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Beam-Based Secure Physical Layer key Generation for mmWave Massive MIMO system 15th

Beam-Based Secure Physical Layer Key Generation for mmWave M...

引用

15th EAI International Conference on Communications and networking, ChinaCom 2020

作者： Gao, Hao Huang, Yanling Liu, Danpu Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9783030677190

Massive MIMO system greatly enriches the randomness of the secret keys in the physical layer and increases the rate of key generation. However, it is not practical to obtain full channel state information for key generation in actual communication scenarios due to a large number of additional signaling overhead. In this paper, we proposed a feasible physical layer key generation scheme by using the beam information as a random source. The procedure for key generation is designed based on the current beam management mechanism in 5G NR. Therefore, the secret key is synchronously generated in the process of two-stage beam search between the gNB and the UE before data transmission, and the additional signaling overhead for key generation is little. Furthermore, to cope with the non-uniform distributed characteristics of the beams, we adopt Huffman code in the encoding of the beam index, thereby improving the efficiency of the key generation. Simulation results show that the proposed scheme can achieve mutual information per bit as high as 0.97, which is 2% to 3% better than that of equal length coding. Furthermore, the bit disagreement rate can be less than 1% in a harsh communication environment with a signal-to-noise ratio of −10 dB. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： MIMO systems

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Research on Unequal Clustering Protocol based on Fuzzy Logic and Entropy Weight Method 7

Research on Unequal Clustering Protocol based on Fuzzy Logic...

引用

7th International Conference on Computer and Communications, ICCC 2021

作者： An, Quanbiao Wu, Muqing Lu, Sixu Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

ISBN: (纸本)9781665409506

Clustering is an effective strategy to minimize the energy consumption of nodes in energy-constrained wireless sensor networks. In clustered wireless sensor networks, the network is divided into multiple clusters, and each cluster has a coordinator called cluster head, which collects data from its cluster members and forwards it to the base station through other cluster heads. Cluster wireless sensor networks often have hot spot problems. Due to high energy consumption caused by data forwarding load, cluster heads near the base station die earlier. This kind of node death leads to the coverage loophole of the network early and reduces the life cycle of the network. Unequal clustering is a technology to solve this problem. In non-uniform clustering wireless sensor networks, the size of clusters near the base station is smaller than that far away from the base station. In the process of cluster formation, non-cluster-head nodes are generally added to nearby cluster-head nodes. In this paper, an unequal clustering protocol based on fuzzy logic and entropy weight method (FEUC) is proposed to extend the life cycle of the network. This protocol makes the network form clusters of different sizes. Fuzzy logic method is used to select cluster heads and non-cluster heads join cluster heads to form clusters. The objective entropy weight method is used to select relay cluster heads to implement multi-hop routing strategy. Mamdani method is used for fuzzy reasoning. The proposed protocol is compared with the low-energy adaptive clustering hierarchy (LEACH) protocol, the energy-aware unequal clustering fuzzy protocol (EAUCF), and the fuzzy-based unequal clustering protocol (FUCA), in all scenarios, the proposed protocol has better performance. © 2021 IEEE.

关键词： Base stations

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Weighted Voronoi Sensing Partition Algorithm for Multi-layer Wireless Sensor network 7

Weighted Voronoi Sensing Partition Algorithm for Multi-layer...

引用

7th International Conference on Computer and Communications, ICCC 2021

作者： Xing, Zehui Wu, Muqing Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing China

ISBN: (纸本)9781665409506

Wireless sensor networks have been widely implemented in plenty of areas such as environmental observation, agricultural industry, military programs, etc. These sensors are usually deployed in places that are inconvenient or hostile to people, and thus, they cannot be charged and will be abandoned once their energy runs out. In this article, a novel algorithm, WVSP (Weighted Voronoi Sensing Partition Algorithm), is proposed. It is based on hierarchical architecture, which improves the scalability of networks when there are plenty of nodes within the networks. WVSP divides the sensing area into several concentric fan-like rings whose center is the sink node. In each fan-like layer, WVSP computes an optimal number of cluster heads by a correction factor and uses weighted Voronoi polygons to set up clusters. Compared to the LEACH (Low Energy Adaptive Clustering Hierarchy algorithm) and OHILEACH (Optimized Heuristic algorithm of Improved Low Energy Adaptive Clustering Hierarchy), the proposed WVSP algorithm improves the performance of network lifetime and energy efficiency. The simulation demonstrates that in the first scenario, WVSP can save 46.7% and 20.2% more energy than LEACH and OHILEACH, with 75.5% and 35.5% more nodes still alive than LEACH and OHILEACH. In the second scenario, WVSP can save 26.7% and 10.3% more energy than LEACH and OHILEACH, with 65.5% and 40.0% more nodes still alive than LEACH and OHILEACH. © 2021 IEEE.

关键词： Heuristic algorithms

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Identification of key Nodes in Complex networks 7

Identification of Key Nodes in Complex Networks

引用

7th International Conference on Computer and Communications, ICCC 2021

作者： Qiao, Lilin Wu, Muqing Zhao, Min Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665409506

Identification of key nodes in network is of great significance in practical application. Some of the existing importance evaluation indexes have the defects of limited scope of application and incomplete evaluation results. Considering that the importance of nodes in complex networks is not only affected by a single factor, this paper proposes a key node identification algorithm based on multi-attribute weighted fusion (KNIA-MWF). We quantitatively analyze the influence of different attributes on nodes and assign the index weights by the combination of objective entropy weight method (EWM) and subjective analytic hierarchy process (AHP) to obtain the final topological importance (FTI) of each node which represents its structural importance. This algorithm can not only be used to identify the key nodes of different types of complex networks, but also be easy to be extended. Experimental results of removing key nodes in five kinds of networks show that KNIA-MWF can accurately identify the critical nodes in complex networks. © 2021 IEEE.

关键词： Complex networks

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Reliability and Latency of MmWave Communications Based on Blockage Avoidance in Internet of Vehicles 13

Reliability and Latency of MmWave Communications Based on Bl...

引用

13th International Conference on Wireless Communications and Signal Processing, WCSP 2021

作者： Cao, Yongxu He, Xinxin Yu, Congqing Yin, Changchuan Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing100876 China

ISBN: (纸本)9781665407854

The millimeter wave(mmWave) communication is a viable approach to support the Gbps data rates that would be required for raw sensor data exchange among autonomous vehicles. However, there is a main challenges resulting from the use of high-frequency bands: the mmWave blockage effect. In this paper, we propose a blockage avoidance based mmWave relay scheme for the Internet of Vehicles. Specifically, we first propose a mmWave link availability identification method based on the vehicle geometric relationship and the spatial correlation between sub-6 GHz signals and mmWave signals. Secondly, in order to improve the reliability of all vehicle sensor data transmission and reduce the overall transmission delay, a resource allocation scheme based on the real-time blocking relationship graph among multilane vehicles is proposed. The simulation show that compared with the baseline, the packet loss rate of proposed scheme is increased by 20%, and the transmission delay is reduced by 80%, which can realize stable, reliable and efficient transmission. © 2021 IEEE.

关键词： Millimeter waves

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Location-Based Multi-site Coordination Beam Tracking for Vehicle mmWave Communications 15th

Location-Based Multi-site Coordination Beam Tracking for Veh...

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15th EAI International Conference on Communications and networking, ChinaCom 2020

作者： He, Xingwen Liu, Danpu Zhang, Zhilong Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9783030677190

Millimeter wave (mmWave) system with massive multiple input multiple output (mMIMO) meets increasing data traffic requirements. However, fast beam tracking for vehicles with high mobility causes enormous overhead, especially in an ultra-dense network (UDN) with frequently base station (BS) handover. In this paper, we proposed a multi-site coordination beam tracking scheme utilizing the spatial correlation of channel state information (CSI) among different sites to reduce the signaling overhead for beam training and handover. The scenario is a hyper-cellular network (HCN) with one control-BS (CBS) and multiple traffic-BSs (TBSs). The proposed scheme consists of two stages. In the first stage, more accurate position measurement of the moving user equipment (UE) can be achieved by using uniform planar array (UPA), and Extended Kalman Filter (EKF) is exploited in CBS to predict the UE’s location in the next slot. In the second stage, the relationship between multi-site and UE’s location is used by the CBS to remotely infer the candidate beam between each TBS and the UE, and make a TBS handover decision when necessary. Given that it is the CBS in charge of beam tracking between all the TBSs and the UE centrally, the overhead for beam training and handover are both efficiently reduced. Simulation results based on realistic 3D scenario show that the proposed scheme can achieve 99% of the optimal spectral efficiency with fewer overhead for beam sweeping and handover signaling. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Extended Kalman filters

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Arrival Angle Estimation Based on Transfer Learning in Complex Environments

Arrival Angle Estimation Based on Transfer Learning in Compl...

引用

International Conference on Computer and Communications (ICCC)

作者： Xingjian Li Xinghe Chu Luhan Wang Zhaoming Lu Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Infrmation Networks Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

Signal Angle-of-Arrival estimation has been widely studied as an important sensing technology in Integrated Sensing and Communications, but its performance is limited by complex multipath environments and the scale of antenna arrays. In recent years, learning-based signal angle-of-arrival estimation methods have made breakthroughs, but the effectiveness of learning methods is closely related to the richness of datasets. In the new generation of communication systems, the large-scale deployment of base stations for sensing needs, the data set is difficult to cover a large number of complex and changeable scenarios, and there are problems such as excessive collection scale and difficult labeling. In order to achieve effective estimation of signal angle-of-arrival in complex environments, this paper uses the method of transfer learning to reduce the cost of data set collection and improve the accuracy of estimation. The transfer learning in this paper uses a domain adversarial model to achieve unlabeled transfer from simple to complex scenes. The experiments set up multiple scenarios such as multi-source, multi-path, and array defects. The migration results show that the method can effectively improve the performance of angle-of-arrival estimation in most scenarios, and verify the adaptability of the proposed method to complex environments.

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Joint Base Station Sleeping and Functional Split Orchestration in Crosshaul-Based V-RAN

Joint Base Station Sleeping and Functional Split Orchestrati...

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IEEE Conference on Wireless Communications and networking

作者： Zhenghe Zhu Hang Li Yawen Chen Xiangming Wen Zhaoming Lu Luhan Wang Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing University of Posts and Telecommunications Beijing China

The intensive deployment of base stations (BSs) in the radio access network (RAN) incurs huge energy consumption and operating overheads. Although the centralized RAN (C-RAN) architecture can significantly relieve the BS overheads by centralizing BS functions, the strict front-haul requirements of C-RAN make it challenging to realize a fully centralized RAN. Recently, the virtualized RAN (V-RAN) architecture has been proposed, allowing flexible function split (FS) and crosshaul to balance the centralization and mid-haul requirements. On the other hand, considering the tidal effect of traffic, sleep some BSs with low loads and migrating their traffic to other BSs is an effective way to further reduce energy consumption. In this paper, we investigate joint BS sleeping and FS orchestration in crosshaul-based V-RAN that jointly optimizes BS working mode, FS, traffic migration, and routing selection. The joint optimization model is formulated as a mixed-integer nonlinear programming (MINLP) that minimizes total expenditure, including RAN energy consumption and operating overheads. Considering the complexity of the problem, we propose a heuristic algorithm to solve it in polynomial time. Simulation results validate that our algorithm can save significant expenditure compared to baselines, and the results can reach within 1.13 times the optimum in a relatively short time.

关键词： Energy consumption Base stations Costs Simulation Heuristic algorithms Programming Routing

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Cooperative double-IRS Assisted Integrated Sensing and Communication Under NLoS Conditions

Cooperative double-IRS Assisted Integrated Sensing and Commu...

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IEEE International Conference on Communications (ICC)

作者： Wan Xiang Yawen Chen Zhaoming Lu Xiangming Wen Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing University of Posts and Telecommunications Beijing China

We study an integrated sensing and communication (ISAC) system assisted by cooperative double-intelligent reflecting surface (IRS). The IRSs are deployed near the base station (BS) and the users respectively. The BS uses its nearby IRS to sense the potential target in the blocked area and uses the double-reflection and single-reflection links provided by the IRS to realize the communication between the BS and the multi-users. We consider an orthogonal transmission signal, aiming to maximize the weighted sum of the minimum signal-to-interference-plus-noise ratio (SINR) of the sensing and the minimum communication SINR among all users, jointly optimizing the active beamforming of the BS and the passive beamforming of two distributed IRSs. We propose an efficient algorithm for obtaining high quality solutions using alternating optimization and semidefinite relaxation techniques. Simulation results show that, compared with the benchmark algorithm, the proposed joint beamforming design achieves the balance between communication and sensing performance, and shows that the use of cooperative double-IRS is beneficial to improve the performance of ISAC system.

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Joint Latency and Energy Consumption Optimization with Deep Reinforcement Learning for Proximity Detection in Road networks 7

Joint Latency and Energy Consumption Optimization with Deep ...

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7th International Conference on Computer and Communications, ICCC 2021

作者： Zhao, Tongyu Liu, Yaqiong Shou, Guochu Hu, Yihong Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing China

ISBN: (纸本)9781665409506

Artificial intelligence and the automobile business have grown significantly in recent years, and autonomous driving has progressively been the industry's focus. The problem of proximity detection in road networks refers to determining if two moving objects are close to one other in real time. However, in the real world, mobile devices' battery life and computing capabilities are restricted, resulting in excessive latency and energy usage. As a result, determining the proximity relationship between mobile users with low latency and energy usage is a difficult task. We formalize the joint latency and energy consumption optimization problem for proximity detection in road networks into a constrained optimization problem (COP) and solve it using a deep Q network (DQN). The simulation results show that DQN can ensure the desired sum cost under a variety of important factors, effectively reducing latency and energy usage. © 2021 IEEE.

关键词： Reinforcement learning

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