Main Conference
Track 4 – Emerging Technologies, Architectures and Services
Session T4-S1
Streaming and Video
Conference
11:00 AM
—
12:30 PM KST
Local
May 25 Mon, 10:00 PM
—
11:30 PM EDT
Distributed Video Analysis for Mobile Live Broadcasting Services
Yuanqi Chen (Nanjing University Of Science And Technology, China); Yongjie Guan (UNC Charlotte, USA); Tao Han (University of North Carolina at Charlotte, USA)
0
While webcast platforms on mobile devices are becoming more and more prevalent, inspection for irregularities is getting harder and harder. To solve this problem, the convolution neural network(CNN) has been applied to recognize or detect specified objections in pictures and videos. However, when supervising large platforms, it isn't very easy to collect mountain piles of video data and send them to the computation center. Other problems like long time delay and the high computational burden will reduce system performance, especially when dealing with data from live streams. This paper presents a method to coordinate mobile devices with remote servers(computers or embedded systems) to achieve real-time monitoring of live streams. The system can make use of computational capacity on mobile devices and reduce the cost of sending data while guaranteeing accuracy for supervision.
Optimal Buffering for High Quality Video Streaming in D2D Underlay Networks
Suvadip Batabyal (BITS Pilani, Hyderabad Campus, India); Ozgur Ercetin (Sabanci University, Turkey)
0
Device-to-device (D2D) communication helps in enhancing the capacity of the cellular network. However, the provision of video streaming in a D2D underlay network is challenging due to the dynamic and limited availability of resources especially under high mobility. Scalable video coding (SVC) allows for dynamic adjustment of video quality level according to the instantaneous network conditions, e.g., achievable data rate, player buffer occupancy and user preferences. In this paper, we propose an optimal decision theory (ODT) based scheme to fill the buffers with appropriate video quality levels so as to minimize the absolute distortion under constrained stall percent. A setup with one-pair of D2D user and other cellular users (CUs) sharing the same bandwidth with different mobility patterns is used to evaluate the proposed scheme. The scheme is compared with two other schemes viz., the random allocation scheme and the greedy allocation scheme to observe the performance of the ODT based scheme.
Joint Quality Selection and Caching for SVC Video Services in Heterogeneous Networks
Jianwen Meng, Hancheng Lu and Jinxue Liu (University of Science and Technology of China, China)
0
Edge caching has been regarded as an effective way to relieve backhaul pressure as well as reduce service delivery delay. In this paper, we attempt to improve user's quality of experience (QoE) of video services in cache-enabled heterogeneous networks (HetNets). Scalable video coding (SVC) based video services are considered and hence the proper video quality can be selected for each user according to its channel conditions. Intuitively, caching video layers that cannot be delivered to users leads to the waste of limited cache resource. Based on this observation, we formulate the joint video quality selection and caching problem, with the goal to maximize user's QoE. Furthermore, we propose a two-fold dynamic programming algorithm to approach the optimal video quality selection and caching strategies. Finally, the simulation results demonstrate that the proposed strategies can utilize the limited cache space more effectively and achieve more QoE gains compared to existing caching strategies.
Reducing Latency in Interactive Live Video Chat Using Dynamic Reduction Factor
YangXin Zhao, Anfu Zhou (Beijing University of Posts and Telecommunications, China); Xiaojiang Chen (Alibaba Group, China)
0
Live video traffic is taking an increasing share of Internet traffic in recent years. To provide the best user experience, jitter buffers are employed to eliminate the effects of network jitter and to enable smooth video playback. At the same time, an additional delay is added, namely jitterdelay. In this work, we examine how jitter buffer performs in the Web Real-Time Communications (WebRTC), which is the de-facto standard used in mainstream browsers for interactive video chat applications. We collect a dataset from a video live streaming service provider, which adopts WebRTC. After an in-depth analysis of the dataset, we find that jitter buffer can dynamically adjust the jitterdelay but is too conservative, resulting in a very slow decline of jitterdelay. To address the issue, we analyze the control logic of the jitter buffer and find that it uses a fixed reduction factor, known as psi (\psi), which causes the problem. To handle the problem, we propose an enhanced jitter buffer adaptation mechanism called JTB-\psi, which dynamically adjusts \psi according to the size and the duration of the large frame, to reasonably speed up the decline of jitterdelay. Practical testbed experiments show that JTB-\psi achieves a 41.5\% lower jitterdelay and improves receiving frame rate, quantization parameter (QP) and sending bit-rate under different network conditions, compared to the fixed-\psi approach.
QFR: A QoE-driven Fine-grained Routing Scheme for Virtual Reality Video Streaming over SDN
Xiaoyu Liu, Yumei Wang and Yu Liu (Beijing University of Posts and Telecommunications, China)
0
In order to meet the Quality of Experience (QoE) requirements of Virtual Reality (VR) video users under limited resources, efficient and adaptive routing scheme is required. The next generation mobile networks 5G can match network and computing resources according to service requirements, which will be the communication technology for the VR industry. In 5G architecture, the introduction of Software Defined Networking (SDN) decouples the control plane and the forwarding plane, and provides the ability of more granular network resource management. It can actively allocate resources for VR video to optimize transmission performance. In this paper, a QoE-driven Fine-grained routing (QFR) scheme based on SDN has been proposed. The core of QFR is the route calculation algorithm and the route allocation strategy. The route calculation algorithm is a two-stage adaptive routing algorithm. In the first stage, by means of an improved Dijkstra algorithm, the algorithm calculates k paths with the shortest delay. In the second stage, the k paths with the shortest delay are ranked according to the predicted QoE of each path. In addition, tile-based VR video provides a prerequisite for fine-grained routing scheduling. Through differentiated routing of Field of View (FoV) video streaming and Non-FoV video streaming, we develope a fine-grained route allocation strategy. The route allocation strategy determines how to allocate the sorted k paths with the shortest delay according to the residual bandwidth. Comparative evaluation of QFR is conducted to show its preponderance over several existing routing schemes, in terms of download bitrate and QoE of VR video.
Session Chair
Youngbin Im (UNIST, Korea)
Session T4-S2
Security and Privacy
Conference
11:00 AM
—
12:30 PM KST
Local
May 25 Mon, 10:00 PM
—
11:30 PM EDT
Blockchain and Stackelberg Game Model for Roaming Fraud Prevention and Profit Maximization
Cong Thanh Nguyen (Ho Chi Minh City University of Technology, VNU-HCM, Vietnam); Diep N. Nguyen (University of Technology Sydney, Australia); Hoang Thai Dinh (University of Technology Sydney (UTS), Australia); Hoang-Anh Pham (Ho Chi Minh City University of Technology & Vietnam National University Ho Chi Minh City, Vietnam); Nguyen Huynh Tuong (Faculty of Computer Science & Engineering, Ho Chi Minh city University of Technology, Vietnam); Eryk Dutkiewicz (University of Technology Sydney, Australia)
0
Roaming fraud is one of the most significant financial losses for mobile service providers. The inefficiency of current exchanging data management methods among mobile service providers is the main obstacle for roaming fraud prevention. In this paper, we introduce a novel blockchain-based data exchange management system to address roaming fraud problems in mobile networks. This system provides a secure and automatic data exchange service among mobile service providers and mobile subscribers. In addition, we introduce an emerging Proof-of-Stake (PoS) consensus mechanism for the proposed blockchain-based roaming fraud prevention system, which can significantly reduce the delay in exchanging information as well as implementation costs for mobile service providers. To further enhance benefits and security efficiency for the proposed blockchain system, we develop an economic model based on Stackelberg game. This game model is very effective in maximizing profits for both the stakeholders and stake pool and useful in designing a robust blockchain-based mobile roaming management system. Through performance analysis and numerical results, we show that our proposed framework not only provides an effective solution to prevent mobile roaming fraud but also opens many business opportunities for future mobile networks.
A Secure Session Key Negotiation Scheme in WPA2-PSK Networks
Jiang Guo, Miao Wang, Hanwen Zhang and Yujun Zhang (Institute of Computing Technology, Chinese Academy of Sciences, China)
0
This talk does not have an abstract.
Weighted Trustworthiness for ML Based Attacks Classification
Zina Chkirbene (Qatar University & Electrical Engineering, Qatar); Aiman Erbad, Ridha Hamila, Ala Gouissem, Amr Mohamed and Mohsen Guizani (Qatar University, Qatar); Mounir Hamdi (Hamad Bin Khalifa University, Qatar)
0
Recently, machine learning techniques are gaining a lot of interest in security applications as they exhibit fast processing with real-time predictions. One of the significant challenges in the implementation of these techniques is the collection of a large amount of training data for each new potential attack category, which is most of the time, unfeasible. However, learning from datasets that contain a small training data of the minority class usually produces a biased classifiers that have a higher predictive accuracy for majority class(es), but poorer predictive accuracy over the minority class. In this paper, we propose a new designed attacks weighting model to alleviate the problem of imbalanced data and enhance the accuracy of minority classes detection. In the proposed system, we combine a supervised machine learning algorithm with the node1 past information. The machine learning algorithm is used to generate a classifier that differentiates between the investigated attacks. Then, the system stores these decisions in a database and exploits them for the weighted attacks classification model. Thus, for each attack class, the weight that maximizes the detection of the minority classes will be computed and the final combined decision is generated. In this work, we use the UNSW dataset to train the supervised machine learning model. The simulation results show that the proposed model can effectively detect intrusion attacks and provide better accuracy, detection rates and lower false alarm rates compared to state-of-the art techniques.
Wearable Proxy Device-Assisted Authentication Request Filtering for Implantable Medical Devices
Ziting Zhang (Beijing University of Posts and Telecommunications, China); Xiaodong Xu (Beijing University of Posts and Telecommunications & Wireless Technology Innovation Institute, China); Shujun Han and Yacong Liang (Beijing University of Posts and Telecommunications, China); Cong Liu (China Mobile Research Institute, China)
0
As the deepening of 5G's support for the e-health industry, more and more wireless medical devices will suffer from various attacks and threats. Especially, the security of implantable medical devices (IMDs) which have limited computational capabilities and stringent power constraints becomes a critical issue. According to the channel state information, we exploit the special characteristics of the received signal strength (RSS) ratio between wearable proxy devices (WPDs) and IMDs in wireless body area networks (WBANs) to distinguish legitimate users and attackers. Moreover, based on the idea of proposed authentication request filtering (ARF), we design two corresponding light-weight security protocols to defend the forced authentication (FA) attacks and enhance the accessibility of IMD in emergency mode respectively. Simulation results show that the proposed ARF scheme to defend FA attacks achieves a high authentication response rate (ARR) with 99.2% for legitimate users and a low ARR with 2.4% for attackers at the maximum gap threshold point. Furthermore, when applied in emergency mode, the ARF scheme allows up to 96.3% emergency rescue devices to access the IMDs with only one attempt.
A New Privacy-Preserving Framework based on Edge-Fog-Cloud Continuum for Load Forecasting
Shiming Hou and Hongjia Li (Chinese Academy of Sciences, China); Chang Yang (Institute of Information Engineering, Chinese Academy of Sciences, China); Liming Wang (Chinese Academy of Sciences, China)
0
As an essential part to intelligently fine-grained scheduling, planning and maintenance in smart grid and energy internet, short-term load forecasting makes great progress recently owing to the big data collected from smart meters and the leap forward in machine learning technologies. However, the centralized computing topology of classical electric information system, where individual electricity consumption data are frequently transmitted to the cloud center for load forecasting, tends to violate electric consumers' privacy as well as to increase the pressure on network bandwidth. To tackle the tricky issues, we propose a privacy-preserving framework based on the edge-fog- cloud continuum for smart grid. Specifically, 1) we gravitate the training of load forecasting models and forecasting workloads to distributed smart meters so that consumers' raw data are handled locally, and only the forecasting outputs that have been protected are reported to the cloud center via fog nodes; 2) we protect the local forecasting models that imply electricity features from model extraction attacks by model randomization; 3) we exploit a shuffle scheme among smart meters to protect the data ownership privacy, and utilize a re-encryption scheme to guarantee the forecasting data privacy. Finally, through comprehensive simulation and analysis, we validate our proposed privacy-preserving framework in terms of privacy protection, and computation and communication efficiency.
Session Chair
Hyang-Won Lee (Konkuk University, Korea)
Session T4-S3
Localization and Tracking
Conference
2:00 PM
—
3:30 PM KST
Local
May 26 Tue, 1:00 AM
—
2:30 AM EDT
NLOS-Aware VLC-based Indoor Localization: Algorithm Design and Experimental Validation
Chuanxi Huang (Institut Supérieur d'Electronique de Paris (ISEP), France); Xun Zhang (Institut Superieur d Electronique de Paris, France); Fen Zhou (Institut Supérieur d'Electronique de Paris (ISEP) & University of Avignon, France); Zhan Wang and Lina Shi (ISEP, France)
1
The Visible Light Indoor Positioning System (VL-IPS) has been a popular research area recently. In VL-IPS, many localization methods have been proposed by leveraging the Received Signal Strength (RSS) based trilateration. However, the traditional RSS based trilateration localization (RSS-TL) method is very sensitive to the lighting environment and would results in a big localization error due to the presence of non- line-of-sight (NLOS) light signal. In light of this, we propose a novel NLOS-aware localization algorithm, namely Enhanced Fingerprinting-aided RSS-TL (EFP-RSS-TL). It permits to improve the localization accuracy for the corner regions of a room by eliminating the NLOS impact while keeping the same high accuracy for the room center. This is achieved by leveraging a RSS fingerprint database which records the line-of-sight (LOS) light power ratios beforehand. For validation purpose, we built a real VL-IPS platform and implemented the proposed algorithm. Experimental results show that the proposed NLOS-aware EFP- RSS-TL algorithm enables to reduce significantly the average positioning error (by up to 79%) compared to its counterparts. Besides, our proposal cuts the database size by 50% and is more robust to environment changes. In a room of 4.7 m x 2.7 m, the achieved average positioning error is around 6 cm when it is vacant and it is no more than 14.5 cm when it is occupied by several people.
ROLATIN: Robust Localization and Tracking for Indoor Navigation of Drones
Alireza Famili and Jung-Min (Jerry) Park (Virginia Tech, USA)
0
In many drone applications, drones need the ability to fly fully or partially autonomously to carry out their mission. To enable such fully/partially autonomous flights, the ground control station that is supporting the drone's operation needs to constantly localize and track the drone, and send this information to the drone's navigation controller to enable autonomous/semi- autonomous navigation. In outdoor environments, localization and tracking can be readily carried out using GPS and the drone's Inertial Measurement Units (IMUs). However, in indoor areas or GPS-denied environments, such an approach is not feasible. In this paper, we propose a localization and tracking scheme for drones called ROLATIN (Robust Localization and Tracking for Indoor Navigation of drones) that was specifically devised for GPS-denied environments. Instead of GPS signals, ROLATIN relies on speakergenerated ultrasonic acoustic signals to estimate the target drone's location and track its movement. Compared to vision and RF signal-based methods, our scheme offers a number of advantages in terms of performance and cost.
Indoor Localization with Particle Filter in Multiple Motion Patterns
Qiao Li, Xuewen Liao and Zhenzhen Gao (Xi'an Jiaotong University, China)
0
In this paper, a novel mobile tracking method based on pedestrian dead reckoning (PDR) and wireless local area network (WLAN) RSS fingerprint is proposed, which estimates the real-time location of pedestrian continuously using the improved particle filter. The existing PDR systems mostly focus on the condition that sensor axes are relatively fixed to user. However, the sensor axes may be changing during walking period in several motion patterns, for example that the smartphone is swinging with hand or kept in bag. Therefore, we propose a novel PDR algorithm for different handheld patterns, which detects the steps based on multimode finite-state machine (MFSM) with adaptive updating thresholds and estimates the heading direction with principal component analysis (PCA) and ambiguity resolution. On the other hand, for a long continuous walking process, localization error will accumulate and lead to the particle filter losing tracking of the target device. To deal with this problem, we design an improved particle filter with advanced resampling strategy for recovery when localization fails. We conduct experiments for four motion patterns in two realistic representative indoor environments: office building and shopping mall. Experiment results reveal the proposed localization system could achieve an average localization accuracy within 2 m even in the toughest motion pattern.
An Enhanced Direction Calibration Based on Reinforcement Learning for Indoor Localization System
Qiao Li, Xuewen Liao and Zhenzhen Gao (Xi'an Jiaotong University, China)
0
In this paper, we propose an advanced direction calibration method for the smartphone-based indoor localization system on the basis of map information and reinforcement learning (RL). Currently, the direction estimated by pedestrian dead reckoning (PDR) is biased due to the low-precision sensor in smartphone and magnetic field distortion in indoor environment. Thus, the direction calibration methods draw increasing attention. Since the movement of pedestrian is restricted by the indoor environment, the map information could be used to correct the heading of pedestrian and then improve the localization performance. Furthermore, since the tracking of pedestrian can be modeled as a Markov decision process. we propose a novel direction calibration algorithm based on deep Q-network (DQN). Different from the traditional direction calibration algorithms that usually rely on image processing, the proposed method use DQN to find an optimal policy to determine the moving direction. We conduct experiments in a realistic representative office environment to reveal the validity of the proposed direction calibration algorithm. The experiment results indicate that the proposed algorithm can remarkably alleviate the cumulative error, and improve the accuracy, stability and robustness of the indoor positioning system.
TLS-Regularization Framework for Target Tracking under Perturbations
Mostafizur Laskar (Indian Institute of Technology Kharagpur, India); Debarati Sen (Indian Instutute of Technology Kharagpur, India)
0
Perturbation in discrete dynamic systems (e.g., a manoeuvring aircraft, an autonomous vehicle having frequent lane change or turning, etc.) makes the linear tracking filter(e.g., Kalman Filter (KF)) sub-optimal. The existing robust filters such as Ridge-based KF (Ridge-KF), Tikhonov-based KF (TRKF), and minimax algorithm perform enhanced estimation under low and moderate perturbations only. The investigation of severe perturbation for multi-degree of freedom (m-DOF) motion of manoeuvres is carried out in this research article. The severity of perturbation due to m-DOF motion makes the observation matrix ill-posed for the tracking filters. To enhance the estimation performance (in terms of root means square error (RMSE)), we propose a novel algorithm called TLSKF. It offers much-improved performance than KF, Ridge-KF, and TRKF under high perturbation for estimating state parameters (position, velocity, etc.). Further, TLSKF approaches to KF at extremely low perturbation. The improvement in the RMSE enhances the tracking resolution of the radar. The comparison with existing literature is also strived to justify the novelty of the proposed algorithm.
Session Chair
Jin-Ho Chung (Ulsan National Institute of Science and Technology, Korea)
Session T4-S4
URLLC
Conference
4:00 PM
—
5:30 PM KST
Local
May 26 Tue, 3:00 AM
—
4:30 AM EDT
Low-Complexity Centralized Multi-Cell Radio Resource Allocation for 5G URLLC
Ali Karimi (Aalborg University, Denmark); Klaus I. Pedersen (Nokia-Bell Labs, Aalborg University, Denmark); Preben Mogensen (Nokia–Bell Labs, Research Center Aalborg, Sweden)
0
This paper addresses the problem of downlink centralized multi-cell scheduling for ultra-reliable low-latency communications in a fifth generation New Radio (5G NR) system. We propose a low-complexity centralized packet scheduling algorithm to support quality of service requirements of URLLC services. Results from advanced 5G NR system-level simulations are presented to assess the performance of the proposed solution. It is shown that the centralized architecture significantly improves the URLLC latency. The proposed algorithm achieves gains of 99% and 90% URLLC latency reduction in comparison to distributed scheduling and spectral efficient dynamic point selection.
A Fully Coordinated New Radio-Unlicensed System for Ultra-Reliable Low-Latency Applications
Roberto Maldonado Cuevas (Aalborg University, Denmark); Claudio Rosa (Nokia, Denmark); Klaus Pedersen (Nokia - Bell Labs, Denmark)
0
Communications over the unlicensed spectrum are susceptible to be delayed by mandatory channel access mechanisms. Based on the need for improving the latency-reliability performance of New Radio-Unlicensed for supporting new use-cases, such as industrial applications, different types of channel access are evaluated in this paper. By using asynchronous and demand-driven channel access, it is shown that approximately 50% of the delay experienced by a downlink packet is due to listen before talk (LBT). Furthermore, UEs might be blocked by an unsuccessful uplink LBT losing the opportunity to transmit their previously scheduled data. As an alternative, synchronous channel access is evaluated. By using a coordinated LBT among the nodes, the channel access delay is reduced to a constant value. However, UEs can still be blocked when initiating their uplink transmissions due to neighbours transmissions. Motivated by this fact, an approach in which a central node is in charge of the frame selection is proposed. Therefore, all the nodes in the system are coordinated in both the channel access and the frame configuration. In this case, a latency reduction of 70% as compared to the previously mentioned alternatives is achieved at high loads and 99.9999% reliability.
Analysis of High-Reliable and Low-Latency Communication Enablers for New Radio Unlicensed
Roberto Maldonado Cuevas (Aalborg University, Denmark); Claudio Rosa (Nokia, Denmark); Klaus Pedersen (Nokia - Bell Labs, Denmark)
0
In this paper, the performance impact of several high-reliable and low-latency communications technology enablers in the unlicensed spectrum for standalone operation is evaluated. Firstly, a comparison between MulteFire (MF) and New Radio-Unlicensed (NR-U) is established. It is shown that higher sub-carrier spacings and shorter processing times provide clear latency reduction benefits. Additionally, different transmission time intervals (TTI) durations are evaluated. Shortening the TTI duration decreases the latency by a factor of 5.75 at 99.99% reliability and reduces the uplink Listen Before Talk (LBT) blocking probability by 18%. The possibility of having multiple switching points during the frame is also evaluated. It is concluded that having multiple switching points provides a latency reduction mainly due to the reduction of the number of channel accesses and the reduced gaps within the frame. A time-diversity technique to cope with high uplink LBT blocking probability is also evaluated. By combining the aforementioned features, a latency reduction factor of 31 is achieved when optimized NR-U and MulteFire performances are compared.
Robust URLLC Packet Scheduling of OFDM Systems
Jing Cheng and Chao Shen (Beijing Jiaotong University, China); Shuqiang Xia (ZTE Corporation, China)
0
In this paper, we consider the power minimization problem of joint physical resource block (PRB) assignment and transmit power allocation under specified delay and reliability requirements for ultra-reliable and low-latency communication (URLLC) in downlink cellular orthogonal frequency-division multiple-access (OFDMA) system. To be more practical, only the imperfect channel state information (CSI) is assumed to be available at the base station (BS). The formulated problem is a combinatorial and mixed-integer nonconvex problem and is difficult to tackle. Through techniques of slack variables introduction, the first-order Taylor approximation and reweighted-norm, we approximate it by a convex problem and the successive convex approximation (SCA) based iterative algorithm is proposed to yield sub-optimal solutions. Numerical results provide some insights into the impact of channel estimation error, user number, the allowable maximum delay and packet error probability on the required system sum power.
Efficient and Reliable Wireless Communications Through Multi-Connectivity and Rateless Coding
Philipp Schulz (Technische Universität Dresden, Germany); Andre N Barreto (Barkhausen Institut gGmbH, Germany & Universidade de Brasilia, Brazil); Gerhard Fettweis (Barkhausen Institut, Germany)
2
Achieving extremely high reliability is one of the key targets in the development of fifth generation mobile networks. To meet this ambitious aim, usually redundancy is introduced by simultaneously utilizing multiple links that are separated in frequency and/or space. However, current standards simply duplicate packets on these links, resulting in an inefficient high usage of resources that could have been used for other applications. To address this problem, rateless coding using multiple links is proposed for ultra-reliable communications, mathematically modeled, and evaluated in this paper. The benefits comprise efficient resource usage and a simplified feedback mechanism. Finally, they can be implemented in a technology- agnostic manner on application layer to easily exploit interface diversity.
Transceiver Design for Full-Duplex Ultra-Reliable Low-Latency Communications with Finite Blocklength
Keshav Singh (University College Dublin (UCD), Dublin, Ireland); Sudip Biswas (Indian Institute of Information Technology, Guwahati, India); Meng-Lin Ku (National Central University, Taiwan); Mark Flanagan (University College Dublin, Ireland)
0
In this paper, we jointly optimize the transceiver design and decoding error probability of a full-duplex (FD) ultra- reliable low-latency communication (URLLC) system, where the base-station (BS) operates in an FD mode while the uplink (UL) and downlink (DL) users work in a half-duplex (HD) mode. Accordingly, an optimization problem is formulated for an FD URLLC system under the finite blocklength (FBL) to maximize the achievable total (UL plus DL) rate subject to the reliability (i.e., the decoding error probability) of each link and total transmission power constraints at the UL user and the BS. We convexify the formulated non-convex problem by analyzing the problem structure. Next, an efficient iterative algorithm is proposed to find the near-optimal power allocation for the UL user and the transceiver weights for the BS. Simulation examples show the impact of the blocklength and decoding error probability on the system performance.
Session Chair
Hu Jin (Hanyang University, Korea)
Session T4-S5
Vehicular Networks
Conference
4:00 PM
—
5:30 PM KST
Local
May 26 Tue, 3:00 AM
—
4:30 AM EDT
Energy-Efficient Power Control and Resource Allocation for V2V Communication
Lei Gao (Beijing University Of Posts And Telecommunications, China); Yanzhao Hou, Xiaofeng Tao and Min Zhu (Beijing University of Posts and Telecommunications, China)
0
In recent years, vehicle-to-vehicle (V2V) communication underlaying cellular networks has attracted more and more attention both in academy and industry. In this paper, guaranteeing the latency and reliability of vehicle users (VUEs), we study the resource management problem to maximize the energy efficiency of VUEs while considering the QoS requirement of cellular users (CUEs). Based on the Lyapunov optimization theory, a novel two-layer power control and resource allocation scheme is proposed by exploiting the properties of fractional programming. Simulation results show that the proposed scheme can achieves remarkable improvements in terms of EE and ensure the latency and reliability requirements of V2V communication.
Maximization of Con-current Links in V2V Communications Based on Belief Propagation
Xunchao Wu, Yanzhao Hou and Xiaofeng Tao (Beijing University of Posts and Telecommunications, China); Xiaosheng Tang (BeiJing University of Posts & Telecommunications, China)
0
In this paper, spectrum resource allocation in vehicle-to-vehicle (V2V) communications network is studied. Multiple V2V links can share one resource block (RB) for maximizing con-current links with the satisfaction of quality of service (QoS). The resource allocation problem is transformed into an inferential problem on a factor graph model. To solve this problem, the Belief Propagation based on Real-time Update of Messages (BPRUM) algorithm is proposed. In this method, the information matrix is updated after each message passing procedure is completed rather than after once iteration. From the simulation results, the proposed method achieves a significant increment in spectrum utilization compared to the existing algorithms.
Vehicle platooning schemes considering V2V communications: A joint communication/control approach
Tiago Rocha Goncalves (CentraleSupelec, France); Vineeth S Varma (CRAN & CNRS, France); Salah Eddine Elayoubi (CentraleSupélec, France)
0
This article addresses communication and control aspects of platooning systems with the related challenges introduced by the overlap of both areas. The main objective is to provide a dynamic control mechanism where the parameters of the well-known Predicted Cooperative Adaptive Cruise Control (PCACC) are adapted based on the observed quality of the V2V (Vehicle-to-Vehicle) communication links. Different from the state of the art, our main design goal is the minimization of inter-vehicular distances while being robust in terms of an extremely low probability of emergency braking. A new adaptive control scheme based on the offline optimization of the control gains is proposed. We evaluate the new approach in a highway scenario and show the improvements obtained by the dynamic adaptation of the control parameters over static control strategies.
Analytical Performance Evaluation of the Collective Perception Service in IEEE 802.11p Networks
Florian Alexander Schiegg (Leibniz University of Hanover & Robert Bosch GmbH, Germany); Daniel Bischoff (Technical University Darmstadt & Opel Automobile GmbH, Germany); Johannes Ruben Krost (Robert Bosch Car Multimedia GmbH, Germany); Ignacio Llatser (Robert Bosch GmbH, Germany)
1
A vast number of advanced driver assistance systems are currently being developed, from platoon controllers to intersection assistants. All these systems depend on the vehicle's capability to accurately sense its environment. In order to overcome line of sight and other constraints of standard on-board vehicle sensors, Vehicle-to-Everything (V2X) communication has been introduced. Through concepts like collaborative positioning, cooperative awareness and collective perception, traffic participants are enabled to share data gathered by their sensors, permitting to significantly enhance their environmental perception. This paper is aimed at supporting the current standardization efforts at the European Telecommunications Standards Institute (ETSI) with respect to the latter. It analyzes the performance of the collective perception service in IEEE 802.11p networks in terms of its impact on the traffic participant's gained environmental perception and draws conclusions for the further development of the service.
Path Optimization for Flying Base Stations in Multi-Cell Networks
Jongyul Lee and Vasilis Friderikos (King's College London, United Kingdom (Great Britain))
0
A crucial aspect when deploying Unmanned Aerial Vehicles (UAVs) to operate as flying base stations (FBSs) assisting 5G networks is path (trajectory) optimization. Even though this topic has received significant research attention for multiple UAVs located at the same base station (BS), the area of path optimization in the case of multiple UAVs located in different BSs serving user equipment (UE) or cluster points (CPs) in a multi cell environment received less attention. This paper addresses a mixed integer linear programming (MILP) formulation for FBS path optimization in terms of travel time considering a multi-cell environment which the BSs can act as the depots for multiple UAVs. Numerical investigations reveal that the proposed UAV path optimization approach can decrease the overall travel time for the deployment of the FBSs compared to other solutions that do explicitly optimize the case of multiple BSs and the UEs and/or CPs that belong within the coverage area of different BSs.
Session Chair
Yeongjin Kim (Inha University, Korea)