Sung Joon Maeng

Bio: Sung Joon Maeng is an academic researcher from North Carolina State University. The author has contributed to research in topics: Engineering & Cellular network. The author has an hindex of 6, co-authored 30 publications receiving 94 citations. Previous affiliations of Sung Joon Maeng include Chung-Ang University.

3-D Trajectory Optimization in UAV-Assisted Cellular Networks Considering Antenna Radiation Pattern and Backhaul Constraint

Abstract: This article explores the effects of 3-D antenna radiation pattern and backhaul constraint on optimal 3-D path planning problem of an unmanned aerial vehicle (UAV), in interference prevalent downlink cellular networks. We consider a cellular-connected UAV that is tasked to travel between two locations within a fixed time, and it can be used to improve the cellular connectivity of ground users by acting as a relay. Since the antenna gain of a cellular base station changes significantly with the UAV altitude, the UAV can improve the signal quality in its backhaul link by changing its height over the course of its mission. This problem is nonconvex, and thus, we explore the dynamic programming technique to solve it. We show that the 3-D optimal paths can introduce significant network performance gain over the trajectories with fixed UAV heights.

Precoder Design for Physical-Layer Security and Authentication in Massive MIMO UAV Communications

Abstract: Supporting reliable and seamless wireless connectivity for unmanned aerial vehicles (UAVs) has recently become a critical requirement to enable various different use cases of UAVs. Due to their widespread deployment footprint, cellular networks can support beyond visual line of sight (BVLOS) communications for UAVs. In this paper, we consider cellular connected UAVs (C-UAVs) that are served by massive multiple-input-multiple-output (MIMO) links to extend coverage range, while also improving physical layer security and authentication. We consider Rician channel and propose a novel linear precoder design for transmitting data and artificial noise (AN). We derive the closed-form expression of the ergodic secrecy rate of C-UAVs for both conventional and proposed precoder designs. In addition, we obtain the optimal power splitting factor that divides the power between data and AN by asymptotic analysis. Then, we apply the proposed precoder design in the fingerprint embedding authentication framework, where the goal is to minimize the probability of detection of the authentication tag at an eavesdropper. In simulation results, we show the superiority of the proposed precoder in both secrecy rate and the authentication probability considering moderate and large number of antenna massive MIMO scenarios.

Effects of 3D Antenna Radiation and Two-Hop Relaying on Optimal UAV Trajectory in Cellular Networks

Abstract: In this paper, considering an interference limited inband downlink cellular network, we study the effects of scheduling criteria, mobility constraints, path loss models, backhaul constraints, and 3D antenna radiation pattern on trajectory optimization problem of an unmanned aerial vehicle (UAV). In particular, we consider a UAV that is tasked to travel between two locations within a given amount of time (e.g., for delivery or surveillance purposes), and we consider that such a UAV can be used to improve cellular connectivity of mobile users by serving as a relay for the terrestrial network. As the optimization problem is hard to solve numerically, we explore the dynamic programming (DP)technique for finding the optimum UAV trajectory. We utilize capacity and coverage performance of the terrestrial network while studying all the effects of different techniques and phenomenon. Extensive simulations show that the maximum sum-rate trajectory provides the best per user capacity whereas, the optimal proportional fair (PF)rate trajectory provides higher coverage probability than the other two. Since, the generated trajectories are infeasible for the UAV to follow exactly as it can not take sharp turns due to kinematic constraints, we generate smooth trajectory using Bezier curves. Our results show that the cellular capacity using the Bezier curves is close to the capacity observed when using the optimal trajectories.

Preamble Design Technique for GMSK-Based Beamforming System With Multiple Unmanned Aircraft Vehicles

Abstract: The use of beamforming techniques at the ground station is known to be effective in obtaining coverage extension or SNR gain for communication with unmanned aerial vehicles (UAVs). When a UAV moves, periodic beam tracking is necessary to maintain beam gain. To track beams for multiple UAVs, the ground station needs to receive different preambles from multiple UAVs. In this paper, a Hadamard sequence is considered for designing preambles for multiple UAVs because of its ideal cross-correlation property. A preamble that is appropriate for a Gaussian minimum shift keying (GMSK)-based communication system with multiple UAVs is proposed after analyzing the property of received signals in the system with the Hadamard sequence as the input. A preamble appropriate for asynchronous channel environments is also proposed after analyzing the property of the signals received from multiple UAVs with different time delays. The performance of the proposed preambles in the GMSK-based communication system with multiple UAVs is evaluated via simulation with a 3-D spatial channel model in both synchronous and asynchronous channel environments.

Precoder Design for mmWave UAV Communications with Physical Layer Security

Abstract: The integration of unmanned aerial vehicles (UAVs) into the terrestrial cellular networks is envisioned as one key technology for next-generation wireless communications. In this work, we consider the physical layer security of the communications links in the millimeter-wave (mmWave) spectrum which are maintained by UAVs functioning as base stations (BS). In particular, we propose a new precoding strategy which incorporates the channel state information (CSI) of the eavesdropper (Eve) compromising link security. We show that our proposed precoder strategy eliminates any need for artificial noise (AN) transmission in underloaded scenarios (fewer users than number of antennas). In addition, we demonstrate that our nonlinear precoding scheme provides promising secrecy-rate performance even for overloaded scenarios at the expense of transmitting low-power AN.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

Abstract: This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

Millimeter wave beamforming for wireless backhaul and access in small cell networks and practical approaches in software-defined radio

Abstract: Mobile data traffic will continue its tremendous growth in some markets, and has already resulted in an apparent radio spectrum scarcity. There is a strong need for more efficient methods to use spectrum resources, leading to extensive research on increasing spectrum reusability on flexible radio platforms. This study solves this problem in two sub topics, millimeter wave communication on wireless backhaul for spectrum reusability, and flexible prototyping radio platform using software-defined radio (SDR). Wireless backhaul has received significant attention as a key technology affecting the development of future wireless cellular networks because it helps to easily deploy many small size cells, an essential part of a high capacity system. Millimeter wave is considered a possible candidate for cost-effective wireless backhaul. In the outdoor deployment using a millimeter wave, beamforming methods are key techniques to establish wireless links in the 60 GHz to 80 GHz to overcome pathloss constraints (i.e., rainfall effect and oxygen absorption). The millimeter wave communication system cannot directly access the channel knowledge. To overcome this, a beamforming method based on codebook search is considered. The millimeter wave communication cannot access channel knowledge, therefore alternatively a beamforming method based on a codebook search is considered. In the first part, we propose an efficient beam alignment technique using adaptive subspace sampling and hierarchical beam codebooks. A wind sway analysis is presented to establish a notion of beam coherence time. This highlights a previously unexplored tradeoff between array size and wind-induced movement. Generally, it is not possible to use larger arrays without risking a performance loss from wind-induced beam misalignment. The performance of the proposed alignment technique is analyzed and compared with other search and alignment methods. Results show significant performance improvement with reduced search time. In the second part of this study, SDR is discussed as an approach toward flexible wireless communication systems. Most layers of SDR are implemented by software. Therefore, only a software change is needed to transform the type of radio system. The translation of the signal processing into software performed by a regular computer opens up a huge number of possibilities at a reasonable price and effort. SDR systems are widely used to build prototypes, saving time and money. In this project, a robust wireless communication system in high interference environment was developed. For the physical layer (PHY) of the system, we implemented a channel sub-bandding method that utilizes frequency division multiplexing to avoid interference. Then, to overcome a further interfered channel, Direct Spread Spectrum System (DSSS) was considered and implemented. These prototyped testbeds were evaluated for system performance in the interference environment.

Simultaneous Navigation and Radio Mapping for Cellular-Connected UAV With Deep Reinforcement Learning

Abstract: Cellular-connected unmanned aerial vehicle (UAV) is a promising technology to unlock the full potential of UAVs in the future by reusing the cellular base stations (BSs) to enable their air-ground communications. However, how to achieve ubiquitous three-dimensional (3D) communication coverage for the UAVs in the sky is a new challenge. In this paper, we tackle this challenge by a new coverage-aware navigation approach, which exploits the UAV’s controllable mobility to design its navigation/trajectory to avoid the cellular BSs’ coverage holes while accomplishing their missions. To this end, we formulate an UAV trajectory optimization problem to minimize the weighted sum of its mission completion time and expected communication outage duration, which, however, cannot be solved by the standard optimization techniques due to the lack of an accurate and tractable end-to-end communication model in practice. To overcome this difficulty, we propose a new solution approach based on the technique of deep reinforcement learning (DRL). Specifically, by leveraging the state-of-the-art dueling double deep Q network (dueling DDQN) with multi-step learning, we first propose a UAV navigation algorithm based on direct RL, where the signal measurement at the UAV is used to directly train the action-value function of the navigation policy. To further improve the performance, we propose a new framework called simultaneous navigation and radio mapping (SNARM) , where the UAV’s signal measurement is used not only for training the DQN directly, but also to create a radio map that is able to predict the outage probabilities at all locations in the area of interest. This enables the generation of simulated UAV trajectories and predicting their expected returns, which are then used to further train the DQN via Dyna technique, thus greatly improving the learning efficiency.

A Survey of Wireless Networks for Future Aerial Communications (FACOM)

Abstract: Electrification turned over a new leaf in aviation by introducing new types of aerial vehicles along with new means of transportation. Addressing a plethora of use cases, drones are gaining attention in the industry and increasingly appear in the sky. Emerging concepts of flying taxi enable passengers to be transported over several tens of kilometers. Therefore, unmanned traffic management systems are under development to cope with the complexity of future airspace, thereby resulting in unprecedented communication needs. Moreover, the long-term increase in the number of commercial airplanes pushes the limits of voice-oriented communications, and future options such as single-pilot operations demand robust connectivity. In this survey, we provide a comprehensive review and vision for enabling the connectivity applications of aerial vehicles utilizing current and future communication technologies. We begin by categorizing the connectivity use cases per aerial vehicle and analyzing their connectivity requirements. By reviewing more than 500 related studies, we aim for a comprehensive approach to cover wireless communication technologies, and provide an overview of recent findings from the literature toward the possibilities and challenges of employing the wireless communication standards. After analyzing the proposed network architectures, we list the open-source testbed platforms to facilitate future investigations by researchers. This study helped us observe that while numerous works focused on cellular technologies to enable connectivity for aerial platforms, a single wireless technology is not sufficient to meet the stringent connectivity demands of the aerial use cases, especially for the piloting operations. We identified the need of further investigations on multi-technology heterogeneous network architectures to enable robust and real-time connectivity in the sky. Future works should consider suitable technology combinations to develop unified aerial networks that can meet the diverse quality of service demands of the aerial use cases.

3-D Trajectory Optimization in UAV-Assisted Cellular Networks Considering Antenna Radiation Pattern and Backhaul Constraint

Abstract: This article explores the effects of 3-D antenna radiation pattern and backhaul constraint on optimal 3-D path planning problem of an unmanned aerial vehicle (UAV), in interference prevalent downlink cellular networks. We consider a cellular-connected UAV that is tasked to travel between two locations within a fixed time, and it can be used to improve the cellular connectivity of ground users by acting as a relay. Since the antenna gain of a cellular base station changes significantly with the UAV altitude, the UAV can improve the signal quality in its backhaul link by changing its height over the course of its mission. This problem is nonconvex, and thus, we explore the dynamic programming technique to solve it. We show that the 3-D optimal paths can introduce significant network performance gain over the trajectories with fixed UAV heights.