Journal of Beijing University of Posts and Telecommunications

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Multi-user-oriented SWIPT-MEC Task Hierarchical Processing Offloading Mechanism

Journal of Beijing University of Posts and Telecommunications 2023, 46 (5): 72-79.

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In order to ensure the multi-user mobile edge computing (MEC) network based on simultaneous wireless information and power transfer (SWIPT), the delay and energy consumption during the offloading process can be minimized under the condition of limited channel resources.This paper proposes a multi-task hierarchical processing mechanism (MHPM) by planning the offloading ratio of computing tasks and the channel allocation during the link transmission ,which realizes the rational scheduling of channel resources in the process of computing offloading.According to the average time consumption and energy consumption of mobile equipment in the process of MEC offloading, a mathematical model of constrained multi-objective optimization problem was established, and the model was solved by combining MHPM and sorting genetic algorithm ⅱ optimization algorithm, which maximized the relationship between device delay and energy consumption.Simulation results show that MHPM can reduce the average time consumption and energy consumption of equipment in offloading process, and the optimal solution of objective function can be obtained by using constrained multi-objective optimization algorithm.

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Fine-grained emotion analysis of online comments based on the fusion of ontology and deep learning

Journal of Beijing University of Posts and Telecommunications 2023, 46 (5): 125-131.

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Fine grained emotion analysis analyzes the author's emotional tendency from the perspective of the evaluation object and its attributes through the text. Its main tasks include the recognition of the evaluation object and its attributes (topic recognition) and emotion recognition. To solve the problems of poor fine grained emotion recognition and poor interpretability of deep learning methods in previous studies, a fine-grained emotion analysis model integrating ontology and deep learning is proposed. The model uses domain ontology and CNN fusion methods to identify explicit and implicit topics, and combines emotion dictionary and Bi LSTM+Attention model to identify fine-grained emotions of online comment texts. The experimental results show that the proposed fine-grained sentiment analysis method has advantages over other methods in accuracy, recall and F value.

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PERC Roberta：Emotion Recognition in Conversation using ERC Roberta with Learning

Qi-Wei GONG

Journal of Beijing University of Posts and Telecommunications 2023, 46 (5): 106-111.

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With a broad area of its applications, the task of emotion recognition in conversation has increasingly attracted attention. The text in the dialogue contains information about the speakers and links closely with the preceding ones, thus a particular word order and structural features are represented by it. Excellent results have been obtained in studies on emotion recognition in conversation using transformer-based pre-training models. However， its traditional classification approaches cannot take into account conversational word order and structural feature. And a mismatch will occur between the downstream task and the pre-trained task. learning can narrow the gap between them by reconstructing downstream tasks. Therefore, the PERC Roberta model is proposed. This model first learns word order and structural features of the dialogue by predicting masked texts and then reconstructs the downstream task through ing learning, thus a richer dialogue knowledge distributed in the pre-training model can be further stimulated. The experiments conducted on two public data, MELD and EmoryNLP, demonstrate the superior performance of the proposed PERC Roberta model. Further, the ablation experimental results also prove the effectiveness of each step in the PERC Roberta model. The code is publicly available on GitHub repository1.

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Deterministic Scheduling and Routing Joint Intelligent Optimization Scheme in Computing First Network

Journal of Beijing University of Posts and Telecommunications 2023, 46 (2): 9-14.

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The Compute first network (CFN) integrates heterogeneous computing power information with the network to improve resource utilization and network transmission efficiency. The time-sensitive network (TSN) ensures low-latency and high-reliability transmission performance. The fusion of the two can achieve high efficiency deterministic forwarding. The resource scheduling and routing planning in the integrated decision-making CFN and the gate control arrangement in the TSN will have problems such as too many decision variables, too high computational complexity, and insufficient optimization performance. In response to the above problems, a fusion architecture based on IEEE 802.1Qbv for gated arrangement, computing network routing planning, and computing resource scheduling is proposed. Based on deep reinforcement learning, an improved RBDQN (reward-back deep Q-learning) algorithm is proposed to optimize gate control list, and a greedy algorithm is used to assist routing path planning. The algorithm establishes a utility function based on the average delay, energy consumption and user satisfaction as multiple optimization indicators. The simulation results show that, compared with the genetic algorithm, RBDQN can reduce the convergence time of small-scale scheduling problems by more than 1 times, and can reduce the convergence time by dozens of times for multi-service and multi-node computing network problems. At the same time, the algorithm can avoid the model from falling into a local optimum. Compared with the traditional DQN, the decision result improves the performance of the utility function index by more than 10%, and the convergence time under the same index decreases by about 50%.

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Service Networking Over Hyper-WAN Integrated Distributed Cloud：Vision and Key Technologies

Journal of Beijing University of Posts and Telecommunications 2023, 46 (2): 1-8.

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With the development of cloud computing, edge computing, distributed cloud and other technologies, the future network should distribute and cooperate all kinds of service resources (computing power, data, content, etc.) intelligently and dynamically at multiple levels of “cloud edge”, and even across wide area network of multiple operators. To meet the service need and networking wish, Service Networking Over Hyper-WAN Integrated Distributed Cloud is proposed originality. Future network dual plane networking vision and layered architecture are introduced and the key technologies with cloud management platform and network operating system are proposed, such as service identification, dynamic networking routing, deterministic network and resource integrated scheduling in terms of principle and performance. Finally, the existing challenges and future directions are discussed．

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Integrated sensing and communication interference management: recent advances and future trends

Journal of Beijing University of Posts and Telecommunications 2022, 45 (6): 32-41.

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For the sixth generation mobile communication system (6G), the integrated sensing and communication technology, as one of the key technologies of 6G, will help realize the development needs of 6G digitization, networking and intelligence. Interference management in the integrated communication and sensing system faces many challenges. The connotation not only includes the mutual interference cancellation when the sensing subsystem and the communication subsystem cooperate to realize the integrated communication and sensing function, but also includes more flexible and efficient interference avoidance and interference utilization methods, which reflects the development concept of green communication. First describes the necessity of interference management in the integrated system of sensing and communication. Then, the interference elimination methods are reviewed respectively from three paradigms of integrated system implementation and the feasible methods to realize the vision of interference avoidance and interference are put forward follow. Finally, we conclude the paper and identify some open problems in this field.

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Virtual Massive MIMO Channel Estimation Algorithm in UAV Swarm Communications

Journal of Beijing University of Posts and Telecommunications 2022, 45 (6): 48-54.

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In the application scenario of hot spots coverage with UAV (unmanned aerial vehicle) swarm communications, a channel estimation algorithm for virtual large-scale multiple input multiple output channel in UAV swarm communication is proposed. The proposed channel algorithm includes a direction of arrival (DOA) estimation algorithm and sub-array spacing estimation algorithm in the steering-vector of the channel state information. Considering that the air to ground channel state depends on the angle domain information of the ground users, the auxiliary user is used to estimate the direction angle of the UAV. Based on this, a reduced rank based DOA estimation algorithm is proposed to obtain high-precision DOA information. Furthermore, considering that the dynamic position change of UAV results in the relative position change of antenna arrays of different UAVs, a sub-array spacing estimation algorithm based on optimization search is proposed to avoid the high computational complexity caused by large-scale search. Simulation results show that the proposed DOA and sub-array spacing estimation algorithm can improve the accuracy of channel estimation.

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Research progress of potential applications of AI in 6G air interface physical layer

Journal of Beijing University of Posts and Telecommunications 2022, 45 (6): 22-31.

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With the rapid development of artificial intelligence (AI) and the rapid growth of network traffic, emerging intelligent applications urgently need a faster, more reliable, and more flexible form of communication network. As a key enabling technology for the intelligent information society in 2030, 6G is expected to support an unprecedented "Internet of Everything" scenario and meet a variety of diverse and challenging needs. However, it also puts forward more stringent requirements for the next generation of wireless communication. In this thesis, academia and industry apply AI to the physical layer of wireless communication, which provides a new idea for the optimization of the transmission architecture of wireless communication systems. This thesis first introduces the AI native theory briefly, then analyzes the relevant research in recent years around four key AI based 6G air interface PHY technologies which includs channel estimation, signal detection, passive beamforming and index modulation (IM), what’s more, summarizes their applications and contributions, and finally points out the challenges and future research directions of AI in 6G.

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Description and measurement of semantic information for the intelligent machine communication

Journal of Beijing University of Posts and Telecommunications 2022, 45 (6): 12-21.

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Semantic information has the characteristics of high abstraction, intelligence and simplicity. Semantic communication introduces a new semantic dimension and focuses on information content rather than coding symbols, which will greatly improve the efficiency of information transmission. With the deep integration of artificial intelligence and communication technology, semantic communication has been widely concerned by the academic and industrial circles, which will help solve the problems of super-large-scale connection and massive data transmission in intelligent machine communication, and play an important role in realizing efficient communication between machines. Based on information theory and guided by artificial intelligence, this paper summarizes the design method of end-to-end intelligent semantic communication system, presents the description and measurement of semantic information, investigates the encoding and decoding methods and analyses the evaluation indexes of semantic communication system.

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Polar Coded Modulation for 6G System

Journal of Beijing University of Posts and Telecommunications 2022, 45 (6): 1-11.

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The next 6th generation of mobile communications system (6G) will reveal significant improvements in the key performance indicators and support diverse communication scenarios. These put forward higher requirements on the coded modulation technologies. In this paper, the advantages of the polar-coded modulation (PCM) in 6G are first investigated. Then, the principles of multilevel PCM (MLC-PCM) and bit-interleaved PCM (BIPCM) are discussed for the high spectral efficiency and low latency scenarios, respectively. In practical PCM systems, the existing construction methods encounter the problems of high complexity and poor flexibility. To solve these problems, a universal construction framework of PCM is proposed, and the operating procedures in MLC-PCM and BIPCM are also discussed in detail. This construction method utilizes “sum rate approximation” to assign code rates to polar component codes, which performs independently of the actual channel conditions and can significantly reduce the construction complexity of PCM. Simulation results further verify its flexibility and universality with better performance than the 5G low-density parity-check (LDPC)- coded modulation schemes.

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Construction of Multi-Modal Knowledge Graph for Epilepsy Related Papers

LI Xingyuan, WANG Peng, SHEN Mu, LI Lei, ZHANG Lin

Journal of Beijing University of Posts and Telecommunications 2022, 45 (4): 19-24. DOI: 10.13190/j.jbupt.2021-187

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The performance of the existing named entity recognition and relation extraction models would sharply decline due to the lack of a large amount of annotated data for epilepsy-related papers. To solve this issue, a zero-resource named entity recognition and relation extraction model in the epilepsy domain is proposed based on medical data and a pre-training model from similar domains. The performance of the existing unsupervised and semi-supervised models on the epilepsy paper data set isevaluated, and then a domain adversarial network and a relation discriminator are introduced based on the characteristics of the data set to effectively improve the construction effect of the epilepsy domain knowledge graph. Electroencephalography (EEG) features of epilepsy patients are embedded into the knowledge graph in a visual modality. While improving the interpretability of EEG analysis, it builds a more intuitive multi-modal knowledge graph.

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Lung Nodule Detection System Based on Data Augmentation and Attention Mechanism

LI Yang, GAO Shiqi

Journal of Beijing University of Posts and Telecommunications 2022, 45 (4): 25-30. DOI: 10.13190/j.jbupt.2021-189

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To solve the problem of limited model learning ability caused by insufficient labeled medical image data and easy loss of tiny nodule features caused by sub-sampling in the process of deep detection, a lung computer aided-detection system based on a generative adversarial network based on computed tomography data augmentation and improved you only look once-V4 (YOLO-V4) detection framework is designed. First, the regularization method DropBlock is introduced into the nodule generation framework computed tomography-generative adversarial networks to augment the data of annotated medical images, which can improve the generation quality of pulmonary nodules. Second, the coordinate attention model is introduced in YOLO-V4, which was constructed to capture the position perception, direction perception and cross-channel information of pulmonary nodules, which can further help the model to detect the region of interest of pulmonary nodules more accurately. The experimental results show that the performance indexes of data augmentation and nodule detection in the lung nodule analysis 16 data set of the proposed lung computer aided detection system are superior to the comparison algorithm, which can effectively expand the data set and improve the performance of nodule detection.

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Siamese Network Target Trackingthat Combines Dual Attention and Feature Fusion

LI Xue, LI Xiaoyan, WANG Peng, SUN Mengyu, Lü Zhigang

Journal of Beijing University of Posts and Telecommunications 2022, 45 (4): 116-122. DOI: 10.13190/j.jbupt.2021-169

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In order to solve the problem that the evolution of siamese visual tracking with very deep networks (SiamRPN++) algorithm when the target is occluded and deformed. A siamese network target tracking algorithm combining dual attention and feature fusion is proposed. Firstly, the channel and spatial attention module are used to enhance the target information, suppress the interference information in the image and improve the accuracy of the model; then, multi-layer feature fusion is carried out for the shallow and deep feature information output from the attention layer to obtain better expressive target features and improve the tracking accuracy; finally, the online template update mechanism is introduced to reduce tracking drift and improve the tracking robustness. The OTB100 dataset is used for experimental and the results show that the success rate of the improved algorithm is increased by 1.3% compared with SiamRPN++, indicating that the tracking accuracy of the algorithm is higher; under the four test sequences with occlusion and deformation attributes, the average overlap rate of the improved algorithm is increased by 3%, and the average center position error is reduced by 0.37 pixels, which is better robustness against occlusion and appearance deformation.

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6G Vision, Scenarios and Network Requirements

CUI Chun-feng, WANG Sen, LI Ke, DONG Jing, ZHENG Zhi-min

Journal of Beijing University of Posts and Telecommunications 2020, 43 (6): 10-17. DOI: 10.13190/j.jbupt.2020-160

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Towards the year 2030 and beyond, the overall visions and typical scenarios of the sixth generation of mobile communications system (6G) are discussed preliminarily, and a method for estimating key performance indicators (KPIs) of 6G networks is proposed innovatively. Besides, according to the prediction of the service oriented for 2030, we formulate the traffic models. In addition, the values of KPIs under different typical scenarios are calculated based on the parameters of the traffic models and the user models.

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A Cloud-Edge Collaborative Computing Task Scheduling Algorithm for 6G Edge Networks

MA Lu, LIU Ming, LI Chao, LU Zhao-ming, MA Huan

Journal of Beijing University of Posts and Telecommunications 2020, 43 (6): 66-73. DOI: 10.13190/j.jbupt.2020-161

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A distributed cloud-edge collaborative computing architecture for the sixth generation of mobile communications system (6G) is proposed. Furthermore, a cloud-edge collaborative computing task scheduling algorithm based on the Proximal Jacobian alternating direction multiplier method (ADMM) is designed. This algorithm models the computing task scheduling in cloud-edge collaboration architecture as a system costs minimization problem considering the system delay, energy consumption, bandwidth costs, and quality of service (QoS) loss etc. Then the algorithm is solved through an efficient distributed parallel computing method. The simulation results show that the proposed algorithm can reduce network operating costs while ensuring QoS, and achieve high execution efficiency and fast convergence.

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Data-Importance-Aware Resource Allocation in IRS-Aided Edge Intelligent System

TIAN Hui, NI Wan-li, WANG Wen, ZHENG Jing-heng, HE Shuo

Journal of Beijing University of Posts and Telecommunications 2020, 43 (6): 51-58. DOI: 10.13190/j.jbupt.2020-162

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In order to solve the problem of model aggregation in intelligent reflecting surface (IRS) aided edge intelligent system, a data-importance-aware resource allocation algorithm is proposed by using convex optimization and branch-and-bound methods to alternately design the user's uplink power, transmission time, and the phase shifts of IRS. Simulation results show that the proposed algorithm can effectively aggregate the model parameters of the distributed agents based on the importance difference of local data, and can maximize the uplink weighted sum rate.

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Intelligent Resource Allocation Algorithm for 6G Multi-Tenant Network Slicing Based on Deep Reinforcement Learning

GUAN Wan-qing, ZHANG Hai-jun, LU Zhao-ming

Journal of Beijing University of Posts and Telecommunications 2020, 43 (6): 132-139. DOI: 10.13190/j.jbupt.2020-211

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In the future, the sixth generation of mobile communications system (6G) network services merge reality and virtual reality, and support real-time interaction. It is urgent to quickly match the personalized service requirements of multiple tenants, therefore a two-layer hierarchical intelligent management scheme for network slicing is proposed, including the global resource manager at the upper level and the local resource managers for different tenants at the lower level. Firstly, based on the real-time status description of end-to-end slice, a service quality evaluation model is established considering the difference of multi-type slice requests from different tenants. With the service quality feedback, deep reinforcement learning (DRL) algorithm is adopted to optimize the global resource allocation and local resource adjustment. Hence, utilization efficiency of multi-dimensional resources in different domains are improved and tenants are able to customize resource usage. The simulation results show that the proposed scheme can optimize the long-term revenue of resource providers while guaranteeing the service quality.

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Entropy Reduced Mobile Networks Empowering Industrial Applications

ZHANG Ping, XU Xiao-dong, HAN Shu-jun, NIU Kai, XU Wen-jun, LAN Yue-heng

Journal of Beijing University of Posts and Telecommunications 2020, 43 (6): 1-9. DOI: 10.13190/j.jbupt.2020-260

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Currently, the mobile networks represented by the fifth generation of mobile communications system (5G) are facing various challenges in empowering industrial applications. The requirements and challenges of 5G empowering industrial applications in communication, control, computation, and security are analyzed. It formulates the sixth generation of mobile communications system(6G) evolution of the mobile networks for empowering industrial application, in a special form named as entropy reduced mobile networks. Based on information theory and directed by systems theory, the entropy reduced mobile networks emphasizes the utilization of endogenous intelligence of semantic information and endogenous simplicity architecture to achieve the global optimization for realizing mobile networks empowering industrial applications, which formulates a potential evolution path to 6G.

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Research and Prospect of TCP Optimization in 5G Multi-Access Networks

WANG Ying, LI Hong-lin, FEI Zi-xuan, ZHAO Hong-yu, WANG Hong

Journal of Beijing University of Posts and Telecommunications 2019, 42 (1): 1-15. DOI: 10.13190/j.jbupt.2018-280

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In order to optimize the transmission control protocol (TCP) in the fifth generation of mobile communications system (5G), a survey on the optimization mechanism of TCP protocols in 5G multi-access networks is given. Firstly, the limitations and challenges of TCP protocols in wireless access networks are analyzed. Then, the TCP optimization schemes in wireless access networks are sorted out, which are mainly classified into single-path TCP optimization and multipath TCP optimization, simultaneously the comparative analysis of various optimization schemes is summarized. Finally, the development directions of TCP protocol optimization are presented.

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A Survey of Positioning Technology for 5G

ZHANG Ping, CHEN Hao

Journal of Beijing University of Posts and Telecommunications 2018, 41 (5): 1-12. DOI: 10.13190/j.jbupt.2018-185

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Seamless wide-area coverage, high-capacity hot-spot, low-power massive-connections and low-latency high-reliability are the four major technical scenarios of the fifth generation of mobile communications system(5G). The location information of the mobile terminal is not only the demand of new services, but also effectively meets the key challenges faced by 5G new services in terms of traffic density, number of connections, ultra-low latency, high reliability, and high mobility. A survey of positioning technology oriented to 5G is given by analyzing the main directions involved in positioning. Firstly, starting from the demand of 5G technical scenarios, the research progress of existing positioning technology for 5G demand is introduced. After the classification of positioning method, the 5G technologies that are good for localization is summarized. Finally, the challenges of 5G mobile station positioning are analyzed, and the future research directions are given.

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Overview on the Progress of Design and Standardization of the Fifth Generation of Mobile Communications System

SUN Shao-hui, GAO Qiu-bin, DU Ying, LIU Xiao-feng, AI Ming

Journal of Beijing University of Posts and Telecommunications 2018, 41 (5): 26-43. DOI: 10.13190/j.jbupt.2018-195

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With the continuous development of information technology, the key technology and system design of the fifth generation of mobile communications system (5G) has become a hotspot in both academia and industry. A complete overview of 5G design and standardization progress,including thekey performance index (KPI) of 5G was provided,the work plan of international standardization organization on 5G,and 5G design based on 3GPP R15. Specifically,the key technology of physical layer,the protocol stack and procedure of air interface,the radio access network architecture and interface design,the key technology and architecture of core network were introduced and analyzed. We try to provide a whole picture of 5G design,from radio access network to core network. Therefore, a clear understanding of the overall design ideas, solutions and features of 5G technology, as well as the 5G standardized contents can be achieved.

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Analysis of eMTC for 5G mMTC Scenarios

WEN Xiang-ming, PAN Qi, LU Zhao-ming, JING Wen-peng, LI Lin-pei

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM 2018, 41 (5): 13-19. DOI: 10.13190/j.jbupt.2018-164

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In order to clarify the enhanced machine type communications (eMTC) proposed by the third generation partnership project (3GPP), the improvements of eMTC for support of 5G mMTC scenarios were summarized. Key technologies were discussed and analyzed in terms of system cost and complexity, coverage and power consumption. Besides, the main technical enhancements of eMTC in Rel-14 were introduced. Finally, the future development trend for eMTC was also be interpreted and analyzed based on present existing problems.

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A Review on Physical Layer Security Techniques for 5G

REN Pin-yi, TANG Xiao

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM 2018, 41 (5): 69-77. DOI: 10.13190/j.jbupt.2018-205

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Physical layer security techniques exploit the inherent randomness of wireless medium for information security, but which has been significantly challenged by the rapid development and evolvement of the fifth generation of mobile communications system (5G). The research and application of physical layer security techniques in 5G wireless networks was reviewed from three aspects:the joint investigation of physical layer security techniques and the new transmission techniques, the security enhancement schemes under emerging network scenarios, and the countermeasure design against the new threats in 5G wireless networks. Based on the survey of the latest researches in these areas, the open issues and future research directions were discussed.

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Latest Progress on 5G NR Trial of Enhanced Mobile Broad Band

LIU Guang-yi, ZHENG Yi, WANG Fei, LIU Jian-jun, WANG Qi-xing

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM 2018, 41 (5): 44-51. DOI: 10.13190/j.jbupt.2018-206

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As the Release 15 of the fifth generation of mobile system (5G) frozen in June 2018 by 3 ^rd generation partner project (3GPP), the industrialization of 5G system is being accelerated for commercial launch towards 2020. As the next step of the production of 5G system, it is needed to validate if the 5G specifications can meet the minimum performance requirements defined by 3GPP. Based on the latest 5G specifications, a prototype of 5G new radio (NR) base station was designed and developed, and the field trial of enhanced mobile broad band (eMBB) was conducted in the typical urban scenarios. The key performance indicators were validated against the minimum requirements of peak throughput, cell throughput, coverage and latency. The results proved that the 5G prototype can fulfil the minimum requirements of 5G system defined by 3GPP.

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Overview on IMT-2020 Channel Model Standard

TIAN Lei, ZHANG Jian-hua

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM 2018, 41 (5): 62-68. DOI: 10.13190/j.jbupt.2018-211

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Wireless channel model, as the baseline in the technology evaluation, is very complex. To support the demand of the fifth generation of mobile communications system (5G) technology evaluation, the main characteristics and simulation method of the 5G channel model in the standard are introduced, comparing with the the fourth generation of mobile communications system channel model delivered by the International Telecommunication Union (ITU), including scenario configuration, simulation procedure, and advanced channel components, etc. Hence, a detailed understanding of ITU 5G channel model has been made for the readers, in order to improve the further simulation and evaluation of 5G technology, as well as subsequent research and development.

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Wireless Big Data Enabled Emerging Technologies for Beyond 5G System

ZHANG Si-hai, ZHANG Jian-hua, CHEN Ying, ZHU Jin-kang

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM 2018, 41 (5): 52-61. DOI: 10.13190/j.jbupt.2018-258

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The fifth generation of mobile communications system (5G) will be deployed in 2020 and provide diverse communication capabilities, but the promising future of beyond 5G is surely necessary for the communication requirements incurred by fast growing information technology in the next decade. Among several roadmaps toward beyond 5G, wireless big data (WBD) plus artificial intelligence (AI) based communication technology, which covers physical layer, network layer and application layer, is considered as one of the most promising ways. Along with this thought, some emerging research works have been published, which further stimulate more researcher to pay more attention in this area. This paper introduces three interesting works toward this aim, which covers channel modelling, huge access, and network topology design. The channel modelling part starts with the feasible ways to apply machine learning to wireless channel modelling, and presents the prevailing methods in parameter estimation, channel multipath clustering, which is of great importance for future research. The huge access part focuses on fractal phenomenon and its possible applications in wireless networks. After introducing the basic concept, this part investigates the maximum capacity fractal D2D social networks. The network topology design part proposes an interesting topic, whose motivation is to utilize the dynamic mobility features of mobile users to decrease the wireless resource consumption in ultra dense networks (UDN). In summary, these three works are considered as promising topics in beyond 5G, which combines wireless big data analysis and may shed light on related future research.

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