Characteristic of Line-of-Sight in Infrastructure-to-Vehicle Visible Light Communication Using MIMO Technique

Visible Light Communication(VLC)technology is aggressive research for the next generation of communication.Currently,Radio Frequency(RF)communication has crowed spectrum.An Intelligent Transportation System(ITS)has been improved in the communication network for Vehicle-to-Vehicle(V2 V),Vehicle-to-Infrastructure(V2I),and Infrastructure-to-Vehicle(I2V)by using the visible light spectrum instead of the RF spectrum.This article studies the characterization of Line-of-Sight(LOS)optical performance in an Outdoor Wireless Visible Light Communication(OWVLC)system employing a Multiple-Input Multiple-Output(MIMO)technique for I2V communications in ITS regulations.We design the new configuration of the OWVLC-I2V system,which is an alternative approach to communication for I2V system at nighttime.The results show the Channel Impulse Response(CIR)of the LOS links in visible light communication for I2V system in ITS by investigating the receiver on the vehicle moving along the coverage communication area.Furthermore,the OWVLC-I2V system using the MIMO technique depicts the performance of throughput and Bit Error Rate(BER)vs.vehicle speed while the vehicle passes a street light.

A Compact Ultra-Wideband Circularly Polarized Antenna Array for Vehicular Communications

In this paper,a new compact ultrawideband(UWB)circularly polarized(CP)antenna array for vehicular communications is proposed.The antenna array consists of a 2×2 sequentially rotated T-shaped cross dipole,four parasitic elements,and a feeding network.By loading the T-shaped cross dipoles with parasitic rectangular elements with cut corners,the bandwidth can be expanded.On this basis,the radiation pattern can be improved by the topology with sequential rotation of four T-shaped cross-dipole antennas,and the axial ratio(AR)bandwidth of the antenna also can be further enhanced.In addition,due to the special topology that the vertical arms of all Tshaped cross dipoles are all oriented toward the center of the antenna array,the gain of proposed antenna is improved while the size of the antenna is almost the same as the traditional cross dipole.Simulated and measured results show that the proposed antenna has good CP characteristics,an impedance bandwidth for S11<-10 d B of about 106.1%(3.26:1,1.57-5.12 GHz)and the 3-d B AR bandwidth of about 104.1%(3.17:1,1.57-4.98 GHz),a wide 3-d B gain bandwidth of 73.3%as well as the peak gain of 8.6 d Bic at 3.5 GHz.The overall size of antenna is 0.56λ×0.56λ×0.12λ(λrefers to the wavelength of the lowest operating frequency in free space).The good performance of this compact UWB CP antenna array is promising for applications in vehicular communications.

Using discriminant analysis to detect intrusions in external communication for self-driving vehicles

Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoe networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System （IDS） to protect the external communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service （DOS） and black hole attacks on vehicular ad hoe networks （VANETs）. The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis （LDA） and Quadratic Diseriminant Analysis （QDA） which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.

DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

It is essential to maximize capacity while satisfying the transmission time delay of unmanned aerial vehicle(UAV)swarm communication system.In order to address this challenge,a dynamic decentralized optimization mechanism is presented for the realization of joint spectrum and power(JSAP)resource allocation based on deep Q-learning networks(DQNs).Each UAV to UAV(U2U)link is regarded as an agent that is capable of identifying the optimal spectrum and power to communicate with one another.The convolutional neural network,target network,and experience replay are adopted while training.The findings of the simulation indicate that the proposed method has the potential to improve both communication capacity and probability of successful data transmission when compared with random centralized assignment and multichannel access methods.

Spectrum and energy efficient multi-antenna spectrum sensing for green UAV communication

Unmanned Aerial Vehicle(UAV)communication is a promising technology that provides swift and flexible ondemand wireless connectivity for devices without infrastructure support.With recent developments in UAVs,spectrum and energy efficient green UAV communication has become crucial.To deal with this issue,Spectrum Sharing Policy(SSP)is introduced to support green UAV communication.Spectrum sensing in SSP must be carefully formulated to control interference to the primary users and ground communications.In this paper,we propose spectrum sensing for opportunistic spectrum access in green UAV communication to improve the spectrum utilization efficiency.Different from most existing works,we focus on the problem of spectrum sensing of randomly arriving primary signals in the presence of non-Gaussian noise/interference.We propose a novel and improved p-norm-based spectrum sensing scheme to improve the spectrum utilization efficiency in green UAV communication.Firstly,we construct the p-norm decision statistic based on the assumption that the random arrivals of signals follow a Poisson process.Then,we analyze and derive the approximate analytical expressions of the false-alarm and detection probabilities by utilizing the central limit theorem.Simulation results illustrate the validity and superiority of the proposed scheme when the primary signals are corrupted by additive non-Gaussian noise and arrive randomly during spectrum sensing in the green UAV communication.

The Innovation and Development of Internet of Vehicles

With the advancements in wireless sensor networks, Internet of Vehicles(IOV) has shown great potential in aiding to ease traffic congestion. In IOV, vehicles can easily exchange information with other vehicles and infrastructures, thus, the development of IOV will greatly improve vehicles safety, promote green information consumption and have a profound impact on many industries. The purpose of this paper is to promote the innovation and development of IOV. Firstly, this paper presents general requirements of IOV such as guidelines, basic principles, and the goal of development. Secondly, we analyze critical applications, crucial support, and business model to promote the industrial development of IOV. Finally, this paper proposes some safeguard measures to further promote the development of IOV.

Outage Probability Based on Relay Selection Method for Multi-Hop Device-to-Device Communication

To improve the connectivity of device-to-device(D2D)communication between delay-assisted vehicles,a multi-hop D2D relay selection strategy based on outage probability is proposed.The algorithm firstly clusters the relay users based on the distance of D2D users,and determines the number of one-hop relay nodes through the outage probability threshold.Two-hop relay nodes directly select the same number of relays as one-hop relay nodes according to the descending order of signal noise ratio(SNR)to establish a square matrix.The Hungarian algorithm is used to assign the relay nodes of two clusters to complete the inter relay communication.Finally,the information is sent to the D2D receiver by combining technology.The simulation results show that this algorithm can reduce the cost of relay probing process and the outage probability of system in multi-hop D2D relay communication.

Optimization for UAV-assisted simultaneous transmission and reception communications in the existence of malicious jammers

In this paper,we study an unmanned aerial vehicle(UAV)-assisted communication system,where the UAV is dispatched to implement simultaneous transmission and reception(STR)in the existence of multiple malicious jammers.Two schemes are investigated,namely frequency band-division-duplex(FDD)and time-fraction(TF).Based on the FDD scheme,the UAV can transmit information by using the portion of the bandwidth and receive information within the remaining portion of the bandwidth simultaneously.To perform the STR within the whole bandwidth,the TF-based scheme is considered by using a fraction of a time slot for the downlink,while the remaining fraction of the time slot is allocated for the uplink.We aim to maximize the worst-case throughput by optimizing the UAV three-dimensional(3D)trajectory and resource allocation for each scheme.The optimization problem is non-convex and thus computationally intractable.To handle the nonlinear problem,we use the block coordinate decomposition method to disaggregate the optimization problem into four subproblems and adopt the successive convex approximation technique to tackle non-convex problems.The simulation results demonstrate the performance of the TF-based scheme over the benchmark schemes.

Resource Allocation and Trajectories Design for UAV-Assisted Jamming Cognitive UAV Networks

Unmanned aerial vehicle(UAV)communications are subject to the severe spectrum scarcity problem.Cognitive UAV networks are promising to tackle this issue while the confidential information is susceptible to be eavesdropped.A UAV jamming assisted scheme is proposed.A joint resource allocation and trajectories optimization problem is formulated in a UAV-assisted jamming cognitive UAV network subject to diverse power and trajectory constraints.An alternative optimization algorithm is proposed to solve the challenging non-convex joint optimization problem.Extensive simulation results demonstrate the superiority of our proposed scheme and many meaningful insights are obtained for the practical design of cognitive UAV networks.

UAV target tracking algorithm based on task allocation consensus

In order to adapt to the changes in the states of moving targets and meet the requirements of quality of service in communication among unmanned aerial vehicles (UAVs), the UAVs formation needs to dynamically adjust tracking tasks and tracking paths, when they carry out a mission of tracking multiple moving targets. A multi-targets tracking algorithm based on task allocation consensus is proposed for UAVs to track multiple moving targets under the distributed control architecture in the limited communication range. This algorithm creates a distributed dynamic task allocation model using intermittent asynchronous communication principle to realize the sharing of observation information gathered by each UAV with fewer communications. In addition, this algorithm also makes it possible that multi-UAVs can plan tracking paths for multiple moving targets. We implement the algorithm on the formation with three UAVs to track three moving targets through simulation. Simulation results show the effectiveness of the proposed algorithm. © 2016 Beijing Institute of Aerospace Information.

Range-rate tradeoffs in the communication between LED traffic lights and vehicles

Visible light communication between light emitting diode(LED) traffic lights and vehicles with a receiving photodiode front-end is developed for intelligent transportation systems. In this letter, the communication data rates for different ranges are evaluated. The data rates are based on real scenarios of the background noise and path losses and are experimentally obtained with a testing system built upon commercial offthe-shelf components. Comparisons of range-rate performance for different average noise levels are also conducted with the use of red/yellow/green LED lights. Results show that achieving the data rates of kilobits per second at a communication range of hundred meters is possible under the ordinary noise scenario, a finding that is highly significant for practical applications.

End-to-End Rate Adaptation to Support Heterogeneous Services for Infrastructure-Based Vehicular Networks

Vehicle to Infrastructure （V2I） communications aim to provide mobile users on the road low-cost Internet and driver safety services. However, to meet Quality of Service （QoS） requirements of various applications and officiently utilize limited wireless channel resourc- es, the transport layer protocol has to perform effective rate control in low channel quality and frequent changing topology communica- tion environment. In this paper, we propose a novel rate-control scheme in infrastructure based vehicular networks that avoids conges- tion and starvation and promotes fairness in end-to-end V2I communications. In vehicular networks, a bottleneck roadside unit （RSU） keeps track of its buffer size, aggregate incoming rate, and link throughput, and appropriately allocates bandwidth to traversing flows. With feedback information from the RSU, source nodes dynamically adjust their sending rates to avoid buffer overflow or starvation at the bottleneck RSU. Simulation results show that the proposed scheme can reduce not only packet losses owing to buffer overflow but also buffer starvation time, which improves the utilization efficiency of wireless channel resource.

A modeling and simulation framework for UAVs utilizing 4G-LTE cellular networks

Only a small amount of work has been published on the topic of exploiting existing Long-Term Evolution-Advanced(LTE)cellular communication network infrastructure for Unmanned Aerial Vehicles(UAV)data links.This paper documents a modeling and simulation(m&s)framework that has been developed utilizing the powerful OMNeT++simulation tool for assessing the feasibility and effectiveness of this prospect in various UAV scenarios.Using multiple scenarios,we have studied the data rate requirements for communications between small and medium-sized UAVs and base stations.Using this framework,we have shown that the data rate requirements for the links are within the data throughput achieved by LTE networks.The developed framework implements a propagation model endorsed by the 3GPP LTE project team and also accurately models the high mobility of UAVs.The framework is highly configurable and extensible and boasts of automatic aggregation of results and chart plotting.The outcomes of this research may be utilized by industry for rapidly deploying highly mobile,low-cost UAVs in a wide range of applications and scenarios.