IEEE/CIC International Conference on Communications in China
Mobile and Wireless Networks
Session MWN-04
UAV
Conference
10:30 AM
—
12:00 PM CST
Local
Aug 10 Mon, 10:30 PM
—
12:00 AM EDT
Invited Talk: Coordinated Transmission on the Ocean for Cell-Free Satellite-UAV-Terrestrial Networks
Wei Feng (Tsinghua University, China)
3
Current maritime coverage mainly relies on onshore base stations (BSs) and marine satellites. The former could only cover limited offshore areas and the later usually lack of broadband communications capability. In this paper, we investigate a new usage of unmanned aerial vehicles (UAVs) under the hybrid satellite-UAV-terrestrial network architecture for better coverage on the ocean. Particularly, we adopt tethered UAVs coordinating with terrestrial BSs along the coastline, so as to liberate UAVs from harsh environments above the ocean and also provide additional aerial BS sites for facilitating the onshore-BS-sites scarcity problem. All spectrum is shared among satellites, UAVs and terrestrial BSs for elastic resource allocation and agile coverage. This hybrid network is irregular due to geographical limitations of terrestrial BSs and the deployment restriction of UAVs, thus leading to more challenging co-channel interference (CCI) for spectrum sharing than conventional cellular networks. We formulate a cell-free coordinated transmission regime, where multiple terrestrial BSs and UAVs form a virtual cluster to jointly serve a ship in a user-centric manner. Inter-cluster interference and leakage interference to satellite users are further mitigated by joint power allocation. The presented method requires only large-scale channel state information (CSI) and practically affordable computing cost, while offering a significant performance improvement in terms of system sum rate.
A Mobility Aware Clustering Scheme Based on Swarm Intelligence in FANETs
Wang Min (Shanghai Jiao Tong University, China)
0
The emerging Flying ad-hoc Network (FANET) has been used in many applications and services ranging from military to emergency rescue. UAV clustering is a significant technology in FANETs. In each cluster, the cluster head (CH) is responsible for the entire cluster management. However, due to the frequent movement and limited energy of UAVs, one of the foremost challenges in FANETs is unstable cluster. Hence, to cope with this issue, we proposed a mobility aware clustering scheme based on swarm intelligence (MACSI) for FANETs, which is enlightened by the animal collective behavior. More specifically, the modified glowworm swarm optimization (GSO) algorithm based on chaos strategy is put forward for CH selection and cluster formation. It aims to help UAVs follow the CH to perform missions by improving global search capability. In addition, a stable CH selection mechanism is adopted, which depends on the residual energy, current position and the movement coordination relationship among neighbors. Our proposal has been evaluated with respect to metrics as energy consumption and cluster life time. The experimental results obtained validate that, the proposed scheme has less energy consumption and extended cluster life time compared with existing clustering schemes.
Joint Access and Backhaul Link Optimization in Multiple UAV-Assisted Emergency Network
Xiaoxu Yuan (Beijing University of Posts and Telecommunications, China); Hui Tian (Beijng university of posts and telecommunications, China); Gaofeng Nie (Beijing University of Posts and Telecommunications, China)
0
With the development of unmanned aerial vehicles (UAVs) in both hardware technology and theoretical approaches, UAVs begin to emerge as important potential equipment for future communication networks, where UAV-assisted emergency communication attracts the most attention due to the flexibility and mobility of UAVs. In this paper, we consider a remote emergency scenario with the ground base stations (BSs) being destroyed and study the access and backhaul link optimization problem. We propose a joint user association, UAV positioning, and resource allocation (UPR) algorithm to maximize the system throughput. We deploy UAVs not only as BSs to provide access links but also as relays to provide backhaul links, where the transmission rate of the system depends on the minimum of all the transmission links. We theoretically analyze the maximization problem of the system throughput and derive the optimal resource allocation for all the transmission links. We also prove the optimality of the equidistant alignment of UAV relays and their linear alignment with the emergency vehicle and solve the resulting optimization problem by alternating between the positioning of UAVs and user association. Simulation results verify the effectiveness of the proposed UPR algorithm.
Flying LTE for UAV Dynamic Access Control
Xiafei Bu and Chungang Yang (Xidian University, China)
0
Unmanned areial vehicles (UAVs) are widely applied to the military and civil domains. These applications are largely depend on UAV communications. UAVs can act as aerial base stations (BSs), aerial relays (ARs) and aerial user equipments (UEs) in networks. However, both high-speed movement of UAVs and dynamic topology make existing medium access control (MAC) protocols not suitable, such as IEEE 802.11. The existing UAV MAC protocols are mostly based on the time division multiple access (TDMA), which studied the improvement of network throughput and delay. These works rarely considered the problem that UAVs are powered by batteries and have limited energy. Thus the orthogonal frequency-division multiplex access (OFDMA) technology is utilized by UAVs to improve the network energy efficiency (EE). This paper first introduces three communication scenarios of UAVs. Then, paper describes several existing UAV MAC protocols and challenges. Next, we propose that UAV BSs access to long term evolution (LTE) networks by OFDMA technology for limited energy of UAVs. Finally, two types of subcarrier quantity allocation are simulated, which one is equal number and the other is based on signal to interference-plus-noise ratio (SINR) between users. The results show that the subcarrier allocation based on the SINR ratio between users has higher throughput. Besides, this allocation is more suitable for dense scenes and has higher EE.
Sum Rate Maximization for UAV-Enabled Wireless Powered NOMA Systems
Jin Du, Zhengqiang Wang, Zifu Fan and Xiaoyu Wan (Chongqing University of Posts and Telecommunications, China)
0
In this paper, we consider the sum rate maximization problem of uplink non-orthogonal multiple access (NOMA) system with wireless power transfer (WPT). The sum rate problem in non-convex problem, which is difficult to handle directly because the energy harvesting time and position of UAV are coupled in the objective function. We propose an iterative algorithm to find the energy harvesting time and the position of UAV. The energy harvesting time problem is solved by the bisection search. Then, the position optimization problem for UAV is solved by quadratic transform method. Finally, based on the above two methods, we propose a two-tier iterative algorithm to jointly optimizing the energy harvesting time and position of UAV. Simulation results show that the proposed algorithm has a better performance compared with the benchmark algorithms.
Session Chair
Chungang Yang, Gaofeng Nie
Session MWN-07
Code Design and Beamforming
Conference
10:30 AM
—
12:00 PM CST
Local
Aug 10 Mon, 10:30 PM
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12:00 AM EDT
Beam Management for Cellular-Connected UAVs: A Fast Link Recovery Approach
Jinli Wu (Xidian University, China); Xinhong Mao (Institute of Telecommunication Satellite, China); Ronghui Hou, Xixiang Lv and Hui Li (Xidian University, China)
0
Due to the short wavelength of millimeter wave (mmWave) and high directional beamforming, the massive MIMO systems are highly vulnerable to link blockage. Beam switching to unblocked direction is an effective solution to overcome blockage and restore communication links. To this end, a set of candidate beams for beam switching should be selected before the beam is blocked. However, due to the high speed movement of the UAV, identifying the appropriate beam for an UAV with any position is not trivial. In this work, a fast link recovery approach is proposed. Specifically, our proposed beam selection method considers the spatial correlation, estimated reliability probability of the beams and signal quality. The simulation results show that the proposed method can efficiently recover the interrupted link, and the outage probability is almost reduced to 0% in the scene where the UAV moves at high speed.
Improved method of deblocking filter based on convolutional neural network in VVC
Jing Yang (CQUPT, China); Biao Du and Tong Tang (Chongqing University of Posts and Telecommunications, China)
0
With the rapid development of 5G and the Internet of Things, video has gained broad application space as a carrier of information, and video codec technology can reduce video storage space, save transmission bandwidth, and provide the possibility for the promotion of video applications. Multi-functional video coding (VVC), the latest generation of video coding standard today, still uses block-based coding, which inevitably introduces coding artifacts, and deblocking filters can effectively reduce artifacts and improve the quality of compressed video. The deblocking filter in VVC still adopts the method based on empirical threshold when making the filtering decision, but the actual video scene changes variously, and it is obviously impossible to obtain the optimal filtering effect with a fixed threshold. The decision of the filtering mode is essentially a classification problem. Existing research shows that the convolutional neural network(CNN) has a strong ability in classification tasks, and its feature extraction and nonlinear fitting ability can greatly improve the learning ability of the target, so as to obtain better classification accuracy. Therefore, we improves the deblocking filter in VVC based on CNN. Experimental results show that, compared with the original filtering method of VVC, our method can better improve the quality of compressed video.
Receiver Assisted LBT Mechanism Design for Beam-based Transmission in Unlicensed Bands
Wenxin Wang, Ming Zeng and Fei Zesong (Beijing Institute of Technology, China)
0
In the unlicensed spectrum of 5GHz, Listen-Before-Talk (LBT) technology is used to ensure the fair and friendly coexistence of NR-U (New Radio Unlicensed) and WiFi. However, when signals are transmitted in the mmWave band, the propagation distance is short. Thus, the beamforming technology is used to form a directional narrow beam with high antenna gain, which changes the interference layout, resulting in the limited range of LBT. In this case, to better evaluate the potential interference, the receiver utilizes the useful information received through beam transmission to better manage the interference in the unlicensed mmWave spectrum, which is called receiver-assisted LBT. The performance of the system based on receiver-assisted LBT will be significantly affected by the Energy Detection (ED) threshold of the receiver. Therefore, this paper aims to find the optimal ED threshold of the receiver. We propose the inner approximation algorithm, which can improve the spectral efficiency and the system throughput when multi Radio Access Technologies (RATs) work in the unlicensed mmWave spectrum. The simulation results show the effectiveness of the method.
An Almost Blank Subframe Allocation Algorithm for 5G New Radio in Unlicensed Bands
Qingqing Tang, Ming Zeng, Jing Guo and Fei Zesong (Beijing Institute of Technology, China)
0
The 5G new radio communications in unlicensed bands (5G NR-U) can meet the growing data traffic requirements and make better use of the unlicensed bands. However, the harmonic coexistence of NR-U and WiFi in unlicensed bands is a challenging problem as NR-U and WiFi employ different access technologies. To address this problem, this paper proposes an almost blank subframe (ABS) optimization mechanism by jointly considering the data transmission of WiFi users and the positions of ABS, which can achieve fair coexistence of NR-U and WiFi and effectively improve the system throughput. Specifically, we first investigate the optimal number of ABS according the data transmission of WiFi users. Then, we use the Q-learning algorithm to learn the data transmission rules of WiFi users to solve the problem of matching data transmission positions of WiFi users with ABS positions. Simulation results show that the algorithm can effectively improve the total throughput compared with the traditional ABS allocation algorithm.
Research and Evaluation on Beam Scheduling Algorithm based on Hybrid Beamforming in Millimeter Wave
Hui Liu (China Academy of Information and Communications Technology, China); Jiamo Jiang (China Academy of Information and Communications Technology (CAICT), China); Xia Shen (China Academy of Information and Communication Technology, China); Jiahui Li (Beijing University of Posts and Telecommunications, China)
0
Ministry of Industry and Information Technology of China has issued commercial license for 5G medium and low frequency bands last year, and 5G is in a critical period of commercial deployment. According to national frequency plan, research and development of millimeter wave equipment and technology will be carried out in the next step to prepare for the commercial use of 5G millimeter wave technology. Three schemes to schedule analog beam based on hybrid beamforming in millimeter wave are presented in this article, along with performance evaluation in system-level simulation.
Session Chair
Ronghui Hou, Jing Guo
Session MWN-05
Performance Analysis and Optimization
Conference
1:30 PM
—
3:00 PM CST
Local
Aug 11 Tue, 1:30 AM
—
3:00 AM EDT
Performance Analysis of the Coexistence of 5G NR-Unlicensed and Wi-Fi with Mode Selection
Yifan Jiang, Jing Guo and Zesong Fei (Beijing Institute of Technology, China)
0
By allowing to utilize the unlicensed spectrum band, the New Radio Unlicensed (NR-U) is a key technology of the fifth-generation (5G) wireless system to relief the spectrum shortage issue of licensed band. In this paper, we investigate the WiFi and 5G NR coexisted network, where the NR base stations implement the mode selection procedure to use the licensed spectrum band or the unlicensed spectrum band. Leveraging the stochastic geometry, we present a tractable mathematical framework to characterize the medium access probability, the conditional coverage probability for different types of access points and the overall coverage probability. The accuracy of the analytical evaluations is validated by simulation. Our results show that the incorporation of NR-U can improve the overall network performance by comparing with the performance of the stand-alone cellular network. In addition, there is an optimal mode selection probability (i.e., the probability of switching to use the unlicensed band) which maximizes the overall coverage probability.
Adaptive Fast Simplified Successive Cancellation List Polar Decoding based on Path Selecting
Ling Wang (Chongqing University of Posts and Telecommunications, China)
0
5G is designed for high reliability and low latency massive data interaction scenarios. Compared with 4G mobile communication, it puts forward higher requirements for channel decoding. To improve the error correction performance and reduce delay, some improved simplified successive-cancellation list (SSCL) have been proposed in the past. The fast SSCL exploits some special constituent nodes and gives the bound of path splitting to reduce the required number of time-steps. In this paper, an adaptive path selecting strategy based on path metric (PM) is proposed, which induces the sorting complexity and tightens the exact bound of path splitting of the fast SSCL. Simulation results show that, the proposed scheme has lower complexity and higher efficiency than SCL without any performance loss. Also, compare to the empirical Fast-SCL, it shows better error correction performance. Moreover, the proposed scheme outperforms existing adaptive decoding algorithms, avoiding any priori information as a threshold stored in memory.
Statistical QoS Provisioning Resource Allocation Over SWIPT Based Relay Networks
Ya Gao (Luoyang Normal University, China); Yongpeng Shi and Yujie Xia (Luoyang Normal College, China); Hailin Zhang (Xidian University, China)
0
Energy scarcity becomes a key factor restricting the development of the wireless communications network. Wireless power transfer, as it can provide a sustainable and reliable energy supply for wireless communications devices, has drawn a lot of interests in recent a few years. Thus, combining wireless power transfer to the wireless communications network can potentially extend the lifetime of wireless devices and thus prolong the operating-time of networks. In this paper, we consider the two-hop wireless networks, where the source node transmits information to the destination assisted by the relay node and the relay simultaneously harvests energy and receive information from the source node. In order to maximize the effective capacity (EC), which is the maximum constant arrival rate under specified quality of service (QoS) requirements, we investigate the statistical QoS supported resource allocation policies under full duplex transmission mode for wireless powered relay networks. Finally, numerical results are demonstrated to validate the theoretical derivations, which highlights the proposed scheme in terms of EC performance in comparison to the benchmark scheme.
A Deep Reinforcement Learning-Based Caching Strategy for Internet of Things
Ali Nasehzadeh and Ping Wang (York University, Canada)
1
With the continuous growth of the Internet of Things (IoT), the specific needs of these networks are becoming clearer. Transient data generated and limited energy resources are two of the characteristics of IoT networks that impose some limitations. Moreover, the conventional quality of service requirements such as minimum delay, are still needed in these networks. By implementing an efficient caching policy, it is possible to meet the conventional demands while easing the specific limitations of IoT networks. By leveraging deep reinforcement learning technique, without the need of prior knowledge of the contents popularity, contents life-times or any other type of contextual information, we have managed to develop a caching policy which increases the cache hit rate and decreases the energy consumption of IoT devices while simultaneously considering the limited life time of the data contents. The simulation results show that our proposed method outperforms the conventional Least Recently Used (LRU) method by considerable margins in all aspects.
Maximizing Lifetime of Delay-Tolerant Sensor Networks With a Mobile Sink
Haoliang Li, Peiliang Zuo, Hanbo Jing and Wenbo Wang (Beijing University of Posts and Telecommunications, China)
0
In this paper we investigate the network lifetime maximization problem of the delay-tolerant sensor network where a mobile sink is dispatched to collect aggregated data from the sensors with different available energy levels and diverse storage sizes. The data gathering process is also subject to the bounded delay determined by the traffic and storage size of each sensor. To settle the NP-hard problem, we obtain the data distribution constraint for sensor nodes in degree-constrained data-gathering trees. Based on which the traffic of a node could be approximately estimated by the generated data of its descendant nodes that are within a certain number of hops. We then propose a distributed heuristic method which is composed of three procedures, i.e. selecting residence locations for the mobile sink, constructing a load-balanced data-gathering forest and pruning branches to meet delay requirements. We finally conduct extensive simulations to verify the performance of the proposed method against other heuristics, the simulation results show that the proposed method significantly outperforms them in terms of the network lifetime.
Session Chair
Ya Gao, Ping Wang
Session MWN-08
Resource Allocation and Optimization
Conference
1:30 PM
—
3:00 PM CST
Local
Aug 11 Tue, 1:30 AM
—
3:00 AM EDT
A Cooperative Coded Caching Strategy for D2D-Enabled Cellular Networks
Yunpeng Ma (Northeastern University, China); Weijing Qi (Chongqing University of Posts and Telecommunications, China); Peng Lin and Mengru Wu (Northeastern University, China); Lei Guo (Chongqing University of Posts and Telecommunications, China)
0
With the explosive increase of data traffic in wireless networks, caching video contents by device-to-device (D2D) communication has emerged as an effective solution for alleviating the burden of backhaul links. How to improve cooperative caching between mobile users in D2D-enabled cellular networks is crucial. In this paper, we propose a cooperative coded caching (CCC) strategy for D2D-enabled cellular networks to minimize the delivery delay. In our method, users are divided into different social clusters through an interest-dependent Chinese restaurant process (ICRP) since users request different content based on their interests. Moreover, we exploit the maximum distance separable (MDS) code to encode the contents into distinct segments. We propose a caching algorithm based on a greedy approach to obtain the optimal content placement. Numerical results demonstrate the effectiveness of our proposed caching strategy in terms of average delivery delay.
User Preference and Activity Aware Content Sharing in Wireless D2D Caching Networks
Yulong Qi, Jingjing Luo and Lin Gao (Harbin Institute of Technology, Shenzhen, China); Fu-Chun Zheng (Harbin Institute of Technology, Shenzhen, China & University of York, United Kingdom (Great Britain)); Li Yu (Huazhong University of Science & Technology, China)
0
Device-to-Device (D2D) content sharing has emerged as an important tool to alleviate the backhaul pressure. Most of prior works optimize D2D caching policies with known content popularity, which may not be the case in reality. In this paper, we investigate a D2D caching optimization problem with unknown content popularity in wireless D2D caching networks. To maximize the overall D2D caching hit rate, we propose a distributed caching policy by learning user preferences and user activity levels. For the first time, we exploit the sliding time window method to predict real-time user activity levels. And we employ a logistic regression model to describe the user preference. By predicting user activity levels and user preferences in real time, the proposed policy not only can significantly improve the overall D2D caching hit rate, but also reduce the traffic load of the base station compared to existing policies. Simulation results with MovieLens dataset further show that the overall D2D caching hit rate of our proposed policy is close to that of the optimal caching policy.
IoT Gateway Association and Data Scheduling for Delay Optimization in LEO Satellite Systems
Chong Liu and Rong Chai (Chongqing University of Posts and Telecommunications, China); Qianbin Chen (Chongqing University of Posts and Telecommunication, China)
0
As a critical supplementary to terrestrial communication systems, low-earth-orbit (LEO) satellite communication systems have been gaining growing attention in recent years. In this paper, we consider an LEO system where a number of Internet of things (IoT) gateways need to send their collected data to LEO satellites. The highly dynamic topology of satellite systems and the limited connection status between satellites and gateways pose challenges to the problem of gateway association and data scheduling. To address this problem, we define system transmission delay as the number of time slots needed for all gateways to upload their collected data, and formulate the joint gateway association and data scheduling problem as a system transmission delay minimization problem. To solve the problem, we first consider a relatively simple case, i.e., a single gateway case, and propose a greedy method-based single gateway association and data scheduling algorithm. We then extend the solution to the case of multiple gateways and propose a transmission priority-based joint gateway association and data scheduling algorithm. Simulation results show that the proposed algorithm is superior to the algorithm proposed in previous work.
Cooperative mechanism of entity state information search with trajectory prediction
Puning Zhang, Xuefang Li and Xu yuan Kang (Chongqing University of Posts and Telecommunications, China)
0
In recent years, with the great progress made in embedded technology and communication technology, the number of mobile sensing devices such as smart phones, tablets, and wearable devices has grown exponentially. Such products have certain sensing, storing, computing, and communicating capabilities, and are able to complete some simple sensing tasks. Due to the influences of the location, observation period, energy supply and other factors on the fixed-deployed sensing equipment, the state information acquired by the search system in the process of matching the entity state users demand may not be accurate and complete. In view of this situation, acquiring physical state information through mobile smart devices such as smart phones, tablets, and wearable devices is a good solution. Selecting mobile intelligent devices with high sensing quality to work cooperatively to provide search services is vital, which takes advantage of the high mobility characteristic of mobile intelligent devices to fully acquire entity state information. Based on the research on how to realize the search collaboration among mobile intelligent devices, this paper uses the mobile intelligent devices' moving trajectories to predict whether they have the ability to participate in tasks, and then evaluates their sensing quality according to the historical task completion situation, and finally selects the mobile intelligent devices with high sensing quality to complete the search sensing tasks.
Session Chair
Guanglun Huang, Rong Chai
Session CIS-04
Physical Layer Security
Conference
3:10 PM
—
4:40 PM CST
Local
Aug 11 Tue, 3:10 AM
—
4:40 AM EDT
Physical Layer Secret Key Generation Based on Autoencoder for Weakly Correlated Channels
JingYuan Han, Xin Zeng and Xiaoping Xue (Tongji University, China); Jingxiao Ma (Tongji University, United Kingdom (Great Britain))
0
The reciprocity of the wireless channel is the basis of secret key generation on the physical layer as an emerging method for information security enhancement. Due to the duplex mode of communication systems, the channel responses detected by two connected legitimate nodes are not completely reciprocal. In this paper, an efficient physical layer secret key generation scheme is proposed based on an autoencoder to extract reciprocal features from weakly correlated channel estimates. The encoder part after training is equipped at both nodes to generate features for quantization in various channel environments. Simulation results show lower mean squared error (MSE) and better mutual information of the extracted features comparing to the most efficient linear generation method, the principal component analysis (PCA) based one. It reveals great potential to generate symmetric secret keys with better performance particularly in low SNR scenarios.
Secrecy Rate Maximization for Intelligent Reflecting Surface Aided SWIPT Systems
Wei Sun (Northeastern University, China); Qingyang Song and Lei Guo (Chongqing University of Posts and Telecommunications, China); Jun Zhao (Nanyang Technological University, Singapore)
0
Simultaneous wireless information and power transfer (SWIPT) and intelligent reflecting surface (IRS) are two promising techniques for providing enhanced wireless communication capability and sustainable energy supply to energy-constrained wireless devices. Moreover, the combination of the IRS and the SWIPT can create the "one plus one greater than two" effect. However, due to the broadcast nature of wireless media, the IRS-aided SWIPT systems are vulnerable to eavesdropping. In this paper, we study the security issue of the IRS-aided SWIPT systems. The objective is to maximize the secrecy rate by jointly designing the transmit beamforming and artificial noise (AN) covariance matrix at a base station (BS) and reflective beamforming at an IRS, under transmit power constraint at the BS and energy harvesting (EH) constraints at multiple energy receivers. To tackle the formulated non-convex problem, we first employ an alternating optimization (AO) algorithm to decouple the coupling variables. Then, reflective beamforming, transmit beamforming and AN covariance matrix can be optimized by using a penalty-based algorithm and a semidefinite relaxation (SDR) method, respectively. Simulation results demonstrate the effectiveness of the proposed scheme over baseline schemes.
Proactive Eavesdropping Scheme via Decode-and-Forward Relay with Multiple Full-Duplex Antennas
Lisheng Yang (Chongqing University, China); Jingyue Cui (School of Microelectronics and Communication Engineering, Chongqing University, China); Rui Ma (Chongqing University & Center of Communication and Tracking Telemetry Command, China); Haowei Wu and Jinglan Ou (Chongqing University, China)
1
This paper studies a legitimate proactive eavesdropping scenario where a central monitor covertly wiretaps the communications between suspicious users through a full-duplex multi-antenna relay. Specifically, the suspicious information is intercepted by the eavesdropping relay, and then encoded and forwarded to the central monitor. At the same time, the relay sends jamming signals to the suspect destination to reduce the quality of suspicious communication. To minimize the suspicious secrecy rate, the optimal forwarding and jamming beamforming vectors of the eavesdropping relay are first designed. Based on this optimized result, the best power allocation ratio is obtained. To this end, the optimal beamforming vectors and power allocation ratio are derived in closed-form. The simulation results verify the existence of the optimal forwarding power of the relay and show that the proposed scheme achieves better performance than the conventional schemes.
Dual-antenna Time-delay Countermeasure Against Passive Location System
Shiqi Zhang, Pinyi Ren and Qinghe Du (Xi'an Jiaotong University, China)
0
This paper considers countermeasure technology of satellite passive location system based on TDOA measurement. Considering that TDOA measurement is based on the principle of time difference estimation on emitter signal received by different receivers, a technology of the same signal form spread spectrum signals with different time delay emitted by two antennas in emitter is proposed. The center vectors of the two antennas point to different directions, which makes the power ratios of the two antennas signals received by different satellites different. Then, the paper compares the theoretical derivation of the time difference estimation between traditional location method and dual-antenna time-delay technology, and introduces the satellite passive location algorithm and location error index. Finally, the simulation results show that the time difference value estimated by receivers is wrong after using the dual-antenna time-delay technology, and location error in the satellite coverage area increases effectively. The closer the angle of the antenna center vector is to the ground, the better the effect will be. It is of great significance in protecting the communication security of users.
Secure Transmission in FDD MBM Systems Using Analog Feedback
Xiaomeng Zhou, Zhenzhen Gao and Xuewen Liao (Xi'an Jiaotong University, China)
0
In this paper, the physical layer security (PLS) issue is studied for frequency-division duplex (FDD) multiple-input multiple-output (MIMO) media-based modulation (MBM) systems with a multiple-antenna eavesdropper. A more practical scenario is considered that only the statistic channel state information (CSI) of the eavesdropping link is available and the imperfect CSI of the legitimate link is acquired by analog feedback. Based on these imperfect CSI, an artificial-noised-aided precoding scheme is proposed, and an effective achievable ergodic secrecy rate (ESR) is derived when taking into account the feedback overhead. The secrecy performance of the proposed scheme is evaluated through simulations in terms of ESR and bit error rate (BER). The influences of the key parameters such as the power allocation ratio and the feedback duration are also discussed.
Session Chair
Ning Zhang, Jiliang Li
Session MWN-06
Security
Conference
3:10 PM
—
4:40 PM CST
Local
Aug 11 Tue, 3:10 AM
—
4:40 AM EDT
Secure Routing Based on Geographic Location for Resisting Blackhole Attack In Three-dimensional VANETs
Jingxuan Lyu and Chenju Chen (Beijing University of Posts and Telecommunications, China); Hui Tian (Beijng university of posts and telecommunications, China)
0
Based on dynamic 3D Vehicle Ad Hoc Networks (VANET) environment, this paper puts forward Trust-based Greedy Forwarding Routing (TGF),including establishing trust model to resist black hole attack and selecting the secure routing path. Compared with the two-dimensional VANETs, the problem of transmission loss is considered in the three-dimensional environment. And in the process of establishing the secure route, the influence of geographic location and the number of interactions between nodes is considered. Compared with the Greedy Perimeter Stateless Routing (GPSR), the packet loss rate reduces approximately 24%, and the throughput increases approximately 18%. The NS3 simulation verifies that TGF is more suitable for three-dimensional scenarios with black hole attack than GPSR.
Adaptive Relay Selection with Physical Layer Security for Green Communicaions
Yanjun Yao (No. 38 Research Institute of China Electronic Technology Corporation, China)
0
This paper investigates the issue of physical layer security for green communications. Specifically, the cooperative communication scenario which contains one source node, one eavesdropper, one destination and multiple cooperative nodes is considered. We aim at minimizing the total power consumption under the restriction of security performance. To achieve this goal, two novel cooperation strategies are proposed. The two methods are named as Only Relay and Relay and Jamming Pair. The former selects one relay node for cooperation. However, as the legitimate receiver's channel condition deteriorates, in order to satisfy security performance, the system would switch to the latter method, which selects a relay and jamming node pair for cooperation. The optimum node selection and power allocation method under the two strategies is studied. The performance of minimal power consumption under different circumstances is investigated. Numerical simulation results show that compared to traditional communication without cooperative node, the proposed methods result in less power consumption under security restriction.
Improving the Security of Wireless Network from Software Perspective
Xiaoxue Wu and Weiqiang Fu (Northwestern Polytechnical University, China); Dejun Mu (College of Automation, Northwestern Polytechnical University, China); Deming Mao, Hui Zhang and Wei Zheng (Northwestern Polytechnical University, China)
0
To guarantee the security of the wireless network, effort must be paid to software security as software plays a more and more important role in the development of wireless network intelligentization. Security bug reports (SBRs) are bug reports that describe the security issues of software systems. Cross-project SBR prediction, which uses a prediction model trained with labeled data from one project to predict another project, has been proposed to eliminate SBRs of software products. While reviewing the previous work focused on cross-project SBR prediction, we find the performance (e.g., Recall, F1-score) of cross-project SBR prediction is too low to the production application. This paper proposes a hybrid sampling approach based on text similarity and uncertainty-sampling. We conduct experiments on ten publicly available datasets. The results show our approach could significantly improve the performance of cross-project SBR prediction. On average, the performance of the classification model can be improved by 34%, 64%, 48%, and 11% in terms of Recall, Precision, F1-score, and AUC, respectively.
Secrecy Performance Analysis in Internet of Satellites: Physical Layer Security Perspective
Yongpeng Shi (Luoyang Normal College, China); Ya Gao (Luoyang Normal University, China); Yujie Xia (Luoyang Normal College, China)
0
As the latest evolving architecture of space networks, Internet of Satellites (IoSat) is regarded as a promising paradigm in the future beyond 5G and 6G wireless systems. However, due to the extremely large number of satellites and open links, it is challenging to ensure communication security in IoSat, especially for wiretap resisting. To the best of our knowledge, it is an entirely new problem to study the security issue in IoSat, since existing works concerning physical layer security (PLS) in satellite networks mainly focused on the space-to-terrestrial links. It is also noted that, we are the first to investigate PLS problem in IoSat. In light of this, we present in this paper an analytical model of PLS in IoSat where a terrestrial transmitter delivers its information to multi-satellite in the presence of eavesdroppers. By adopting the key parameters such as satellites' deployment density, minimum elevation angle, and orbit height, two major secrecy metric including average secrecy capacity and probability are derived and analyzed. As demonstrated by extensive numerical results, the presented theoretical framework can be utilized to efficiently evaluate the secrecy performance of IoSat, and guide the design and optimization for communication security in such systems.
Session Chair
Xuefang Li, Rong Chai
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