achievable rate can be guaranteed to support UAV services such as video surveillance, hotspot coverage, and emergency communications, etc. The flexible mmWave beamforming can be used to overcome the high path loss caused by the long propagation distance. In this paper, we study three typical application scenarios for mmWave-UAV communications, namely communication terminal, access point, and backbone link. We present several key enabling techniques for UAV communications, including beam tracking, multi-beam forming, joint Tx/Rx beam alignment, and full-duplex relay techniques. We show the coupling relation between mmWave beamforming and UAV positioning for mmWave-UAV communications. Lastly, we summarize the challenges and research directions of mmWave-UAV communications in detail.

Abstract: Visible light communication (VLC) has been proposed as an alternative or complementary technology to radio frequency vehicular communications. Front and back vehicle lights can serve as wireless transmitters making VLC a natural vehicular connectivity solution. In this paper, we evaluate the performance limits of vehicular VLC systems. First, we use non-sequential ray tracing to obtain the channel impulse responses (CIRs) for vehicle-to-vehicle (V2V) link in various weather conditions. Based on these CIRs, we present a closed-form path loss expression which builds upon the summation of geometrical loss and attenuation loss and takes into account asymmetrical patterns of vehicle light sources and geometry of V2V transmission. The proposed expression is an explicit function of link distance, lateral shift between two vehicles, weather type (quantified by the extinction coefficient), transmitter beam divergence angle and receiver aperture diameter. Then, we utilize this expression to determine the maximum achievable link distance of V2V systems for clear, rainy and foggy weather conditions while ensuring a targeted bit error rate.

Abstract: The integration of the sub-6 GHz and millimeter-wave (mmWave) antennas has become an important issue for the next-generation wireless communication. For the mmWave band, adaptive beam steering is required to solve the path loss and coverage range problems. In this communication, an aperture-sharing technique is developed, so that a four-unit linear 28 GHz array and a 3.5 GHz dipole antenna can be integrated and the same aperture can be shared. The SIW is utilized to enable the integration and maintain the radiation of both antennas, without mutual interference. By adopting a separate feeding network, each mmWave array unit is independently excited, so that a beam steerable in the E-plane can be synthesized in the mmWave band. A prototype is fabricated with a compact size owing to the shared aperture. The measured results show good radiation characteristics and broad 10 dB impedance bandwidth exceeding 20% in both bands. Furthermore, the mmWave beam steering is obtained with a stable gain level. The proposed dual-frequency antenna is suitable for some terminal applications in the next-generation wireless networks.

Abstract: Accurate path loss (PL) prediction is essential for predicting transmitter coverage and optimizing wireless network performance. Traditional PL models are difficult to cope with the development trend of diversity, time-varying and mass wireless channels. In this work, the most widely used multilayer perceptron (MLP) neural network in artificial neural network (ANN) is employed to accurately predict PL. Three types of environmental features are defined and extracted, which describe the propagation environment only by considering limited environmental types instead of complex 3D environment modeling. Principal component analysis (PCA) is used to generate the low-dimensional environmental features, and eliminate redundant information among similar environmental types. Moreover, the information of base station (BS) and the receiver (Rx), including 3D locations, frequency, the transmitted power of BS, the antenna information, the feeder loss, and the received power of all the locations are obtained from the measurements. Different environmental features are combined with the information of BS and Rx to construct seven datasets for PL prediction models based on MLP neural networks. The impacts of the number of neurons in the hidden layer, the number of hidden layers, the number of training samples, and environmental features on PL prediction models are explored by considering the absolute value of mean error (AME), the mean absolute error (MAE), the standard deviation (STD) of error, the correlation coefficient, and the time ratio, respectively. This work aims to understand the propagation characteristics of radio waves, which can provide a theoretical basis for wireless network optimization and communication system design.

Abstract: Wireless sensor networks (WSNs) have received significant attention in the last few years in the agriculture field. Among the major challenges for sensor nodes’ deployment in agriculture is the path loss in the presence of dense grass or the height of trees. This results in degradation of communication link quality due to absorption, scattering, and attenuation through the crop’s foliage or trees. In this study, two new path-loss models were formulated based on the MATLAB curve-fitting tool for ZigBee WSN in a farm field. The path loss between the router node (mounted on a drone) and the coordinator node was modeled and derived based on the received signal strength indicator (RSSI) measurements with the particle swarm optimization (PSO) algorithm in the farm field. Two path-loss models were formulated based on exponential (EXP) and polynomial (POLY) functions. Both functions were combined with PSO, namely, the hybrid EXP-PSO and POLY-PSO algorithms, to find the optimal coefficients of functions that would result in accurate path-loss models. The results show that the hybrid EXP-PSO and POLY-PSO models noticeably improved the coefficient of determination (R2) of the regression line, with the mean absolute error (MAE) found to be 1.6 and 2.7 dBm for EXP-PSO and POLY-PSO algorithms. The achieved R2 in this study outperformed the previous state-of-the-art models. An accurate path-loss model is essential for smart agriculture application to determine the behavior of the propagated signals and to deploy the nodes in the WSN in a position that ensures data communication without unnecessary packets’ loss between nodes.

Abstract: The future 5G networks are expected to use millimeter wave (mmWave) frequency bands to take advantage of the large unused spectrum. However, due to the high path loss at mmWave frequencies, coverage of mmWave signals can get severely reduced, especially for non-line-of-sight (NLOS) scenarios as mmWave signals are severely attenuated when going through obstructions. In this work, we study the use of passive metallic reflectors of different shapes/sizes to improve 28 GHz mmWave signal coverage for both indoor and outdoor NLOS scenarios. We quantify the gains that can be achieved in the link quality with metallic reflectors using measurements, analytical expressions, and ray tracing simulations. In particular, we provide an analytical model for the end-to-end received power in an NLOS scenario using reflectors of different shapes and sizes. For a given size of the flat metallic sheet reflector approaching to the size of the incident beam, we show that the reflected received power for the NLOS link is the same as line-of-sight (LOS) free space received power of the same link distance. Extensive results are provided to study the impact of environmental features and reflector characteristics on NLOS link quality.

Abstract: In this paper, an intelligent reflecting surface (IRS) is deployed to assist the terahertz (THz) communications. The molecular absorption causes path loss peaks to appear in the THz frequency band, and the fading peak is greatly affected by the transmission distance. In this paper, we aim to maximize the sum rate with individual rate constraints, in which the IRS location, IRS phase shift, the allocation of sub-bands of the THz spectrum, and power control for UEs are jointly optimized. For the special case of a single user equipment (UE) with a single sub-band, the globally optimal solution is provided. For the general case with multiple UEs, the block coordinate searching (BCS) based algorithm is proposed to solve the non-convex problem. Simulation results show that the proposed scheme can significantly enhance system performance.

Abstract: Low-power wide-area technologies have demonstrated their usefulness in a wide variety of Internet of Things applications. New applications are emerging, requiring a mesh or point-to-point (P2P) topology, in contrast to the conventional star-of-stars topology. In this article, we evaluate the coverage and model the path loss (PL) of these links, based on experimental campaigns in three environments: 1) urban; 2) forest; and 3) coastal. More obstructions, scattering, and diffraction are encountered because the terminals are typically at a low height. This results in a higher PL compared to the star-of-stars topology. Consequently, more packets drop below the receiver sensitivity. Realistic PL parameters are estimated by also taking the censored data into account. The packet error ratio is determined based on the estimated PL parameters to evaluate the performance of P2P links. Even in these adverse environments, 80% of the transmitted packets are successfully received at a distance of approximately 200 m. Moreover, a range of over 4 km is observed in the line-of-sight scenario. Despite the unfavorable radio propagation in the urban scenario and the densely forested terrain, a maximum range of 1 km is achieved.

Abstract: Path loss prediction is essential for network planning in any wireless communication system. For cellular networks, it is usually achieved through extensive received signal power measurements in the target area. When the 3D model of an area is available, ray tracing simulations can be utilized; however, an important drawback of such an approach is the high computational complexity of the simulations. In this paper, we present a fundamentally different approach for path loss distribution prediction directly from 2D satellite images based on deep convolutional neural networks. While training process is time consuming and completed offline, inference can be done in real time. Another advantage of the proposed approach is that 3D model of the area is not needed during inference since the network simply uses an image captured by an aerial vehicle or satellite as its input. Simulation results show that the path loss distribution can be accurately predicted for different communication frequencies and transmitter heights.

Abstract: According to 3GPP, the frequency bands of 5G technologies are occupied at various parts of the frequency spectrum. E.g. mmWave frequencies are used for short-range communications in 5G mobile communications which can provide much higher bandwidth, supports greater data rates and also overcome the effect of path loss using carrier aggregation feature. However, the frequency bands for 5G wireless technology are classified into FR1 and FR2 frequency ranges. FR1 (4.1 GHz to 7.125 GHz) band of frequencies are used for carrying most of the traditional cellular mobile communications traffic, while the FR2 (24.25 GHz to 52.6 GHz) band of frequencies are focused on short-range, high data rate capabilities. A frequency selective wireless channel is converted into a parallel collection of frequency flat sub-channels using “Orthogonal Frequency Division Multiplexing (OFDM)” techniques that improve multipath fading issues and bandwidth efficiency, also reduces the inter-sub carrier interference. The recent wireless communication standards like 802.11x families combine the techniques of multiple-input-multiple-output (MIMO) and OFDM to provide improved data rates. As MIMO uses an array of antennas, and it is possible to achieve a higher signal-to-noise ratio (SNR) using “beamforming” which in turn reduces the bit error rate (BER). This research paper is focused on the performance of hybrid beamforming for single user and multi-user “massive MIMO-OFDM systems” and facilitate to explore various system-level configurations for different channel modellings in FR1 and FR2 bands.

Abstract: After disasters, network communication is highly susceptible to disruption. In this case, we may need solutions without original architectures to meet the requirements of connectivity and communication. As a research hotspot, existing studies and practices in disaster management are often costly and may have to rely on differentiated strategies to deal with actual situations. In this paper, we choose UAVs as edge node carriers and LoRaWAN (Long Range Wide Area Networking) as a communication method in coping with mobile edge computing (MEC) for disaster management. Here we propose UAV-mounted MEC task management strategies to achieve emergency communication enabled by LoRaWAN. The system model includes two parts, air-to-ground and remote-to-air, in which we choose LoS/NLoS path loss model and log-distance to describe the connections. The experiment results show that our strategy can achieve low-cost, long-range MEC service, which can be quickly deployed in the affected area after disasters. We also choose path loss, SNR (signal-noise ratio), and channel capacity as performance metrics and prove that our solutions can increase the channel capacity while maintaining the same level of path loss and SNR.

Abstract: An empirically based analysis of propagation characteristics in two vegetated suburban areas with different types and fractions of vegetation cover in 5G millimeter-wave (mmWave) bands is presented. A basic distance-dependent path loss model with a Gaussian random variance for shadow fading is utilized in accordance with the maximum-power directional and omnidirectional measurement data, therein exploiting significant path loss exponents in the presence of vegetation. In comparison with the existing ITU-R and 3GPP models, the effect of dense-leaved trees on path loss prediction is similar to that of buildings, whereas these standard models are inapplicable for sparse obstacle-line-of-sight (OLoS) links. Consequently, an azimuth-angle-based path loss characterization is proposed considering the antenna pattern, beam misalignment, and blockage effects. Moreover, several composite and cluster-level small-scale channel parameters, such as the number of clusters, delay spread, and angular spread, are extracted. Analysis of the first-arrival cluster in the OLoS setting reveals that forward scattering through foliage is still dominant and is expected to produce a larger azimuth angular spread of the arrival and compact multipath components in the time domain compared with line-of-sight and reflected clusters. The measurement results improve existing 3GPP channel models for suburban macrocell scenarios in mmWave bands.

Abstract: Low-terahertz (Low-THz, 100 GHz-1.0 THz) technology is expected to provide unprecedented data rates in future generations of wireless system such as the 6th generation (6G) mobile communication system. Increasing the carrier frequencies from millimeter wave to THz is a potential solution to guarantee the transmission rate and channel capacity. Due to the large transmission loss of Low-THz wave in free space, it is particularly urgent to design high-gain antennas to compensate the additional path loss, and to overcome the power limitation of Low-THz source. Recently, with the continuous updating and progress of additive manufacturing (AM) and 3D printing (3DP) technology, antennas with complicated structures can now be easily manufactured with high precision and low cost. In the first part, this paper demonstrates different approaches of recent development on wideband and high gain sub-millimeter-wave and Low-THz antennas as well as their fabrication technologies. In addition, the performances of the state-of-the-art wideband and high-gain antennas are presented. A comparison among these reported antennas is summarized and discussed. In the second part, one case study of a broadband high-gain antenna at 300 GHz is introduced, which is an all-metal model based on the Fabry–Perot cavity (FPC) theory. The proposed FPC antenna is very suitable for manufacturing using AM technology, which provides a low-cost, reliable solution for emerging THz applications.

Abstract: Intelligent reflecting surface (IRS) has been deemed as a transformative technology to achieve smart and reconfigurable environment for wireless communication. This letter studies a new IRS-aided communication system, where multiple IRSs assist in the communication between a multi-antenna base station (BS) and a remote single-antenna user by multi-hop signal reflection. Specifically, by exploiting the line-of-sight (LoS) link between nearby IRSs, a multi-hop cascaded LoS link between the BS and user is established where a set of IRSs are selected to successively reflect the BS's signal, so that the received signal power at the user is maximized. To tackle this new problem, we first present the closed-form solutions for the optimal active and cooperative passive beamforming at the BS and selected IRSs, respectively, for a given beam route. Then, we derive the end-to-end channel power, which unveils a fundamental trade-off in the optimal beam routing design between maximizing the multiplicative passive beamforming gain and minimizing the multi-reflection path loss. To reconcile this trade-off, we recast the IRS selection and beam routing problem as an equivalent shortest simple-path problem in graph theory and solve it optimally. Numerical results show significant performance gains of the proposed algorithm over benchmark schemes and also draw useful insights into the optimal beam routing design.

Abstract: This paper proposes a measurement based modeling of D-band indoor channels. Different indoor environments were considered including Line-of-Sight (LOS) and Non Line-of-Sight (NLOS) conditions. Double steering at the transmitter and receiver sides was performed allowing angular characterization of the channel. Path loss, delay spread, angular spread, intra- and inter- cluster characteristics were also modeled. These characteristics were then compared to the ones obtained in other millimeter wave bands for the same environment.

Abstract: This article presents details about an extensive channel measurement campaign and subsequent statistical channel models for the characterization of 300 GHz channels for wireless rack-to-rack (R2R) and blade-to-blade (B2B) communications in a data center-like environment. Measurements were conducted in various scenarios such as R2R line-of-sight (LoS), R2R obstructed-LoS (OLoS), R2R reflected-non-LoS (RNLoS), R2R obstructed-RNLoS (ORNLoS), B2B RNLoS, B2B ORNLoS, and B2B LoS scenarios. In the aforementioned scenarios, we explored the impact of transmitter (Tx)/receiver (Rx) misalignment and obstructions such as cables, metal cabinets, and mesh structures on terahertz (THz) propagation, as well as feasibility of using existing metal objects as reflectors for NLoS links. For the R2R LoS scenario, an optical lens was used to extend the Tx-Rx separation distance. This led to a waveguide effect in the channels measured thereby resulting into a path loss exponent (PLE) of 1.48 with a shadowing gain of 0.7 dB. When obstructions of cables are present, ORNLoS link outperforms OLoS link with 2.5 dB lower shadowing gain and weaker multipath. Reflector in the RNLoS link has reflection coefficients very close to 1 for all incident angles. For the B2B scenario, a dual-reflector THz transceiver rack system is proposed to enable wireless links across vertically stacked servers and allow easy maintenance and repair of servers. The measured path loss closely follows the Friis values in the LoS link and in the RNLoS link with hollow vertical ground plane. When obstructions of cables are present, the ORNLoS link experiences 5–10 dB higher path loss and on average 0.25 GHz lower coherence bandwidth than the RNLoS link. The measured statistical channel properties show that the shadowing gain caused by cable clusters follows the log-normal distribution.

Abstract: The performance demands from data-intensive applications, such as multimedia streaming, as well as the growing number of devices connecting to the Internet, will increase the need for higher capacity wireless communication links The research community has recently explored regions of the spectrum, including the Terahertz band (01 THz to 10 THz), that are underutilised for communications THz frequencies come with a plethora of special challenges, one of which is the very narrow effective beam, thereby requiring a Line of Sight (LoS) between sender and receiver Researchers have explored the use of reflectors that can redirect beams around blockages In this paper, we propose a THz signal guidance system where a Digital Twin is used to model, predict and control the signal propagation characteristics of an indoor space Our approach finds the best THz signal path from the base station to the mobile target via the tunable metamaterial walls, avoiding obstacles as needed, using geometric (ray tracing), path loss and Terahertz Potential Field (THzPF) models With this knowledge, the digital twin guides the selection of antenna strips at a base station and the reflectors along the signal path A top-view camera, with advanced image processing, provides context updates (obstacle and mobile target locations) to the digital twin The image processing system also senses factors like water vapour concentration, and the material composition and surface roughness of obstacles Such factors affect propagation strength, and the digital twin modifies the beam paths to adapt Simulation results have shown the efficiency of our control system to maintain a reliable signal connection while minimising the use of antenna and reflector strips Our system is the first proposal that maximises THz signal-to-noise ratio (SNR) through such a dynamic and robust control system, which integrates image processing of a room with base station configuration

Abstract: A lot of effort and time is utilized in the planning and building of the cellular wireless networks to use minimum infrastructural components to provide the best network coverage as well as delivery of quality of service Generally, path loss models are used for the prediction of wireless network coverage Therefore, detailed knowledge of the appropriate path loss model suitable for the proposed geographical area is needed to determine the coverage quality of any wireless network design However, to the best of our knowledge, despite the importance of path loss models, as used for the prediction of wireless network coverage, there doesn't exist any comprehensive survey in this field Therefore, the purpose of this paper is to survey the existing techniques and mechanisms which can be addressed in this domain Briefly, the contributions of this paper are: (1) providing a comprehensive and up to date survey of the various network coverage prediction techniques, indicating the different frequency ranges the models were developed, (2) the different suitable terrains for each of the model and the best suit mobile generation were presented, and lastly, (3) providing comparative analysis to aid the planning and implementation of the cellular networks

Abstract: Reconfigurable intelligent surface (RIS)-aided wireless communications have drawn significant attention recently. We study the physical layer security of the downlink RIS-aided transmission framework for randomly located users in the presence of a multi-antenna eavesdropper. To show the advantages of RIS-aided networks, we consider two practical scenarios: Communication with and without RIS. In both cases, we apply the stochastic geometry theory to derive exact probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-interference-plus-noise ratio. Furthermore, the obtained PDF and CDF are exploited to evaluate important security performance of wireless communication including the secrecy outage probability, the probability of nonzero secrecy capacity, and the average secrecy rate. Monte-Carlo simulations are subsequently conducted to validate the accuracy of our analytical results. Compared with traditional MIMO systems, the RIS-aided system offers better performance in terms of physical layer security. In particular, the security performance is improved significantly by increasing the number of reflecting elements equipped in a RIS. However, adopting RIS equipped with a small number of reflecting elements cannot improve the system performance when the path loss of NLoS is small.

Abstract: Fifth generation (5G) mobile networks are expected to play an increasing role in industrial communication with private mobile communication networks deployed on company premises. For planning, standardization and product development, it is crucial to to thoroughly understand the radio channel characteristics of such environments. Frequencies around 3.7 GHz were already reserved by regulation authorities and to meet the increasing demand for higher bandwidths, spectrum in the millimeter wave range around 28 GHz is targeted. This paper presents a wideband channel measurement campaign at both 3.7 and 28 GHz with direction-of-arrival information at 28 GHz. The results are compared to the 3GPP TR 38.901 Indoor Factory model and to two other recent papers. Evaluation of path loss and RMS delay and angle spread show the unique nature of industrial indoor environments.

Abstract: 5G millimeter wave (mmWave) communication is an efficient technique for low delay and high data rate transmission in vehicular networks. Due to the high path loss in 5G mmWave band, 5G base stations need to be densely deployed, which may result in great deployment expenditures. In this letter, we jointly consider a relay selection problem in multihop 5G mmWave device to device (D2D) transmissions and a power level allocation problem of mmWave D2D links. We propose a centralized hierarchical deep reinforcement learning based method to find an optimal solution for the problem. The proposed method does not rely on the information of links, and it tries to find an optimal solution based on the information of vehicles. Simulation results show that the convergence of the proposed method, and the transmission delay performance of proposed method is better than a link-quality-prediction based method, and close to a link-quality-known method.

Abstract: Methods for accurate prediction of radio signal quality parameters are crucial for optimization of mobile networks, and a necessity for future autonomous driving solutions. The power-distance relation of current empirical models struggles with describing the specific local geo-statistics that influence signal quality parameters. The use of empirical models commonly results in an over- or under-estimation of the signal quality parameters and require additional calibration studies.In this paper, we present a novel model-aided deep learning approach for path loss prediction, which implicitly extracts radio propagation characteristics from top-view geographical images of the receiver location. In a comprehensive evaluation campaign, we apply the proposed method on an extensive real-world data set consisting of five different scenarios and more than 125.000 individual measurements.It is found that 1) the novel approach reduces the average prediction error by up to 53 % in comparison to ray-tracing techniques, 2) A distance of $250 -300$ meters spanned by the images offer the necessary level of detail, 3) Predictions with a root-mean-squared error of $\approx 6$ dB is achieved across inherently different data sources.