Terrestrial Users Research Articles

A Mixed FSO/RF Integrated Satellite-High Altitude Platform Relaying Networks for Multiple Terrestrial Users with Presence of Eavesdropper: A Secrecy Performance

In this paper, the secrecy performance of a mixed free space optical (FSO)/radio frequency (RF) integrated satellite-high altitude platform (HAP) relaying networks for terrestrial multiusers with the existence of an eavesdropper is investigated. In this network, FSO is adopted to establish the link between the satellite and HAP for which it experiences Gamma-Gamma distributions under different detection schemes (i.e., heterodyne and intensity modulation direct detection). The transmission between the amplify-and-forward (AF) relaying HAP and terrestrial multiusers is through the RF and is modeled as shadowed-Rician fading distribution. Owning to broadcasting nature of RF link, it is assumed that an eavesdropper attempts to intercept the users’ confidential message, and the eavesdropper link is subjected to Rician distributions. Specifically, the closed-form expression for the system equivalent end-to-end cumulative distribution function is derived by exploiting the Meijer’s G and Fox’s H functions. Based on this expression, the exact closed-form expressions of the system connection outage probability, secrecy outage probability, and strictly positive secrecy capacity are obtained under the different detection schemes at HAP. Moreover, the asymptotic analyze of the system secrecy outage probability is provided to obtain more physical insights. Furthermore, the accuracy of all the derived analytical closed-form expressions is verified through the Monte-Carlo simulations. In addition, the impact of atmospheric turbulence, pointing errors, shadowing severity parameters, and Rician factor are thoroughly evaluated. Under the same system conditions, the results depict that heterodyne detection outperforms the intensity modulation direct detection.

REQIBA: Regression and Deep Q-Learning for Intelligent UAV Cellular User to Base Station Association

Unmanned Aerial Vehicles (UAVs) are emerging as important users of next-generation cellular networks. By operating in the sky, UAV users experience very different radio conditions than terrestrial users, due to factors such as strong Line-of-Sight (LoS) channels (and interference) and Base Station (BS) antenna misalignment. As a consequence, the UAVs may experience significant degradation to their received quality of service, particularly when they are moving and are subject to frequent handovers. The solution is to allow the UAV to be aware of its surrounding environment, and intelligently connect into the cellular network taking advantage of this awareness. In this paper we present REgression and deep Q-learning for Intelligent UAV cellular user to Base station Association (REQIBA), a solution that allows a UAV flying over an urban area to intelligently connect to underlying BSs, using information about the received signal powers, the BS locations, and the surrounding building topology. We demonstrate how REQIBA can as much as double the total UAV throughput, when compared to heuristic association schemes similar to those commonly used by terrestrial users. We also evaluate how environmental factors such as UAV height, building density, and throughput loss due to handovers impact the performance of our solution.

Routing protocol for heterogeneous FANETs with mobility prediction

In recent years, with the growth in Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. In these scenarios, the lack of reliable communication infrastructure has motivated UAVs to establish a network as flying nodes, also known as Flying Ad Hoc Networks (FANETs). However, in FANETs, the high mobility degree of flying and terrestrial users may be responsible for constant changes in the network topology, making end-to-end connections in FANETs challenging. Mobility estimation and prediction of UAVs can address the challenge mentioned above since it can provide better routing planning and improve overall FANET performance in terms of continuous service availability. We thus develop a Software Defined Network (SDN)-based heterogeneous architecture for reliable communication in FANETs. In this architecture, we apply an Extended Kalman Filter (EKF) for accurate mobility estimation and prediction of UAVs. In particular, we formulate the routing problem in SDN-based Heterogeneous FANETs as a graph decision problem. As the problem is NP-hard, we further propose a Directional Particle Swarming Optimization (DPSO) approach to solve it. The extensive simulation results demonstrate that the proposed DPSO routing can exhibit superior performance in improving the goodput, packet delivery ratio, and delay.

Latency versus Reliability in LEO Mega-Constellations: Terrestrial, Aerial, or Space Relay

Large low earth orbit (LEO) mega-constellation systems have been designed and deployed as a global backbone to provide ubiquitous connectivity across the world. However, due to the high traffic load/congestion arisen from the required numerous information relay and forwarding, it is a challenge for LEO mega-constellation systems to set up long-distance connections between two remote terrestrial users for real-time communications, which requires strict low latency. Other than inter-LEO satellite links (ILSL), introducing third-party relays, such as terrestrial, aerial, and satellite relays, is an alternative way to improve the latency performance for wide-area deliveries of real-time traffic. However, the reliability of the transmitted signal will unavoidably degrade, because of the increased path-loss attributed to long-distance relaying transmissions. Then, to reveal the principle that the third-party relays affect the latency and reliability, in this work, an LEO satellite-terrestrial communication scenario is considered, in which two remote terrestrial users communicate with each other via an LEO mega-constellation system. Analysis models are built up to investigate the end-to-end time delay and outage performance while considering different ILSL, terrestrial, aerial, and satellite relay assisted transmission scenarios. More specifically, by applying geometrical probability theory, exact/approximated closed-form analytical expressions have been derived for average time delay

Fresh, Fair and Energy-Efficient Content Provision in a Private and Cache-Enabled UAV Network

In this paper, we investigate a private and cache-enabled unmanned aerial vehicle (UAV) network for content provision. Aiming at delivering fresh, fair, and energy-efficient content files to terrestrial users, we formulate a joint UAV caching, UAV trajectory, and UAV transmit power optimization problem. This problem is confirmed to be a sequential decision problem with mixed-integer non-convex constraints, which is intractable directly. To this end, we propose a novel algorithm based on the techniques of subproblem decomposition and convex approximation. Particularly, we first propose to decompose the sequential decision problem into multiple repeated optimization subproblems via a Lyapunov technique. Next, an iterative optimization scheme incorporating a successive convex approximation (SCA) technique is explored to tackle the challenging mixed-integer non-convex subproblems. Besides, we analyze the convergence and computational complexity of the proposed algorithm and derive the theoretical value of the expected peak age of information (PAoI) to estimate the content freshness. Simulation results demonstrate that the proposed algorithm can achieve the expected PAoI close to the theoretical value and is more 22.11% and 70.51% energy-efficient and fairer than benchmark algorithms.

Joint Trajectory and Resource Optimization for UAV-Aided Two-Way Relay Networks

Unmanned aerial vehicle (UAV)-aided two-way relay networks with multiple terrestrial user pairs is investigated, where a fix-wing UAV is served as a two-way relay to assist information transmission. We aim to maximize the total rate of the two-way relay networks while the quality of service (QoS) being guaranteed. A novel relay strategy, namely <i>time-slots pairing</i>, is proposed by exploiting physical-layer network coding (PNC) protocol. Specifically, the UAV receives and buffers the signals from the scheduled user pair when the UAV approaches one of them, then forwards the modulated signal when the UAV is close to the other. As a result, a non-convex total rate maximization problem is formulated by joint trajectory design and resource optimization. To solve this problem, we first decompose it into three sub-problems, and then a three-step iterative algorithm that can effectively handle the non-convex problem with no worse than a polynomial complexity is developed leveraging the block coordinate descent (BCD) technique and successive convex approximation (SCA) method. Simulation results finally illustrate that: 1) Compared with amplify-and-forward (AF) or decode-and-forward (DF) protocols, the proposed design based on PNC protocol can significantly improve the total rate of the two-way relay networks; 2) the time-slots pairing relay strategy always achieves a significant enhancement on performance than the traditional non-time-slots pairing relay strategy; 3) the time-slots pairing relay strategy is more favorable for the mobile PNC relay networks since it can well resist the degradation of the entire networks caused by users&#x2019; increased service quality requirements.

Service Provisioning for UAV-Enabled Mobile Edge Computing

Unmanned aerial vehicle (UAV)-enabled mobile edge computing has been recognized as a promising technology to flexibly and efficiently handle computation-intensive and latency-sensitive tasks in the era of fifth generation (5G) and beyond. In this paper, we study the problem of Service Provisioning for UAV-enabled mobile edge computiNg (SPUN). Specifically, under task latency requirements and various resource constraints, we jointly optimize the service placement, UAV movement trajectory, task scheduling, and computation resource allocation, to minimize the overall energy consumption of all terrestrial user equipments (UEs). Due to the non-convexity of the SPUN problem as well as complex coupling among mixed integer variables, it is a non-convex mixed integer nonlinear programming (MINLP) problem. To solve this challenging problem, we propose two alternating optimization-based suboptimal solutions with different time complexities. In the first solution with relatively high complexity in the worst case, the joint service placement and task scheduling subproblem, and UAV trajectory subproblem are iteratively solved by the Branch and Bound (BnB) method and successive convex approximation (SCA), respectively, while the optimal solution to the computation resource allocation subproblem is efficiently obtained in the closed form. To avoid the high complexity caused by BnB, in the second solution, we propose a novel approximation algorithm based on relaxation and randomized rounding techniques for the joint service placement and task scheduling subproblem, while the other two subproblems are solved in the same way as that of the first solution. Extensive simulations demonstrate that the proposed solutions achieve significantly lower energy consumption of UEs compared to three benchmarks.

A Two-Layered Shared Tree Multicast Routing Algorithm for Software Defined Hybrid Satellite-Terrestrial Communication Networks

Dynamic routing and congestion control are two major problems in software-defined hybrid satellite-terrestrial multicast networks research. Due to terrestrial users being allowed to join or leave the multicast group at any time and the differences between the satellite and the terrestrial networks, many multicast routing algorithms reroute rapidly and thus increase the rerouting overheads. Meanwhile, the congestion ratio is increased by some hot nodes of satellite-terrestrial link transmission paths. This paper focuses on rerouting overheads and congestion problems in satellite-terrestrial multicast networks. We present a satellite-terrestrial network architecture with the Software-Defined Networking (SDN) features to offer dynamic multicast services for terrestrial users. A Two-Layered Shared Tree Multicast (TSTM) routing algorithm is proposed to achieve efficient dynamic multicast group management, address the trade-off between bandwidth consumption and rerouting overheads. The algorithm also implements congestion control by using a load factor to reflect on the global network bandwidth usage in routing calculations. This algorithm balances the rerouting frequencies of satellite and terrestrial networks to decrease the rerouting overheads and also reduces the network congestion ratio. The simulation shows TSTM decreases rerouting cost, user time delay, and node congestion ratio compared with the locality-aware multicast approach (LAMA).

Interference-Aware NOMA for Cellular-Connected UAVs: Stochastic Geometry Analysis

Efficiency of cellular-connected UAVs is challenged by spectrum inefficiency, limited number of concurrent connectivity, and strong interference. To overcome these issues, in this paper, we study the performance of downlink non-orthogonal multiple access for cellular-connected UAVs. We develop a novel framework based on stochastic geometry for the co-existence of aerial users (AUs) and terrestrial users (TUs), where the spatial distribution of the base stations (BSs) follows a Poisson Point Process. In our analysis, two user association policies and two types of receive antennas are considered while an inter-cell interference coordination (ICIC) technique is also in place. As the main performance measures, we then analytically derive the coverage probability and average rate of AUs and TUs. These derivations are then used to provide quantitative insights on the impact of different system parameters and settings including AU's altitude, TU's distance from the BS, power allocation, successive interference cancellation (SIC) constraints, user association policy, antenna beamwidth, and the number of coordinated BSs. Based on our analysis we then propose an interference-aware scheme based on maximum-SINR user association, directional antenna, and ICIC. A benchmark scheme based on minimum-distance user association, omni-directional antenna, and without ICIC is considered. Compared to the benchmark scheme, our proposed scheme improves the AU's coverage probability by threefold and TU's average rate by six-fold. Compared to the orthogonal multiple access, our proposed scheme trades off a slight reduction in the AU's coverage probability (~1%) with a significant increase in the achieved rate of the TUs (603Kbps/resource block).

Symbol Error Analysis of Amplify-and-Forward Based Multiuser Hybrid Satellite-Terrestrial Relay Network

In this letter, we study the average symbol error rate (ASER) performance in a multiuser hybrid satellite-terrestrial relay network (HSTRN) with opportunistic scheduling. The signal broadcast from the satellite is amplified by relay and forwarded to the terrestrial user that has the maximum instantaneous signal-to-noise ratio (SNR) in its channel. Specifically, both the approximate analytical formula and asymptotic expression at high SNRs of the ASER are derived for the fixed gain relaying as well as the variable gain relaying. Monte Carlo simulation are provided to verify our analysis and indicate the performance disparity between the two kinds of relaying protocols.

UAV Communications With WPT-Aided Cell-Free Massive MIMO Systems

Cell-free (CF) massive multiple-input multiple-output (MIMO) is a promising solution to provide uniform good performance for unmanned aerial vehicle (UAV) communications. In this paper, we propose the UAV communication with wireless power transfer (WPT) aided CF massive MIMO systems, where the harvested energy (HE) from the downlink WPT is used to support both uplink data and pilot transmission. We derive novel closed-form downlink HE and uplink spectral efficiency (SE) expressions that take hardware impairments of UAV into account. UAV communications with current small cell (SC) and cellular massive MIMO enabled WPT systems are also considered for comparison. It is significant to show that CF massive MIMO achieves two and five times higher 95%-likely uplink SE than the ones of SC and cellular massive MIMO, respectively. Besides, the large-scale fading decoding receiver cooperation can reduce the interference of the terrestrial user. Moreover, the maximum SE can be achieved by changing the time-splitting fraction. We prove that the optimal time-splitting fraction for maximum SE is determined by the number of antennas, altitude and hardware quality factor of UAVs. Furthermore, we propose three UAV trajectory design schemes to improve the SE. It is interesting that the angle search scheme performs best than both AP search and line path schemes. Finally, simulation results are presented to validate the accuracy of our expressions.

Sum Secrecy Rate Maximization in NOMA-Based Cognitive Satellite-Terrestrial Network

In this letter, we present a joint beamforming design for non-orthogonal multiple access (NOMA)-based cognitive satellite-terrestrial network (CSTN), where satellite network applies orthogonal multiple access (OMA) technology and NOMA scheme is utilized by the terrestrial network. The scheme key is to maximize sum secrecy rate of satellite users under the imperfect channel state information, while meeting the rate requirements of terrestrial users and transmit power constraints of the CSTN. Since the formulated optimization problem is non convex and intractable, we convert the original non convex maximization problem to a corresponding tractable convex one by successive convex approximation (SCA) and semidefinite relaxation (SDR), and then propose an SCA-based iterative beamforming algorithm to get the secure beamforming vectors. Finally, numerical simulation results are provided to verify the effectiveness and superiority of the proposed joint beamforming design.

Joint Beamforming for Integrated Mmwave Satellite-Terrestrial Self-Backhauled Networks

Satellite communication is considered as an efficient way to achieve the reliable communication for worldwide users. To further enhance the achievable rate of the satellite system, we propose joint beamforming schemes of an integrated satellite-terrestrial self-backhauled (ISTS) system, in which the satellite backhaul and terrestrial access links are operating at the same millimeter wave band. Specifically, the earth station and the base station (BS) constitute a self-backhauled relay to forward the satellite signals to the terrestrial users. A sum rate maximization problem is formulated under the constraints of the maximum power requirements of the satellite and the BS, the minimum quality-of-service requirements of the terrestrial users, and the maximum satellite backhaul capacity. To obtain some insights, we first assume that the perfect channel state information (CSI) on the satellite and terrestrial links is known and transform the formulated optimization problem to a standard difference of convex problem. Then we solve it iteratively by adopting the convex-concave procedure approach. Furthermore, when only imperfect CSI on the satellite and terrestrial links is available, we employ a iterative penalty function algorithm associated with the sequential convex approximation method and the S-procedure approach to obtain suboptimal beamforming vectors. Finally, simulation results demonstrate that the proposed joint beamforming schemes have better performance compared with other benchmark schemes and the ISTS architecture is suitable for the satellite systems in various orbits.

Airplane-Aided Integrated Next-Generation Networking

A high-rate yet low-cost air-to-ground (A2G) communication backbone is conceived for integrating the space and terrestrial network by harnessing the opportunistic assistance of the passenger planes or high altitude platforms (HAPs) as mobile base stations (BSs) and millimetre wave communication. The airliners act as the network-provider for the terrestrial users while relying on satellite backhaul. Three different beamforming techniques relying on a large-scale planar array are used for transmission by the airliner/HAP for achieving a high directional gain, hence minimizing the interference among the users. Furthermore, approximate spectral efficiency (SE) and area spectral efficiency (ASE) expressions are derived and quantified for diverse system parameters.

Multi-resources management in 6G-oriented terrestrial-satellite network

The six-generation (6G) wireless network is expected to satisfy the requirements of ubiquitous connectivity and intelligent endogenous. Terrestrial-satellite networks (TSN) enable seamless coverage for terrestrial users in a wide area, making it very promising in 6G. As data traffic in TSNs surges, the integrated management for caching, computing, and communication (3C) has attracted much research attention. In this paper, we investigate the multi-resource management in the uplink and downlink transmission of TSN, respectively. In particularly, we aim to guarantee both throughput fairness and data security in the uplink transmission of TSN. Considering the intermittent communication of the satellite, we introduce two kinds of relays, i.e., terrestrial relays (TRs) and aerial relays (ARs) to improve the system throughput performance in the downlink transmission of TSN. Finally, we study a specific case of TSN with the uplink and downlink transmission, and the corresponding simulation results validate the effectiveness of our proposed schemes.

UAVs as an Intelligent Service: Boosting Edge Intelligence for Air-Ground Integrated Networks

The air-ground integrated network is a key component of future sixth generation (6G) networks to support seamless and near-instant super-connectivity. There is a pressing need to intelligently provision various services in 6G networks, which however is challenging. To meet this need, in this article, we propose a novel architecture called UaaS (UAVs as a Service) for the air-ground integrated network, featuring UAV as a key enabler to boost edge intelligence with the help of machine learning (ML) techniques. We envision that the proposed UaaS architecture could intelligently provision wireless communication service, edge computing service, and edge caching service by a network of UAVs, making full use of UAVs' flexible deployment and diverse ML techniques. We also conduct a case study where UAVs participate in the model training of distributed ML among multiple terrestrial users, whose result shows that the model training is efficient with a negligible energy consumption of UAVs, compared to the flight energy consumption. Finally, we discuss the challenges and open research issues in the UaaS.

Uplink SINR Distribution of Terrestrial and Aerial Users With Power Control

Due to the particular line-of-sight (LoS) communication link, cellular-supported unmanned aerial vehicles will bring severe interference to terrestrial users. In such a context, we study on the uplink of terrestrial and aerial users with fractional power control via stochastic geometry. Specifically, with the aid of marked point process, an analytical framework is developed to derive the Laplace transform of uplink interference with LoS and NLoS propagation. In addition, distinct compensation factor and transmission power are adopted for terrestrial and aerial users to investigate their mutual effect. Interestingly, different from the single-peak results in related works, our results show that there exist two local maximum points of height for the operation of aerial users, while increasing density of networks makes the first point gradually vanish.

Capacity Analysis of Terrestrial Antenna Array in Distributed Satellite MIMO Communication System

Multiple-Input Multiple-Output (MIMO) techniques are able to enhance the channel capacity by multiplexing the space dimension resources. By constructing distributed satellite MIMO scenarios, MIMO techniques can be potentially employed to satellite communication networks. In this paper, we study the capacity performance of a distributed satellite communication network with the MIMO scheme that contains two geostationary earth orbit (GEO) satellites and a terrestrial antenna array. Specifically, the model of two kinds of terrestrial antenna array, uniform linear array (ULA) and uniform circular array (UCA), are proposed and the coordinate representation of the array elements is provided by coordinate system transformation. Then, the analytical expressions of the system capacity with different antenna arrays are derived considering the rotation angle of the antenna array. The Min-Max ratio is investigated for both ULA and UCA to gain further insights of the system capacity performance. Finally, numerical simulations are provided to validate the analytical expressions, show the impact of the rotation angle and other system parameters on the capacity performance. The research results show that ULA is preferred for terrestrial users with fixed locations and the maximum channel capacity can be obtained through adjusting the rotation angle while UCA is not only suitable for fixed locations, but can also be used in mobile scenarios such as vehicles, ships to ensure the stability of the system capacity.

VNF-Based Service Provision in Software Defined LEO Satellite Networks

Low earth orbit (LEO) satellite networks will play important roles in the sixth generation (6G) communication system. Software defined network technique is a novel approach introduced to the LEO satellite networks to improve the resource flexibility and efficiency, forming the software defined LEO satellite networks (SDLSNs). How to efficiently allocate the resources of SDLSN to provide services for the terrestrial users is a key issue. Hence, in this work, we explore the service provision for SDLSN via virtual network functions (VNFs) orchestration on the software defined time-evolving graph. In view of the scarce, intermittent and unstable satellite-to-satellite (S2S) links, the problem is formulated to minimize the S2S resource consumption while satisfying the terrestrial tasks, which is in the form of integer linear programming. Since the problem is intractable by exhaustive search, we design a branch-and-price algorithm based on the coupling of Dantzig-Wolfe decomposition, column generation, and branch-and-bound to efficiently acquire the optimal solution. Further, to obtain a faster solution for practical usage, we further design an approximation algorithm for the subproblem and leverage the beam search to accelerate the pruning for the search tree. Finally, extensive simulations are conducted and the numerical results validate the effectiveness of the proposed schemes.

GA-based Energy Aware Path Planning Framework for Aerial Network Assistance

Aerial networks have enormous potential to assist terrestrial communications under heavy traffic requests for a predictable duration. However, such potential for improving both the performance and the coverage through the use of drones can face a major challenge in terms of power limitation. Hence, we consider the energy consumption characteristic of the components in such networks to provide energy aware flight path planning. For this purpose, a flight path planning scheme is proposed on an underlying topology graph that models the energy consumption of path traversals in the aerial network. In the proposed model, we offer to seek for the minimum energy consumption on a global problem domain during the entire operational time. Thus, we provide a concrete problem formulation and implement a flight path planning with Genetic Algorithms (GA) approach. Moreover, a novel end-system initiated handover procedure is illustrated to preserve connectivity of terrestrial users in the network architecture. In the end, the evaluation of the proposed model is conducted under three different scales of social event scenarios. A comparison with a dummy path planning scheme without energy awareness concerns is presented according to a set of parameters. The evaluation outcomes show that the proposed model is able to save 20% energy consumption, provides 15% less number of terrestrial replenishment, and 18% more average endurance for the topology. Besides, another energy aware path planning scheme in the literature offering a deployment with Bellman Ford algorithm is also included in the evaluation to evaluate the feasibility of the proposed framework for the enhanced problem domain.