Archive

  • Select all
    |
    FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Yi Fang, Wang Chen, Pingping Chen, Yiwei Tao, Mohsen Guizani
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    This paper proposes a high-throughput short reference differential chaos shift keying cooperative communication system with the aid of code index modulation, referred to as CIM-SR-DCSK-CC system. In the proposed CIM-SR-DCSK-CC system, the source transmits information bits to both the relay and destination in the first time slot, while the relay not only forwards the source information bits but also sends new information bits to the destination in the second time slot. To be specific, the relay employs an $N$-order Walsh code to carry additional ${{\log }_{2}}N$ information bits, which are superimposed onto the SR-DCSK signal carrying the decoded source information bits. Subsequently, the superimposed signal carrying both the source and relay information bits is transmitted to the destination. Moreover, the theoretical bit error rate (BER) expressions of the proposed CIM-SR-DCSK-CC system are derived over additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. Compared with the conventional DCSK-CC system and SR-DCSK-CC system, the proposed CIM-SR-DCSK-CC system can significantly improve the throughput without deteriorating any BER performance. As a consequence, the proposed system is very promising for the applications of the 6G-enabled low-power and high-rate communication.

  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Mingjun Dai, Wanru Li, Chanting Zhang, Xiaohui Lin, Bin Chen
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    To provide reliability in distributed systems, combination property (CP) is desired, where $k$ original packets are encoded into $n \geq k$ packets and arbitrary $k$ are sufficient to reconstruct all the original packets. Shift-and-add (SA) encoding combined with zigzag decoding (ZD) obtains the CP-ZD, which is promising to reap low computational complexity in the encoding/decoding process of these systems. As densely coded modulation is difficult to achieve CP-ZD, research attentions are paid to sparse coded modulation. The drawback of existing sparse CP-ZD coded modulation lies in high overhead, especially in widely deployed setting $m<k$, where $m \triangleq n-k$. For this scenario, namely, $m<k$, a sparse reverse-order shift (Rev-Shift) CP-ZD coded modulation is designed. The proof that Rev-Shift possesses CP-ZD is provided. A lower bound for the overhead, as far as we know is the first for sparse CP-ZD coded modulation, is derived. The bound is found tight in certain scenarios, which shows the code optimality. Extensive numerical studies show that compared to existing sparse CP-ZD coded modulation, the overhead of Rev-Shift reduces significantly, and the derived lower bound is tight when $k$ or $m$ approaches 0.

  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Song Bai, Qiang Li, Donghong Cai
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    Reconfigurable intelligent surface (RIS)-assisted symbiotic radio is a spectrum- and energy- efficient communication paradigm, in which an RIS performs passive beamforming to enhance active transmission, while using the electromagnetic waves from the active transmission for additional information transfer (i.e., passive transmission). In this paper, a hybrid RIS-based modulation, termed hybrid phase and code modulation (HPCM), is proposed to improve the reliability of RIS-assisted symbiotic radio. In RIS-HPCM, the RIS simultaneously performs direct sequence spread spectrum and passive beamforming on incident signals. Moreover, both the spreading code and phase offset are exploited to carry the RIS's own information. A low-complexity detector is designed, in which the receiver first detects the spreading codes and then demodulates the constellation symbols. We analyze the bit error rate (BER) performance of RIS-HPCM over Rician fading channels. BER upper bounds and approximate BER expressions are derived in closed-form for maximum-likelihood and low-complexity detectors, respectively. Simulation results in terms of BER verify the analysis and show the superiority of RIS-HPCM over the existing RIS-based modulation.

  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Ping Yang, Qin Yi, Yiqian Huang, Jialiang Fu, Yue Xiao, Wanbin Tang
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    In this paper, a powerful model-driven deep learning framework is exploited to overcome the challenge of multi-domain signal detection in space-domain index modulation (SDIM) based multiple input multiple output (MIMO) systems. Specifically, we use orthogonal approximate message passing (OAMP) technique to develop OAMPNet, which is a novel signal recovery mechanism in the field of compressed sensing that effectively uses the sparse property from the training SDIM samples. For OAMPNet, the prior probability of the transmit signal has a significant impact on the obtainable performance. For this reason, in our design, we first derive the prior probability of transmitting signals on each antenna for SDIM-MIMO systems, which is different from the conventional massive MIMO systems. Then, for massive MIMO scenarios, we propose two novel algorithms to avoid pre-storing all active antenna combinations, thus considerably improving the memory efficiency and reducing the related overhead. Our simulation results show that the proposed framework outperforms the conventional optimization-driven based detection algorithms and has strong robustness under different antenna scales.

  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Mingqian Liu, Zhaoxi Wen, Yunfei Chen, Ming Li
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    Modulation recognition becomes unreliable at low signal-to-noise ratio (SNR) over fading channel. A novel method is proposed to recognize the digital modulated signals with frequency and phase offsets over multi-path fading channels in this paper. This method can overcome the effects of phase offset, Gaussian noise and multi-path fading. To achieve this, firstly, the characteristic parameters search is constructed based on the cyclostationarity of received signals, to overcome the phase offset, Gaussian white noise, and influence caused by multi-path fading. Then, the carrier frequency of the received signal is estimated, and the maximum characteristic parameter is searched around the integer multiple carriers and their vicinities. Finally, the modulation types of the received signal with frequency and phase offsets are classified using decision thresholds. Simulation results demonstrate that the performance of the proposed method is better than the traditional methods when SNR is over 5dB, and that the proposed method is robust to frequency and phase offsets over multi-path channels.

  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Zhongjie Li, Weijie Yuan, Qinghua Guo, Nan Wu, Ji Zhang
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    Orthogonal time frequency space (OTFS) technique, which modulates data symbols in the delay-Doppler (DD) domain, presents a potential solution for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing (UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model (HMM). The empirical state evolution (SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm, we derive the update criterion for the hyperparameters through the expectation-maximization (EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.

  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Xiaoping Jin, Peng Zhang, Chuan Wan, Dingyou Ma, Yudong Yao
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    Reconfigurable intelligent surface (RIS) assisted dual-function radar communications (DFRC) system is a promising integrated sensing and communication (ISAC) technology for future 6G. In this paper, we propose a scheme of RIS-assisted DFRC system based on frequency shifted chirp spread spectrum index modulation (RDFI) for secure communications. The proposed RDFI achieves the sensing and transmission of target location information in its radar and communication modes, respectively. In both modes, the frequency-shifted chirp spread spectrum index modulation (FSCSS-IM) signal is used as the baseband signal for radar and communications, so that the signal sent by the radar also carries information. This scheme implements the RIS-assisted beamforming in the communication mode through the azimuth information of the target acquired in the radar mode, so that the signal received from the eavesdropper is distorted in amplitude and phase. In addition, this paper analyzes the radar measurement accuracy and communication security of the FSCSS-IM signal using ambiguity function and secrecy rate (SR) analysis, respectively. Simulation results show that RDFI achieves both excellent bit error rate (BER) performance and physical layer security of communications.

  • FEATURE TOPIC:SPARSITY MODULATION FOR 6G COMMUNICATIONS
    Han Hai, Si Wei, Xueqin Jiang, Yuyang Peng, Mohsen Guizani
    Abstract ( ) Download PDF ( ) HTML ( )   Knowledge map   Save

    In this paper, a differential scheme is proposed for reconfigurable intelligent surface (RIS) assisted spatial modulation, which is referred to as RIS-DSM, to eliminate the need for channel state information (CSI) at the receiver. The proposed scheme is an improvement over the current differential modulation scheme used in RIS-based systems, as it avoids the high-order matrix calculation and improves the spectral efficiency. A mathematical framework is developed to determine the theoretical average bit error probability (ABEP) of the system using RIS-DSM. The detection complexity of the proposed RIS-DSM scheme is extremely low through the simplification. Finally, simulations results demonstrate that the proposed RIS-DSM scheme can deliver satisfactory error performance even in low signal-to-noise ratio environments.

  • COMMUNICATIONS THEORIES & SYSTEMS
  • COMMUNICATIONS THEORIES & SYSTEMS
    Renjie Liang, Haiyang Lyu, Jiancun Fan
    Abstract ( )   Knowledge map   Save
    In the fifth generation (5G) wireless system, a closed-loop power control (CLPC) scheme based on deep Q learning network (DQN) is introduced to intelligently adjust the transmit power of the base station (BS), which can improve the user equipment (UE) received signal to interference plus noise ratio (SINR) to a target threshold range. However, the selected power control (PC) action in DQN is not accurately matched the fluctuations of the wireless environment. Since the experience replay characteristic of the conventional DQN scheme leads to a possibility of insufficient training in the target deep neural network (DNN). As a result, the Q-value of the sub-optimal PC action exceed the optimal one. To solve this problem, we propose the improved DQN scheme. In the proposed scheme, we add an additional DNN to the conventional DQN, and set a shorter training interval to speed up the training of the DNN in order to fully train it. Finally, the proposed scheme can ensure that the Q value of the optimal action remains maximum. After multiple episodes of training, the proposed scheme can generate more accurate PC actions to match the fluctuations of the wireless environment. As a result, the UE received SINR can achieve the target threshold range faster and keep more stable. The simulation results prove that the proposed scheme outperforms the conventional schemes.;
  • COMMUNICATIONS THEORIES & SYSTEMS
    Guangyue Lu, Zhipeng Liu, Yinghui Ye, Xiaoli Chu
    Abstract ( )   Knowledge map   Save
    This paper investigates the system outage performance of a simultaneous wireless information and power transfer (SWIPT) based two-way decode-and-forward (DF) relay network, where potential hardware impairments (HIs) in all transceivers are considered. After harvesting energy and decoding messages simultaneously via a power splitting scheme, the energy-limited relay node forwards the decoded information to both terminals. Each terminal combines the signals from the direct and relaying links via selection combining. We derive the system outage probability under independent but non-identically distributed Nakagami-m fading channels. It reveals an overall system ceiling (OSC) effect, i.e., the system falls in outage if the target rate exceeds an OSC threshold that is determined by the levels of HIs. Furthermore, we derive the diversity gain of the considered network. The result reveals that when the transmission rate is below the OSC threshold, the achieved diversity gain equals the sum of the shape parameter of the direct link and the smaller shape parameter of the terminal-to-relay links; otherwise, the diversity gain is zero. This is different from the amplify-and-forward (AF) strategy, under which the relaying links have no contribution to the diversity gain. Simulation results validate the analytical results and reveal that compared with the AF strategy, the SWIPT based two-way relaying links under the DF strategy are more robust to HIs and achieve a lower system outage probability.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Chuang Peng, Rangang Zhu, Mengbo Zhang, LunwenWang
    Abstract ( )   Knowledge map   Save
    Spectrum prediction is one of the new techniques in cognitive radio that predicts changes in the spectrum state and plays a crucial role in improving spectrum sensing performance. Prediction models previously trained in the source band tend to perform poorly in the new target band because of changes in the channel. In addition, cognitive radio devices require dynamic spectrum access, which means that the time to retrain the model in the new band is minimal. To increase the amount of data in the target band, we use the GAN to convert the data of source band into target band. First, we analyze the data differences between bands and calculate FID scores to identify the available bands with the slightest difference from the target predicted band. The original GAN structure is unsuitable for converting spectrum data, and we propose the spectrum data conversion GAN (SDC-GAN). The generator module consists of a convolutional network and an LSTM module that can integrate multiple features of the data and can convert data from the source band to the target band. Finally, we use the generated target band data to train the prediction model. The experimental results validate the effectiveness of the proposed algorithm.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Xiaojun Zhang, Chengguan Chen, Rongcai Zhang, Jianming Cui, Qingtian Zeng
    Abstract ( )   Knowledge map   Save
    To remove the restriction on code length of polar codes, this paper proposes a construction scheme, called stepwise polar codes, which can generate arbitrary-length polar codes. The stepwise polar codes are generated by sub-polar codes with different code lengths. To improve coding performance, sub-polar codes are united by polarization effect priority algorithm, which can reduce the number of incompletely polarized channels. Then, the construction method of the generator matrix of the stepwise polar code is presented. Furthermore, we prove that the proposed scheme has lower decoding complexity than punctured, multi-kernel polar codes. Simulation results show that the proposed method can achieve similar decoding performance compared with the conventional punctured polar codes, rate-compatible punctured polar code, PC-short and asymmetric polar codes (APC) when code length N=48 and 72, respectively.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Xuanhe Yang, Weike Zhang, Shixun Luo, Chang Li, Xiaqing Miao, AihuaWang
    Abstract ( )   Knowledge map   Save
    Coherent fast frequency hopping (CFFH) is attracting growing attention owing to its good anti-jamming performance and the coherent combining ability. However, compared with the conventional non-coherent fast frequency hopping, CFFH requires a more precise system synchronization. In this paper, we propose a new fine synchronization algorithm for CFFH. This algorithm consists two stages, namely, open-loop stage and closed-loop stage. In the open-loop stage, a grid-based search parameter estimation method is proposed. In the closed-loop stage, we construct a fully coherent phase-locked loop (PLL) and a delay-locked loop (DLL) with decoding feedback structure to perform further fine estimation of the system clock skew and time delay, respectively. Moreover, we analyze the effect of the search parameter settings on the estimation error and derive the root mean squared error (RMSE) of estimates in the steady state of the closed-loop stage. Finally, through simulation, the RMSE performance are compared with the corresponding Cramer-Rao low bound (CRLB) and conventional code loop estimation to show the effectiveness of proposed algorithm.
  • NETWORKS & SECURITY
  • NETWORKS & SECURITY
    Ningjie Gao, Ru Huo, ShuoWang, Jiang Liu, Tao Huang, Yunjie Liu
    Abstract ( )   Knowledge map   Save
    With the development and widespread use of blockchain in recent years, many projects have introduced blockchain technology to solve the growing security issues of the Industrial Internet of Things(IIoT). However, due to the conflict between the operational performance and security of the blockchain system and the compatibility issues with a large number of IIoT devices running together, the mainstream blockchain system cannot be applied to IIoT scenarios. In order to solve these problems, this paper proposes SBFT (Speculative Byzantine Consensus Protocol), a flexible and scalable blockchain consensus mechanism for the Industrial Internet of Things. SBFT has a consensus process based on speculation, improving the throughput and consensus speed of blockchain systems and reducing communication overhead. In order to improve the compatibility and scalability of the blockchain system, we select some nodes to participate in the consensus, and these nodes have better performance in the network. Since multiple properties determine node performance, we abstract the node selection problem as a joint optimization problem and use Dueling Deep Q Learning (DQL) to solve it. Finally, we evaluate the performance of the scheme through simulation, and the simulation results prove the superiority of our scheme.
  • NETWORKS & SECURITY
    Yi Zhang, Min Zhang, Yihan Gui, YuWang, Hong Zhu, Wenbin Chen, DanshiWang
    Abstract ( )   Knowledge map   Save
    Accurate traffic pattern prediction in large-scale networks is of great importance for intelligent system management and automatic resource allocation. System-level mobile traffic forecasting has significant challenges due to the tremendous temporal and spatial dynamics introduced by diverse Internet user behaviors and frequent traffic migration. Spatial-temporal graph modeling is an efficient approach for analyzing the spatial relations and temporal trends of mobile traffic in a large system. Previous research may not reflect the optimal dependency by ignoring inter-base station dependency or pre-determining the explicit geological distance as the interrelationship of base stations. To overcome the limitations of graph structure, this study proposes an adaptive graph convolutional network (AGCN) that captures the latent spatial dependency by developing self-adaptive dependency matrices and acquires temporal dependency using recurrent neural networks. Evaluated on two mobile network datasets, the experimental results demonstrate that this method outperforms other baselines and reduces the mean absolute error by 3.7 \% and 5.6 \% compared to time-series based approaches.
  • NETWORKS & SECURITY
    Linjie Zhang, Xiaoyan Zhu, Jianfeng Ma
    Abstract ( )   Knowledge map   Save
    The continuously booming of information technology has shed light on developing a variety of communication networks, multimedia, social networks and Internet of Things applications. However, users inevitably suffer from the intrusion of malicious users. Some studies focus on static characteristics of malicious users, which is easy to be bypassed by camouflaged malicious users. In this paper, we present a malicious user detection method based on ensemble feature selection and adversarial training. Firstly, the feature selection alleviates the dimension disaster problem and achieves more accurate classification performance. Secondly, we embed features into the multi-dimensional space and aggregate it into a feature map to encode the explicit content preference and implicit interaction preference. Thirdly, we use an effective ensemble learning which could avoid over-fitting and has good noise resistance. Finally, we propose a data-driven neural network detection model with the regularization technique adversarial training to deeply analyze the characteristics. It simplifies the parameters, obtaining more robust interaction features and pattern features. We demonstrate the effectiveness of our approach with numerical simulation results for malicious user detection, where the robustness issues are notable concerns.
  • NETWORKS & SECURITY
    Huici Wu, YangWen, Xiaofeng Tao, Jin Xu
    Abstract ( )   Knowledge map   Save
    This paper focuses on anti-jamming and anti-eavesdropping problem in air-to-ground (A2G) communication networks considering the impact of body jitter of unmanned aerial vehicle (UAV). A full-duplex (FD) active ground eavesdropper launches jamming attack while eavesdropping to stimulate the legitimate transmitter (i.e., UAV) to increase its transmission power. The legitimate transmitter's objective is to against the simultaneous wiretapping and jamming with a robust and power-efficient transmission scheme. The active eavesdropper aims to minimize the system secrecy rate. To study the interaction between the legitimate transmitter and the active eavesdropper, a non-cooperative game framework is formulated. Detailed, considering the impact of UAV jitter on antenna array response and secrecy performance, we first investigate the UAV's transmission power minimization problem for the worst scenario with minimum legitimate data rate and maximum eavesdropping data rate under UAV jitter. Then, the active eavesdropper's secrecy rate minimization problem with the worst scenario is investigated by optimizing its jamming strategy. Nash equilibrium is proved to be existed and obtained with the proposed iterative algorithm. Finally, extensive numerical results are provided to evaluate the system secrecy performance and to show the secrecy performance gains of the proposed method.;
  • NETWORKS & SECURITY
    Enyu Du, Yang Gao, Wenjun Wu, Zhaoxin Yang, Yufeng Yin, Pengbo Si
    Abstract ( )   Knowledge map   Save
    To ensure the security of resource and intelligence sharing in 6G, blockchain has been widely adopted in wireless communications and applications. Although blockchain can ensure the traceability and non-tamperability of data in the concatenated blocks, it cannot guarantee the honest behaviors of users in the application before the generation of transactions. Thus, additional technologies are required to ensure that the source of blockchain data is reliable. In this paper, the detailed procedure is designed for the application-oriented task validation in the blockchain-enhanced computing resource sharing and transactions in ultra dense networks (UDN). The corresponding queuing model is built and analyzed with the consideration of the wireless re-transmission and the probability of malicious deception by users. Based on the analysis results, the UDN deployment is optimized to save network cost while ensuring latency performance. Numerical results verify our analysis, and the optimized system deployment including the number and service capacities of both base stations and mobile edge computing (MEC) servers are also given with various system settings.
  • EMERGING TECHNOLOGIES & APPLICATIONS
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Xiangnan Liu, Haijun Zhang, Min Sheng, Wei Li, Saba Al-Rubaye, Keping Long
    Abstract ( )   Knowledge map   Save
    With the evolution of the sixth generation (6G) mobile communication technology , ample attention has gone to the integrated terrestrial-satellite networks. This paper notes that four typical application scenarios of integrated terrestrial-satellite networks are integrated into ultra dense satellite-enabled 6G networks architecture. Then the subchannel and power allocation schemes for the downlink of the ultra dense satellite-enabled 6G heterogeneous networks are introduced. Satellite mobile edge computing (SMEC) with edge caching in three-layer heterogeneous networks serves to reduce the link traffic of networks. Furthermore, a scheme for interference management is presented, involving quality-of-service (QoS) and co-tier/cross-tier interference constraints. The simulation results show that the proposed schemes can significantly increase the total capacity of ultra dense satellite-enabled 6G heterogeneous networks.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Xiangyu Liu, Jingyu Hao, Lei Guo, Song Song
    Abstract ( )   Knowledge map   Save
    In visible light positioning systems, some scholars have proposed target tracking algorithms to balance the relationship among positioning accuracy, real-time performance, and robustness. However, there are still two problems: (1) When the captured LED disappears and the uncertain LED reappears, existing tracking algorithms may recognize the landmark in error; (2) The receiver is not always able to achieve positioning under various moving statuses. In this paper, we propose an enhanced visual target tracking algorithm to solve the above problems. First, we design the lightweight recognition/demodulation mechanism, which combines Kalman filtering with simple image preprocessing to quickly track and accurately demodulate the landmark. Then, we use the Gaussian mixture model and the LED color feature to enable the system to achieve positioning, when the receiver is under various moving statuses. Experimental results show that our system can achieve high-precision dynamic positioning and improve the system's comprehensive performance.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Xiongfei Ren, Lili Tong, Jia Zeng, Chen Zhang
    Abstract ( )   Knowledge map   Save
    The explosion of ChatGPT is considered to be a milestone in the normalization of artificial intelligence education applications. On the technical line, the cross-modal AI generation application based on human feedback system is accelerated. In the business model, the scenes to realize interactive functions are constantly enriched. This paper reviews the evolution process of AIGC, closely follows the current situation of the coexistence of business acceleration and technical worries in the application of artificial intelligence education, analyzes the application of AIGC education in 7 subdivided fields, and analyzes the optimization direction of application cases from the perspective of perception-cognition-creation technology maturity matrix. The 3 recommendations and 2 follow-up research directions will promote the scientific application of artificial intelligence education in the AIGC period.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Jingjing Wang, Yanjing Sun, Bowen Wang, Shenshen Qian, Zhijian Tian, Xiaolin Wang
    Abstract ( )   Knowledge map   Save
    Unmanned aerial vehicles (UAVs) enable flexible networking functions in emergency scenarios. However, due to the movement characteristic of ground users (GUs), it is challenging to capture the interactions among GUs. Thus, we propose a learning-based dynamic connectivity maintenance architecture to reduce the delay for the UAV-assisted device-to-device (D2D) multicast communication. In this paper, each UAV transmits information to a selected GU, and then other GUs receive the information in a multi-hop manner. To minimize the total delay while ensuring that all GUs receive the information, we decouple it into three subproblems according to the time division on the topology: For the cluster-head selection, we adopt the Whale Optimization Algorithm (WOA) to imitate the hunting behavior of whales by abstracting the UAVs and cluster-heads into whales and preys, respectively; For the D2D multi-hop link establishment, we make the best of social relationships between GUs, and propose a node mapping algorithm based on the balanced spanning tree (BST) with reconfiguration to minimize the number of hops; For the dynamic connectivity maintenance, Restricted Q-learning (RQL) is utilized to learn the optimal multicast timeslot. Finally, the simulation results show that our proposed algorithms perform better than other benchmark algorithms in the dynamic scenario.