Unmanned Aerial Vehicles (UAVs) for Integrated Access and Backhaul (IAB) Communications in Wireless Cellular Networks

An integrated access and backhaul (IAB) network architecture can enable flexible and fast deployment of next-generation cellular networks. However, mutual interference between access and backhaul links, small inter-site distance and spatial dynamics of user distribution pose major challenges in the practical deployment of IAB networks. To tackle these problems, we leverage the flying capabilities of unmanned aerial vehicles (UAVs) as hovering IAB-nodes and propose an interference management algorithm to maximize the overall sum rate of the IAB network. In particular, we jointly optimize the user and base station associations, the downlink power allocations for access and backhaul transmissions, and the spatial configurations of UAVs. We consider two spatial configuration modes of UAVs: distributed UAVs and drone antenna array (DAA), and show how they are intertwined with the spatial distribution of ground users. Our numerical results show that the proposed algorithm achieves an average of 2.9× and 6.7× gains in the received downlink signal-to-interference-plus-noise ratio (SINR) and overall network sum rate, respectively. Finally, the numerical results reveal that UAVs cannot only be used for coverage improvement but also for capacity boosting in IAB cellular networks

Reliable and Secure Drone-assisted MillimeterWave Communications

The next generation of mobile networks and wireless communication, including the fifth-generation (5G) and beyond, will provide a high data rate as one of its fundamental requirements. Providing high data rates can be accomplished through communication over high-frequency bands such as the Millimeter-Wave(mmWave) one. However, mmWave communication experiences short-range communication, which impacts the overall network connectivity. Improving network connectivity can be accomplished through deploying Unmanned Ariel Vehicles(UAVs), commonly known as drones, which serve as aerial small-cell base stations. Moreover, drone deployment is of special interest in recovering network connectivity in the aftermath of disasters. Despite the potential advantages, drone-assisted networks can be more vulnerable to security attacks, given their limited capabilities. This security vulnerability is especially true in the aftermath of a disaster where security measures could be at their lowest. This thesis focuses on drone-assisted mmWave communication networks with their potential to provide reliable communication in terms of higher network connectivity measures, higher total network data rate, and lower end-to-end delay. Equally important, this thesis focuses on proposing and developing security measures needed for drone-assisted networks’ secure operation. More specifically, we aim to employ a swarm of drones to have more connection, reliability, and secure communication over the mmWave band. Finally, we target both the cellular 5Gnetwork and Ad hoc IEEE802.11ad/ay in typical network deployments as well as in post-disaster circumstances

An Experimental mmWave Channel Model for UAV-to-UAV Communications

Unmanned Aerial Vehicle (UAV) networks can provide a resilient communication infrastructure to enhance terrestrial networks in case of traffic spikes or disaster scenarios. However, to be able to do so, they need to be based on high-bandwidth wireless technologies for both radio access and backhaul. With this respect, the millimeter wave (mmWave) spectrum represents an enticing solution, since it provides large chunks of untapped spectrum that can enable ultra-high data-rates for aerial platforms. Aerial mmWave channels, however, experience characteristics that are significantly different from terrestrial deployments in the same frequency bands. As of today, mmWave aerial channels have not been extensively studied and modeled. Specifically, the combination of UAV micro-mobility (because of imprecisions in the control loop, and external factors including wind) and the highly directional mmWave transmissions require ad hoc models to accurately capture the performance of UAV deployments. To fill this gap, we propose an empirical propagation loss model for UAV-to-UAV communications at 60 GHz, based on an extensive aerial measurement campaign conducted with the Facebook Terragraph channel sounders. We compare it with 3GPP channel models and make the measurement dataset publicly available.Comment: 7 pages, 7 figures, 3 tables. Please cite it as M. Polese, L. Bertizzolo, L. Bonati, A. Gosain, T. Melodia, An Experimental mmWave Channel Model for UAV-to-UAV Communications, in Proc. of ACM Workshop on Millimeter-Wave Networks and Sensing Systems (mmNets), London, UK, Sept. 202

Terahertz Communications and Sensing for 6G and Beyond: A Comprehensive View

The next-generation wireless technologies, commonly referred to as the sixth generation (6G), are envisioned to support extreme communications capacity and in particular disruption in the network sensing capabilities. The terahertz (THz) band is one potential enabler for those due to the enormous unused frequency bands and the high spatial resolution enabled by both short wavelengths and bandwidths. Different from earlier surveys, this paper presents a comprehensive treatment and technology survey on THz communications and sensing in terms of the advantages, applications, propagation characterization, channel modeling, measurement campaigns, antennas, transceiver devices, beamforming, networking, the integration of communications and sensing, and experimental testbeds. Starting from the motivation and use cases, we survey the development and historical perspective of THz communications and sensing with the anticipated 6G requirements. We explore the radio propagation, channel modeling, and measurements for THz band. The transceiver requirements, architectures, technological challenges, and approaches together with means to compensate for the high propagation losses by appropriate antenna and beamforming solutions. We survey also several system technologies required by or beneficial for THz systems. The synergistic design of sensing and communications is explored with depth. Practical trials, demonstrations, and experiments are also summarized. The paper gives a holistic view of the current state of the art and highlights the issues and challenges that are open for further research towards 6G.Comment: 55 pages, 10 figures, 8 tables, submitted to IEEE Communications Surveys & Tutorial

Performance evaluation of next generation wireless UAV relay with millimeter-wave in access and backhaul

Future wireless communication, particularly densified 5G networks, will bring numerous innovations to the telecommunication industry and will support 100-fold gain in throughput rates, 100-fold in capacity (for at least 100 billion devices), individual user data rate of up-to 10 Gb/s, extremely low latency and response times. In such a scenario, the use of Unmanned Aerial Vehicle (UAV) as a Base Station (gNB) becomes a viable option for providing 5G services, both on-demand and on a regular basis. Recent development of UAVs have made its deployment faster and reliable, resulting in a shift in its usage from traditional military to more commercial and corporate industries. On the other hand, due to the abundant availability of bandwidth in the millimeter-wave band (mmWave), there is an immense potential to utilize this band for next generation radio systems. In this case, smart integration of UAVs in 5G network provides immense potential, however, such network require efficient placement mechanism for providing blazingly fast wireless cellular network services. In this study, we analyze and describe the distinctive characteristics of mmWave propagation. The main goal is to investigate and evaluate the use of mmWave in Access and Back-haul communication links simultaneously for Amplify-and-Forward relays deployed on UAVs. We formulate the required mathematical framework for calculating the UE received power for direct path (gNB-UE) and relay path (gNB-UAV-UE) based on two cases; (i) Friis Transmission Equation and (ii) Log-Distance Path loss Model. We conduct simulations using ray-tracing simulator in different scenarios while comparing and verifying the simulation results vs mathematical equations. For the proposed system architecture, International Telecommunication Union (ITU) recommendation city model is used to calculate the probability for Line of Sight (LoS) and Non Line of Sight (NLoS) paths in different urban environments. Furthermore, we study and identify different parameters i.e., UAV location, and amplification factor to maximize the performance of an Amplify-and-Forward UAV based relay for providing enhanced coverage to the users. Similarly, the optimum UAV-gNB height is evaluated in different urban environments while providing coverage to the users via an Amplify-and-Forward relay. The study concludes with the Signal to Noise Ratio (SNR) analysis for the relay path compared with the direct path where we identify the constraints for effective relaying

Airborne Integrated Access and Backhaul Systems : Learning-Aided Modeling and Optimization

The deployment of millimeter-wave (mmWave) 5G New Radio (NR) networks is hampered by the properties of the mmWave band, such as severe signal attenuation and dynamic link blockage, which together limit the cell range. To provide a cost-efficient and flexible solution for network densification, 3GPP has recently proposed integrated access and backhaul (IAB) technology. As an alternative approach to terrestrial deployments, the utilization of unmanned aerial vehicles (UAVs) as IAB-nodes may provide additional flexibility for topology configuration. The aims of this study are to (i) propose efficient optimization methods for airborne and conventional IAB systems and (ii) numerically quantify and compare their optimized performance. First, by assuming fixed locations of IAB-nodes, we formulate and solve the joint path selection and resource allocation problem as a network flow problem. Then, to better benefit from the utilization of UAVs, we relax this constraint for the airborne IAB system. To efficiently optimize the performance for this case, we propose to leverage deep reinforcement learning (DRL) method for specifying airborne IAB-node locations. Our numerical results show that the capacity gains of airborne IAB systems are notable even in non-optimized conditions but can be improved by up to 30 % under joint path selection and resource allocation and, even further, when considering aerial IAB-node locations as an additional optimization criterion.acceptedVersionPeer reviewe

Map-based Channel Modeling and Generation for U2V mmWave Communication

Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including interpath and intra-path are analyzed in detail. The inter-path parameters are calculated in a deterministic way, while the parameters of intra-path rays are generated in a stochastic way. The statistical properties are obtained by using a Gaussian mixture model (GMM) on the massive ray tracing (RT) data. Then, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. Meanwhile, to reduce the complexity of RT method, the 3D propagation space is reconstructed based on the user-defined digital map. The simulated and analyzed results show that the proposed model and generation method can reproduce non-stationary U2V channels in accord with U2V scenarios. The generated statistical properties are consistent with the theoretical and measured ones as well

A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks

The fifth generation (5G) mobile networks are envisaged to enable a plethora of breakthrough advancements in wireless technologies, providing support of a diverse set of services over a single platform. While the deployment of 5G systems is scaling up globally, it is time to look ahead for beyond 5G systems. This is driven by the emerging societal trends, calling for fully automated systems and intelligent services supported by extended reality and haptics communications. To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks. In this article, we shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing, and energy, from its core to its end nodes. Particularly, this paper aims to answer several 6G framework related questions: What are the driving forces for the development of 6G? How will the enabling technologies of 6G differ from those in 5G? What kind of applications and interactions will they support which would not be supported by 5G? We address these questions by presenting a profound study of the 6G vision and outlining five of its disruptive technologies, i.e., terahertz communications, programmable metasurfaces, drone-based communications, backscatter communications and tactile internet, as well as their potential applications. Then, by leveraging the state-of-the-art literature surveyed for each technology, we discuss their requirements, key challenges, and open research problems