Showing papers in "IEEE Journal on Selected Areas in Communications in 2018"

Task Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network

Abstract: With the development of recent innovative applications (e.g., augment reality, self-driving, and various cognitive applications), more and more computation-intensive and data-intensive tasks are delay-sensitive. Mobile edge computing in ultra-dense network is expected as an effective solution for meeting the low latency demand. However, the distributed computing resource in edge cloud and energy dynamics in the battery of mobile device makes it challenging to offload tasks for users. In this paper, leveraging the idea of software defined network, we investigate the task offloading problem in ultra-dense network aiming to minimize the delay while saving the battery life of user’s equipment. Specifically, we formulate the task offloading problem as a mixed integer non-linear program which is NP-hard. In order to solve it, we transform this optimization problem into two sub-problems, i.e., task placement sub-problem and resource allocation sub-problem. Based on the solution of the two sub-problems, we propose an efficient offloading scheme. Simulation results prove that the proposed scheme can reduce 20% of the task duration with 30% energy saving, compared with random and uniform task offloading schemes.

A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead

Abstract: Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution toward 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, and so on. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.

Computation Rate Maximization in UAV-Enabled Wireless-Powered Mobile-Edge Computing Systems

Abstract: Mobile-edge computing (MEC) and wireless power transfer are two promising techniques to enhance the computation capability and to prolong the operational time of low-power wireless devices that are ubiquitous in Internet of Things. However, the computation performance and the harvested energy are significantly impacted by the severe propagation loss. In order to address this issue, an unmanned aerial vehicle (UAV)-enabled MEC wireless-powered system is studied in this paper. The computation rate maximization problems in a UAV-enabled MEC wireless powered system are investigated under both partial and binary computation offloading modes, subject to the energy-harvesting causal constraint and the UAV’s speed constraint. These problems are non-convex and challenging to solve. A two-stage algorithm and a three-stage alternative algorithm are, respectively, proposed for solving the formulated problems. The closed-form expressions for the optimal central processing unit frequencies, user offloading time, and user transmit power are derived. The optimal selection scheme on whether users choose to locally compute or offload computation tasks is proposed for the binary computation offloading mode. Simulation results show that our proposed resource allocation schemes outperform other benchmark schemes. The results also demonstrate that the proposed schemes converge fast and have low computational complexity.

Energy-Efficient UAV Control for Effective and Fair Communication Coverage: A Deep Reinforcement Learning Approach

Abstract: Unmanned aerial vehicles (UAVs) can be used to serve as aerial base stations to enhance both the coverage and performance of communication networks in various scenarios, such as emergency communications and network access for remote areas. Mobile UAVs can establish communication links for ground users to deliver packets. However, UAVs have limited communication ranges and energy resources. Particularly, for a large region, they cannot cover the entire area all the time or keep flying for a long time. It is thus challenging to control a group of UAVs to achieve certain communication coverage in a long run, while preserving their connectivity and minimizing their energy consumption. Toward this end, we propose to leverage emerging deep reinforcement learning (DRL) for UAV control and present a novel and highly energy-efficient DRL-based method, which we call DRL-based energy-efficient control for coverage and connectivity (DRL-EC3). The proposed method 1) maximizes a novel energy efficiency function with joint consideration for communications coverage, fairness, energy consumption and connectivity; 2) learns the environment and its dynamics; and 3) makes decisions under the guidance of two powerful deep neural networks. We conduct extensive simulations for performance evaluation. Simulation results have shown that DRL-EC3 significantly and consistently outperform two commonly used baseline methods in terms of coverage, fairness, and energy consumption.

Flight Time Minimization of UAV for Data Collection Over Wireless Sensor Networks

Abstract: In this paper, we consider a scenario where an unmanned aerial vehicle (UAV) collects data from a set of sensors on a straight line. The UAV can either cruise or hover while communicating with the sensors. The objective is to minimize the UAV’s total flight time from a starting point to a destination while allowing each sensor to successfully upload a certain amount of data using a given amount of energy. The whole trajectory is divided into non-overlapping data collection intervals, in each of which one sensor is served by the UAV. The data collection intervals, the UAV’s speed, and the sensors’ transmit powers are jointly optimized. The formulated flight time minimization problem is difficult to solve. We first show that when only one sensor is present, the sensor’s transmit power follows a water-filling policy and the UAV’s speed can be found efficiently by bisection search. Then, we show that for the general case with multiple sensors, the flight time minimization problem can be equivalently reformulated as a dynamic programming (DP) problem. The subproblem involved in each stage of the DP reduces to handle the case with only one sensor node. Numerical results present the insightful behaviors of the UAV and the sensors. Specifically, it is observed that the UAV’s optimal speed is proportional to the given energy of the sensors and the inter-sensor distance, but it is inversely proportional to the data upload requirement.

Follow Me at the Edge: Mobility-Aware Dynamic Service Placement for Mobile Edge Computing

Abstract: Mobile edge computing is a new computing paradigm, which pushes cloud computing capabilities away from the centralized cloud to the network edge. However, with the sinking of computing capabilities, the new challenge incurred by user mobility arises: since end users typically move erratically, the services should be dynamically migrated among multiple edges to maintain the service performance, i.e., user-perceived latency. Tackling this problem is non-trivial since frequent service migration would greatly increase the operational cost. To address this challenge in terms of the performance-cost tradeoff, in this paper, we study the mobile edge service performance optimization problem under long-term cost budget constraint. To address user mobility which is typically unpredictable, we apply Lyapunov optimization to decompose the long-term optimization problem into a series of real-time optimization problems which do not require a priori knowledge such as user mobility. As the decomposed problem is NP-hard, we first design an approximation algorithm based on Markov approximation to seek a near-optimal solution. To make our solution scalable and amenable to future fifth-generation application scenario with large-scale user devices, we further propose a distributed approximation scheme with greatly reduced time complexity, based on the technique of the best response update. Rigorous theoretical analysis and extensive evaluations demonstrate the efficacy of the proposed centralized and distributed schemes.

The Role of Caching in Future Communication Systems and Networks

Abstract: This paper has the following ambitious goal: to convince the reader that content caching is an exciting research topic for the future communication systems and networks. Caching has been studied for more than 40 years, and has recently received increased attention from industry and academia. Novel caching techniques promise to push the network performance to unprecedented limits, but also pose significant technical challenges. This tutorial provides a brief overview of existing caching solutions, discusses seminal papers that open new directions in caching, and presents the contributions of this special issue. We analyze the challenges that caching needs to address today, also considering an industry perspective, and identify bottleneck issues that must be resolved to unleash the full potential of this promising technique.

Artificial Noise Aided Secure Cognitive Beamforming for Cooperative MISO-NOMA Using SWIPT

Abstract: Cognitive radio (CR) and non-orthogonal multiple access (NOMA) have been deemed two promising technologies due to their potential to achieve high spectral efficiency and massive connectivity. This paper studies a multiple-input single-output NOMA CR network relying on simultaneous wireless information and power transfer conceived for supporting a massive population of power limited battery-driven devices. In contrast to most of the existing works, which use an ideally linear energy harvesting model, this study applies a more practical non-linear energy harvesting model. In order to improve the security of the primary network, an artificial-noise-aided cooperative jamming scheme is proposed. The artificial-noise-aided beamforming design problems are investigated subject to the practical secrecy rate and energy harvesting constraints. Specifically, the transmission power minimization problems are formulated under both perfect channel state information (CSI) and the bounded CSI error model. The problems formulated are non-convex, hence they are challenging to solve. A pair of algorithms either using semidefinite relaxation (SDR) or a cost function are proposed for solving these problems. Our simulation results show that the proposed cooperative jamming scheme succeeds in establishing secure communications and NOMA is capable of outperforming the conventional orthogonal multiple access in terms of its power efficiency. Finally, we demonstrate that the cost function algorithm outperforms the SDR-based algorithm.

Efficient and Secure Service-Oriented Authentication Supporting Network Slicing for 5G-Enabled IoT

Abstract: 5G network is considered as a key enabler in meeting continuously increasing demands for the future Internet of Things (IoT) services, including high data rate, numerous devices connection, and low service latency. To satisfy these demands, network slicing and fog computing have been envisioned as the promising solutions in service-oriented 5G architecture. However, security paradigms enabling authentication and confidentiality of 5G communications for IoT services remain elusive, but indispensable. In this paper, we propose an efficient and secure service-oriented authentication framework supporting network slicing and fog computing for 5G-enabled IoT services. Specifically, users can efficiently establish connections with 5G core network and anonymously access IoT services under their delegation through proper network slices of 5G infrastructure selected by fog nodes based on the slice/service types of accessing services. The privacy-preserving slice selection mechanism is introduced to preserve both configured slice types and accessing service types of users. In addition, session keys are negotiated among users, local fogs and IoT servers to guarantee secure access of service data in fog cache and remote servers with low latency. We evaluate the performance of the proposed framework through simulations to demonstrate its efficiency and feasibility under 5G infrastructure.

Capacity Characterization of UAV-Enabled Two-User Broadcast Channel

Abstract: Unmanned aerial vehicles (UAVs) have recently gained growing popularity in wireless communications owing to their many advantages such as swift and cost-effective deployment, line-of-sight (LoS) aerial-to-ground link, and controllable mobility in three-dimensional (3D) space. Although prior works have exploited the UAV’s mobility to enhance the wireless communication performance under different setups, the fundamental capacity limits of UAV-enabled/aided multiuser communication systems have not yet been characterized. To fill this gap, we consider, in this paper, a UAV-enabled two-user broadcast channel (BC), where a UAV flying at a constant altitude is deployed to send independent information to two users at different fixed locations on the ground. We aim to characterize the capacity region of this new type of BC over a given UAV flight duration, by jointly optimizing the UAV’s trajectory and transmit power/rate allocations over time, subject to the UAV’s maximum speed and maximum transmit power constraints. First, to draw essential insights, we consider two special cases with asymptotically large/low UAV flight duration/speed, respectively. For the former case, it is shown that a simple hover-fly-hover (HFH) UAV trajectory with time division multiple access (TDMA)-based orthogonal multiuser transmission is capacity-achieving; while in the latter case, the UAV should hover at a fixed location that is nearer to the user with larger achievable rate and in general superposition coding (SC)-based non-orthogonal transmission with interference cancellation at the receiver of the nearer user is required. Next, we consider the general case with finite UAV speed and flight duration. We show that the optimal UAV trajectory should follow a general HFH structure, i.e., the UAV successively hovers at a pair of optimal initial and final locations above the line segment connecting the two users each with a certain amount of time and flies unidirectionally between them at the maximum speed, and SC is generally needed. Furthermore, when TDMA-based transmission is considered for low-complexity implementation, we show that the optimal UAV trajectory still follows an HFH structure, but the hovering locations can only be those above the two users. Extensive simulation results are provided to verify our analysis, which also reveal useful guidelines to the practical design of UAV trajectory and communication jointly.

Airborne Communication Networks: A Survey

Abstract: Owing to the explosive growth of requirements of rapid emergency communication response and accurate observation services, airborne communication networks (ACNs) have received much attention from both industry and academia. ACNs are subject to heterogeneous networks that are engineered to utilize satellites, high-altitude platforms (HAPs), and low-altitude platforms (LAPs) to build communication access platforms. Compared to terrestrial wireless networks, ACNs are characterized by frequently changed network topologies and more vulnerable communication connections. Furthermore, ACNs have the demand for the seamless integration of heterogeneous networks such that the network quality-of-service (QoS) can be improved. Thus, designing mechanisms and protocols for ACNs poses many challenges. To solve these challenges, extensive research has been conducted. The objective of this special issue is to disseminate the contributions in the field of ACNs. To present this special issue with the necessary background and offer an overall view of this field, three key areas of ACNs are covered. Specifically, this paper covers LAP-based communication networks, HAP-based communication networks, and integrated ACNs. For each area, this paper addresses the particular issues and reviews major mechanisms. This paper also points out future research directions and challenges.

Deployment Algorithms for UAV Airborne Networks Toward On-Demand Coverage

Abstract: Due to the flying nature of unmanned aerial vehicles (UAVs), it is very attractive to deploy UAVs as aerial base stations and construct airborne networks to provide service for on-ground users at temporary events (such as disaster relief, military operation, and so on). In the constructing of UAV airborne networks, a challenging problem is how to deploy multiple UAVs for on-demand coverage while at the same time maintaining the connectivity among UAVs. To solve this problem, we propose two algorithms: a centralized deployment algorithm and a distributed motion control algorithm. The first algorithm requires the positions of user equipments (UEs) on the ground and provides the optimal deployment result (i.e., the minimal number of UAVs and their respective positions) after a global computation. This algorithm is applicable to the scenario that requires a minimum number of UAVs to provide desirable service for already known on-ground UEs. Differently, the second algorithm requires no global information or computation, instead, it enables each UAV to autonomously control its motion, find the UEs and converge to on-demand coverage. This distributed algorithm is applicable to the scenario where using a given number of UAVs to cover UEs without UEs’ specific position information. In both algorithms, the connectivity of the UAV network is maintained. Extensive simulations validate our proposed algorithms.

Flexible and Reliable UAV-Assisted Backhaul Operation in 5G mmWave Cellular Networks

Abstract: To satisfy the stringent capacity and scalability requirements in the fifth generation (5G) mobile networks, both wireless access and backhaul links are envisioned to exploit millimeter wave (mmWave) spectrum. Here, similar to the design of access links, mmWave backhaul connections must also address many challenges such as multipath propagation and dynamic link blockage, which calls for advanced solutions to improve their reliability. To address these challenges, 3GPP New Radio technology is considering a flexible and reconfigurable backhaul architecture, which includes dynamic link rerouting to alternative paths. In this paper, we investigate the use of aerial relay nodes carried by e.g., unmanned aerial vehicles (UAVs) to allow for such dynamic routing, while mitigating the impact of occlusions on the terrestrial links. This novel concept requires an understanding of mmWave backhaul dynamics that accounts for: 1) realistic 3-D multipath mmWave propagation; 2) dynamic blockage of mmWave backhaul links; and 3) heterogeneous mobility of blockers and UAV-based assisting relays. We contribute the required mathematical framework that captures these phenomena to analyze the mmWave backhaul operation in characteristic urban environments. We also utilize this framework for a new assessment of mmWave backhaul performance by studying its spatial and temporal characteristics. We finally quantify the benefits of utilizing UAV assistance for more reliable mmWave backhaul. The numerical results are confirmed with 3GPP-calibrated simulations, while the framework itself can aid in the design of robust UAV-assisted backhaul infrastructures in future 5G mmWave cellular.

Dual-UAV-Enabled Secure Communications: Joint Trajectory Design and User Scheduling

Abstract: In this paper, we investigate a novel unmanned aerial vehicle (UAV)-enabled secure communication system. Two UAVs are applied in this system where one UAV moves around to communicate with multiple users on the ground using orthogonal time-division multiple access while the other UAV in the area jams the eavesdroppers on the ground to protect communications of the desired users. Specifically, we maximize the minimum worst-case secrecy rate among the users within each period by jointly adjusting UAV trajectories and user scheduling under the maximum UAV speed constraints, the UAV return constraints, the UAV collision avoidance constraints, and the discrete binary constraints on user scheduling variables. Since the resulting optimization problem is very difficult to solve due to its highly nonlinear objective function and nonconvex constraints, we first equivalently transform it into a more tractable problem. In particular, the binary constraints are equivalently converted to a number of equality constraints. Then, we develop a novel joint optimization algorithm to handle the converted problem. In order to further improve the secrecy rate performance, we also extend the developed algorithm to the case with multiple jamming UAVs. The simulation results show that the proposed joint optimization algorithm achieves significantly better performance than the conventional algorithms.

Spectrum Sharing Planning for Full-Duplex UAV Relaying Systems With Underlaid D2D Communications

Abstract: In this paper, we consider the spectrum sharing planning problem for a full-duplex unmanned aerial vehicle (UAV) relaying systems with underlaid device-to-device (D2D) communications, where a mobile UAV employed as a full-duplex relay assists the communication link between separated nodes without direct link. Our design aims to maximize the sum throughput under the transmit power budget, while guaranteeing the coexistence with terrestrial D2D pairs, satisfying the information causality and UAV’s trajectory constraints. First, the transmit power planning with a given trajectory is investigated, where a successive convex algorithm is developed by leveraging the D.C. (difference of two convex) programming. Then, we propose a two-step trajectory design method for the given transmit power since the constraints of D2D pairs result in a non-convex feasible set. Furthermore, an efficient spectrum sharing method for an aerial UAV and terrestrial D2D communications is designed by alternately optimizing the transmit power and UAV’s trajectory. Finally, simulation results under various parameter configurations are provided to show the effectiveness of the proposed algorithms.

Cooperative UAV Cluster-Assisted Terrestrial Cellular Networks for Ubiquitous Coverage

Abstract: Unmanned aerial vehicles (UAVs), featured by flexible configuration, robust deployment, and line-of-sight links, has a great potential to provide ubiquitous wireless coverage and high-speed transmission. In this paper, we aim to analyze the coverage performance of UAV-assisted terrestrial cellular networks, where partially energy-harvesting-powered caching UAVs are randomly deployed in the 3-D space with a minimum and maximum altitude, i.e., $H_{l}$ and $H_{h}$ . A novel cooperative UAV clustering scheme is proposed to offload ground mobile terminals (GMTs) from ground cellular base stations to cooperative UAV clusters. A cooperative UAV cluster is developed within a cylinder with projection centered on a GMT, based on their energy states, the cached contents, and the cell loads. With tractable Poisson point process and Gamma approximation, explicit expressions for the successful transmission probabilities are obtained. A theoretical analysis reveals that the cooperative probability of a UAV and the offloading probability of a GMT have bell-shaped relation with respect to the radius of the cylinder and the cache hit probability (the matching probability of a content request and content cache). Numerical results are provided to demonstrate the impacts of the system parameters on the cooperative UAV cluster. The results also give the optimal average altitude ( ${H_{l}+H_{h}}/{2}$ ) and altitude difference ( $H_{h}-H_{l}$ ) in maximizing the coverage performance with the proposed cooperative transmission scheme.

Channel Modeling and Parameter Optimization for Hovering UAV-Based Free-Space Optical Links

Abstract: Recently, the use of multi-rotor (MR) unmanned aerial vehicles (UAVs) has emerged as a promising solution for establishing flexible free-space optical communication links. We address, in this paper, the accurate channel modeling to assess the benefits of MR UAV-based deployment for such links. In particular, in the absence of active tracking subsystems, we derive statistical models for ground-to-UAV, UAV-to-UAV, and UAV-to-ground links over both Gamma–Gamma and log-normal atmospheric turbulence models. Unlike previous works on this topic, our proposed model considers the joint effect of atmospheric turbulence along with position and angle-of-arrival fluctuations. The high accuracy of the proposed analytical models is verified by comparing numerically solved and Monte Carlo simulation results in terms of link outage probability. We further discuss the impact of different transmitter/receiver parameters and their optimization in view of maximizing the link availability.

Secrecy Rate Analysis of UAV-Enabled mmWave Networks Using Matérn Hardcore Point Processes

Abstract: Communications aided by low-altitude unmanned aerial vehicles (UAVs) have emerged as an effective solution to provide large coverage and dynamic capacity for both military and civilian applications, especially in unexpected scenarios. However, because of their broad coverage, UAV communications are prone to passive eavesdropping attacks. This paper analyzes the secrecy performance of UAVs networks at the millimeter wave band and takes into account unique features of air-to-ground channels and practical constraints of UAV deployment. To be specific, it explores the 3-D antenna gain in the air-to-ground links and uses the Matern hardcore point process to guarantee the safety distance between the randomly deployed UAV base stations. In addition, we propose the transmit jamming strategy to improve the secrecy performance in which part of UAVs send jamming signals to confound the eavesdroppers. Simulation results verify our analysis and demonstrate the impact of different system parameters on the achievable secrecy rate. It is also revealed that optimizing the density of jamming UAVs will significantly improve security of UAV-enabled networks.

Beam Tracking for UAV Mounted SatCom on-the-Move With Massive Antenna Array

Abstract: Unmanned aerial vehicle (UAV)-satellite communication has drawn dramatic attention for its potential to build the integrated space-air-ground network and the seamless wide-area coverage. A key challenge to UAV-satellite communication is its unstable beam pointing due to the UAV navigation, which is a typical SatCom on-the-move scenario. In this paper, we propose a blind beam tracking approach for Ka-band UAV-satellite communication system, where UAV is equipped with a hybrid large-scale antenna array. The effects of UAV navigation are firstly released through the mechanical adjustment, which could approximately point the beam towards the target satellite through beam stabilization and dynamic isolation . Specially, the attitude information for mechanical adjustment can be realtimely derived from data fusion of low-cost sensors. Then, the precision of beam pointing is blindly refined through electrically adjusting the weight of the massive antennas, where an array structure based simultaneous perturbation algorithm is designed. Simulation results are provided to demonstrate the superiority of the proposed method over the existing ones.

Overcoming Endurance Issue: UAV-Enabled Communications With Proactive Caching

Abstract: Wireless communication enabled by unmanned aerial vehicles (UAVs) has emerged as an appealing technology for many application scenarios in future wireless systems. However, the limited endurance of UAVs greatly hinders the practical implementation of UAV-enabled communications. To overcome this issue, this paper proposes a novel scheme for UAV-enabled communications by utilizing the promising technique of proactive caching at the users. Specifically, we focus on content-centric communication systems, where a UAV is dispatched to serve a group of ground nodes (GNs) with random and asynchronous requests for files drawn from a given set. With the proposed scheme, at the beginning of each operation period, the UAV pro-actively transmits the files to a subset of selected GNs that cooperatively cache all the files. As a result, when requested, a file can be retrieved by each GN either directly from its local cache or from its nearest neighbor that has cached the file via device-to-device communications. It is revealed that there exists a fundamental trade-off between the file caching cost , which is the total time required for the UAV to transmit the files to their designated caching GNs, and the file retrieval cost , which is the average time required for serving one file request. To characterize this trade-off, we formulate an optimization problem to minimize the weighted sum of the two costs, via jointly designing the file caching policy, the UAV trajectory, and communication scheduling. As the formulated problem is NP-hard in general, we propose efficient algorithms to find high-quality approximate solutions for it. Numerical results are provided to corroborate our study and show the great potential of proactive caching for overcoming the endurance issue in UAV-enabled communications.

JESS: Joint Entropy-Based DDoS Defense Scheme in SDN

Abstract: Software-defined networking (SDN) is a communication paradigm that brings cost efficiency and flexibility through software-defined functions resident on centralized controllers Although SDN applications are introduced in a limited scope with related technologies still under development, operational SDN networks already face major security threats Therefore, comprehensive and efficient solutions are crucial Especially, large-scale security threats such as distributed-denial-of-service (DDoS) attacks are jeopardizing safety and availability of data and services in these systems A DDoS attack is aimed at making resources unavailable to legitimate users via overloading systems with excessive superfluous traffic from distributed sources In this paper, we describe and evaluate a joint entropy-based security scheme (JESS) to enhance the SDN security with the aim of a reinforced SDN architecture against DDoS attacks In particular, our proposed model devises a statistical solution to detect and mitigate these hazards To the best of our knowledge, JESS is the first model that utilizes joint entropy for DDoS detection and mitigation in the SDN environment Since it relies on a statistical model, it mitigates not only known attacks but also unfamiliar types in an efficient manner

Joint Placement of Controllers and Gateways in SDN-Enabled 5G-Satellite Integrated Network

Abstract: Leveraging the concept of software-defined network (SDN), the integration of terrestrial 5G and satellite networks brings us lots of benefits. The placement problem of controllers and satellite gateways is of fundamental importance for design of such SDN-enabled integrated network, especially, for the network reliability and latency, since different placement schemes would produce various network performances. To the best of our knowledge, it is an entirely new problem. Toward this end, in this paper, we first explore the satellite gateway placement problem to obtain the minimum average latency. A simulated annealing based approximate solution (SAA), is developed for this problem, which is able to achieve a near-optimal latency. Based on the analysis of latency, we further investigate a more challenging problem, i.e., the joint placement of controllers and gateways, for the maximum network reliability while satisfying the latency constraint. A simulated annealing and clustering hybrid algorithm (SACA) is proposed to solve this problem. Extensive experiments based on real world online network topologies have been conducted and as validated by our numerical results, enumeration algorithms are able to produce optimal results but having extremely long running time, while SAA and SACA can achieve approximate optimal performances with much lower computational complexity.

Secure and Precise Wireless Transmission for Random-Subcarrier-Selection-Based Directional Modulation Transmit Antenna Array

Abstract: In this paper, a practical wireless transmission scheme is proposed to transmit confidential messages to the desired user securely and precisely by the joint use of multiple techniques, including artificial noise (AN) projection, phase alignment/beamforming, and random subcarrier selection (RSCS) based on orthogonal frequency division multiplexing (OFDM), and directional modulation (DM), namely RSCS-OFDM-DM. This RSCS-OFDM-DM scheme provides an extremely low-complexity structure for the desired receiver and makes the secure and precise wireless transmission realizable in practice. For illegal eavesdroppers, the receive power of confidential messages is so weak that their receivers cannot intercept these confidential messages successfully once it is corrupted by AN. In such a scheme, the design of phase alignment/beamforming vector and AN projection matrix depends intimately on the desired direction angle and distance. It is particularly noted that the use of RSCS leads to a significant outcome that the receive power of confidential messages mainly concentrates on the small neighboring region around the desired receiver and only small fraction of its power leaks out to the remaining large broad regions. This concept is called secure precise transmission. The probability density function of real-time receive signal-to-interference-and-noise ratio (SINR) is derived. Also, the average SINR and its tight upper bound are attained. The approximate closed-form expression for average secrecy rate is derived by analyzing the first-null positions of the SINR and clarifying the wiretap region. Simulation and analysis show that the proposed scheme actually can achieve a secure and precise wireless transmission of confidential messages in line-of-propagation channel, and the derived theoretical formula of average secrecy rate is verified to coincide with the exact results well for medium and large scale transmit antenna array or in the low and medium SNR regions.

Optimization or Alignment: Secure Primary Transmission Assisted by Secondary Networks

Abstract: Security is a challenging issue for cognitive radio (CR) to be used in future 5G mobile systems. Conventionally, interference will degrade the performance of a primary user (PU) when the spectrum is shared with secondary users (SUs). However, when properly designed, SUs can serve as friendly jammers to guarantee the secure transmission of PU. Thus, in this paper, we propose two schemes to improve the sum rate of SUs while guaranteeing the secrecy rate of PU. In the first scheme, the secondary transceivers are jointly designed to maximize their sum rate while satisfying a threshold on the PU’s secrecy rate. Due to the non-convex nature, it is first converted into a convex one and then, an alternating optimization algorithm based on the second-order cone programming is proposed to solve it. In the second scheme, the principle of interference alignment is employed to eliminate interference from PU and other SUs at each secondary receiver, and the interference from SUs is zero-forced at the primary receiver. Thus, interference-free transmission can be performed by the legitimate CR network, with eavesdropping towards PU disrupted by SUs. The key features and performances of the two proposed schemes are also compared. Finally, simulation results are presented to verify the effectiveness of the two proposed schemes for secure CR networks.

Physical-Layer Security in Multiuser Visible Light Communication Networks

Abstract: In this paper, we study the physical-layer security in a 3-D multiuser visible light communication (VLC) network. The locations of access points (APs) and mobile users are modeled as two 2-D, independent and homogeneous Poisson point processes at distinct heights. Using mathematical tools from stochastic geometry, we provide a new analytical framework to characterize the secrecy performance in multiuser VLC networks. Closed-form results for the outage probability and the ergodic secrecy rate are derived for networks without AP cooperation. Considering the cooperation among APs, we give tight lower and upper bounds on the secrecy outage probability and the ergodic secrecy rate. To further enhance the secrecy performance at the legitimate user, a disk-shaped secrecy protected zone is implemented in the vicinity of the transmit AP. Based on the obtained results, it is shown that cooperating neighboring APs in a multiuser VLC network can bring performance gains on the secrecy rate, but only to a limited extent. We also show that building an eavesdropper-free protected zone around the AP significantly improves the secrecy performance of legitimate users, which appears to be a promising solution for the design of multiuser VLC networks with high security requirements.

Joint Beamforming for Secure Communication in Cognitive Satellite Terrestrial Networks

Abstract: This paper investigates the secure communication of a cognitive satellite terrestrial network with software-defined architecture, where a gateway is acting as a control center to offer the resource allocation for the wireless systems. Specifically, we propose beamforming (BF) schemes to utilize the interference from the terrestrial network as a green source to enhance the physical-layer security for the satellite network, provided that the two networks share the portion of millimeter-wave frequencies. Supposing that the satellite employs multibeam antenna while the base station is equipped with a uniform planar array, we first formulate a constrained joint optimization problem to minimize the total transmit power while satisfying both the quality-of-service requirement of the terrestrial user and the secrecy rate (SR) requirements of the satellite users. Since the formulated optimization problem is nonconvex and mathematically intractable, we then propose two BF schemes to obtain the optimal solutions with high computational efficiency. For the case of one eavesdropper (Eve), we present a method to convert the nonconvex SR constraint to a second-order cone one and then adopt a penalty function approach to obtain the BF weight vectors. In the case of multiple Eves, by introducing a list of auxiliary variables, we propose a two-layer iterative BF scheme using penalty function approach together with gradient-based method to calculate the BF weight vectors. Finally, simulation results are given to demonstrate the effectiveness and superiority of the proposed BF schemes.

Resource Allocation and HARQ Optimization for URLLC Traffic in 5G Wireless Networks

Abstract: 5G wireless networks are expected to support ultra-reliable low latency communications (URLLC) traffic which requires very low packet delays (<; 1 ms) and extremely high reliability (~99.999%). In this paper, we focus on the design of a wireless system supporting downlink URLLC traffic. Using a queuing network-based model for the wireless system, we characterize the effect of various design choices on the maximum URLLC load it can support, including: 1) system parameters such as the bandwidth, link SINR, and QoS requirements; 2) resource allocation schemes in orthogonal frequency-division multiple access (OFDMA)-based systems; and 3) hybrid automatic repeat request schemes. Key contributions of this paper which are of practical interest are: 1) study of how the minimum required system bandwidth to support a given URLLC load scales with associated QoS constraints; 2) characterization of optimal OFDMA resource allocation schemes which maximize the admissible URLLC load; and 3) optimization of a repetition code-based packet re-transmission scheme.

Secure NOMA Based Two-Way Relay Networks Using Artificial Noise and Full Duplex

Abstract: In this paper, we develop a non-orthogonal multiple access (NOMA)-based two-way relay network with secrecy considerations, in which two users wish to exchange their NOMA signals via a trusted relay in the presence of single and multiple eavesdroppers. To ensure secure communications, the relay not only forwards confidential information to the legitimate users but also keeps emitting jamming signals all the time to degrade the performance of any potential eavesdropper. Moreover, we equip the relay and each user with the full-duplex technique in the multiple-access phase to combat the eavesdropping and improve the data transmission efficiency, respectively. We propose different decoding schemes based on the successive interference cancellation for the legitimate users, relay, and eavesdroppers. Closed-form expressions for the achievable ergodic secrecy rates of all data symbols under both single- and multiple-eavesdropper cases are derived, validated by the excellent fitting to the computer simulation results for our proposed network.

Secure Communications in NOMA System: Subcarrier Assignment and Power Allocation

Abstract: Secure communication is a promising technology for wireless networks because it ensures secure transmission of information. In this paper, we investigate the joint subcarrier (SC) assignment and power allocation problem for non-orthogonal multiple access amplify-and-forward two-way relay wireless networks, in the presence of eavesdroppers. By exploiting cooperative jamming (CJ) to enhance the security of the communication link, we aim to maximize the achievable secrecy energy efficiency by jointly designing the SC assignment, user pair scheduling and power allocation. Assuming the perfect knowledge of the channel state information at the relay station, we propose a low-complexity subcarrier assignment scheme (SCAS-1), which is equivalent to many-to-many matching games, and then SCAS-2 is formulated as a secrecy energy efficiency maximization problem. The secure power allocation problem is modeled as a convex geometric programming problem, and then, solved by interior point methods. Simulation results demonstrate that the effectiveness of the proposed SSPA algorithms under scenarios of using and not using CJ, respectively.

Hierarchical Edge Caching in Device-to-Device Aided Mobile Networks: Modeling, Optimization, and Design

Abstract: The explosive growth of content requests from mobile users is stretching the capability of current mobile networking technologies to satisfy users’ demands with acceptable quality of service. An effective approach to address this challenge, which has not yet been thoroughly studied, is to offload network traffic by caching popular content at the edges (e.g., mobile devices and base stations) of mobile networks, thus reducing the massive duplication of content downloads. In this paper, we address the system modeling, large-scale optimization, and framework design of hierarchical edge caching in device-to-device aided mobile networks. In particular, taking into account the analysis of social behavior and preference of mobile users, heterogeneous cache sizes, and the derived system topology, we investigate the maximum capacity of the network infrastructure in terms of offloading network traffic, reducing system costs, and supporting content requests from mobile users locally. Our proposed framework has a low complexity and can be applied in practical engineering implementation. Trace-based simulation results demonstrate the effectiveness of the proposed framework.