Edge Intelligence-Based RAN Architecture for 6G Internet of Things by Yang Liu, Qingtian Wang, Haitao Liu, Jiaying Zong, Fengyi Yang

“…In this study, we proposed Edge Intelligent Radio Access Network Architecture (EIRA) by introducing new intelligence modules, which include broadband edge platforms that allow policies to interact with virtualized RAN for various applications. We also developed a Markov chain-based RAN Intelligence Control (RIC) scheduling policy for allocating intelligence elements. …”
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Modeling the Impact of Virtual Contact Network with Community Structure on the Epidemic Spreading by Jianlin Zhou, Haiyan Liu

“…We first use a microscopic Markov chain approach to characterize the coupled disease-awareness dynamics and then analyze the effect of different factors on the coevolution of information dissemination and epidemic spreading based on the Monte Carlo simulation. …”
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Cracking-resistance net-flow fingerprint scheme based on multi-dimensional orthogonal carriers by Cheng LEI, Hong-qi ZHANG, Yi SUN, Xue-hui DU

“…It achieves crack-ing-resistance by interval centroid carrier characteristics and hidden Markov model based decoding technique. Ultimately, it improves the robustness of scheme. …”
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Continuous speech speaker recognition based on CNN by Zhendong WU, Shucheng PAN, Jianwu ZHANG

“…GMM-HMM (Gaussian mixture-hidden Markov model) have been the main method for speaker recognition. …”
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Analysis and Design of Networked Control Systems with Random Markovian Delays and Uncertain Transition Probabilities by Li Qiu, Chengxiang Liu, Fengqi Yao, Gang Xu

“…The resulting closed-loop system is modeled as a discrete-time Markovian delays system governed by two Markov chains. Using Lyapunov stability theory, a result is established on the Markovian structure and ensured that the closed-loop system is stochastically stable. …”
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Mean-Square Exponential Synchronization of Markovian Switching Stochastic Complex Networks with Time-Varying Delays by Pinning Control by Jingyi Wang, Chen Xu, Jianwen Feng, Man Kam Kwong, Francis Austin

“…The switching parameters are modeled by a continuous-time, finite-state Markov chain, and the complex network is subject to noise perturbations, Markovian switching, and internal and outer time-varying delays. …”
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Optimizing Breeding Strategies for Pekin Ducks Using Genomic Selection: Genetic Parameter Evaluation and Selection Progress Analysis in Reproductive Traits by Jun Zhou, Jiang-Zhou Yu, Mei-Yi Zhu, Fang-Xi Yang, Jin-Ping Hao, Yong He, Xiao-Liang Zhu, Zhuo-Cheng Hou, Feng Zhu

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Under-five mortality and its associated factors in sub-Saharan Africa: a multilevel analysis of recent demographic and health surveys data based on Bayesian approach by Atalay Liknaw Birhanie, Zemenu Tadesse Tessema, Bekalu Endalew, Koku Sisay Tamirat

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Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation by WANG Chaowei, PANG Mingliang, WANG Su, ZHAO Lingli, GAO Feifei, CUI Gaofeng, WANG Weidong

“…The continuous resource allocation process with temporal correlation was modeled as a Markov decision process, and a decision-evaluation dual-network algorithm was proposed to solve it. …”
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Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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Multiobjective Lightning Flash Algorithm Design and Its Convergence Analysis via Martingale Theory by Jiandong Duan, Jing Wang, Xinghua Liu, Gaoxi Xiao

“…The charge population state of the lightning flash algorithm is defined, and we prove that the charge population state sequence is a Markov chain. Since the convergence analysis of MOLFA is to investigate whether a Pareto optimal solution can be reached when the optimal charge population state is obtained, the development of a charge population state is analyzed to achieve the goal of this paper. …”
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Statistical Investigation of Bearing Capacity of Pile Foundation Based on Bayesian Reliability Theory by Zuolong Luo, Fenghui Dong

“…In order to improve the estimation accuracy of bearing capacity of pile foundation, a new forecast method of bearing capacity of pile foundation was proposed on Jeffrey’s noninformative prior using the MCMC (Markov chain Monte Carlo) method of the Bayesian theory. …”
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Scheduling and Resource Allocation in OFDMA Downlink Systems Using Cross-Layer Feedback by Xungong Yin, Hui Feng, Tao Yang, Bo Hu

“…The prob1em of the cross-1ayer schedu1ing and resource a11ocation in orthogona1 frequency division mu1tip1exing access （OFDMA）down1ink was considered, uti1izing the ACK/NAK in MAC 1ayer and periodic feedback of users' SNR in physica1 1ayer simu1taneous1y.This prob1em was mode1ed as a partia11y observab1e Markov decision process （POMDP）with cross-1ayer observations, and a simp1ified version was proposed to reduce the computationa1 comp1exity.Numerica1 experiments show that the performance of the a1gorithm is re1ative1y c1ose to the upper bound proposed by Aggarwa1 R, and does not increase the system overhead of feedback.…”
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A New Synergistic Forecasting Method for Short-Term Traffic Flow with Event-Triggered Strong Fluctuation by Darong Huang, Zhenping Deng, Bo Mi

“…Firstly, we constructed an improved grey Verhulst prediction model by introducing the Markov chain to its traditional version. Then, based on an introduced dynamic weighting factor, the improved grey Verhulst prediction method, and the first-order difference exponential smoothing technique, the new method for short-term traffic forecasting is completed in an efficient way. …”
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Performance of Resource Management Techniques for Weather-Impacted Satellite Networks by Olugbenga Emmanuel Imole, Tom Mmbasu Walingo

“…The proposed technique is based on three Markov models for widespread, shower, and thunderstorm rain events and predicts the attenuation experienced at different periods within the duration of a user’s connection. …”
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Method of dynamic random network coding in DTN environment by Guang-hong DENG, Wan-hua CAO, Jian ZHANG, Li FENG, Xiong CHENG

“…For working out this problem, a dynamic random network coding transfer method (DRNC) was proposed. Based on the Markov channel model, it first computed the transmit speeds of every network channel according to the receive data states of nodes, and then constructed the network flow graphic with channel capacities at the source node, calculated and forecasted the current network multicast capacity, after that, the random network coding scenario was extended and tailored according to the multicast capacity to transmit data packages under DTN environment. …”
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Rolling Bearing Remaining Useful Life Prognosis Method based on Improved CHSMM by Zhu Shuo, Bai Ruilin, Ji Feng

“…A rolling bearing remaining useful life prognostics method based on improved Continuous hidden semi-Markov model（ CHSMM） is proposed,aiming at the problem that the CHSMM algorithm prognostics accuracy is low for remaining useful life of rolling bearings. …”
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Discovering and Characterizing Hidden Variables Using a Novel Neural Network Architecture: LO-Net by Soumi Ray, Tim Oates

“…Two different regularization terms are explored that improve the network's ability to approximate the values of hidden variables, and the performance and capabilities of the network are compared to that of Hidden Markov Models.…”
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Reliability Modeling for Multistate System with Preventive Maintenance under Customer Demand by Jinlei Qin, Zheng Li

“…According to the regular degradation and random failure at each state, based on the Markov random process, the proposed MSS with preventive maintenance can be modeled to satisfy the customer demand in a specific state. …”
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Communication performance analysis of secondary users in cognitive radio networks under primary user emulation attacks by Shan-shan WANG, Xing-guo LUO, Peng LI

“…Cognitive radio network(CRN)is an effective technology and a hot research direction which could solve the problem of deficient resource and revolutionize utilization.And its safety technology attracted more and more researches.Primary user emulation(PUE)is a typically easily and largely affecting attack.PUE attacked come from both malicious misbehavior secondary users(MMU)and selfish misbehavior secondary users(SMU).The former was studied much more deeply than the later one.Distinguishing MMU and SMU,a four dimensional continuous time markov chain model to analyze the communication performance of normal secondary users under PUE attacks,and typically affected by SMUs was proposed.Furthermore,several PUE detection technologies were compared.The emulation results indicate that the SMU detection mechanism is essential for the PUE attack detection technology,which can improve the detection effects largely.…”
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