Controller area networks (CANs), as one of the widely used fieldbuses in the industry, have been extended to the automation field with strict standards for safety and reliability. In practice, factors such as fatigue and insulation wear of the cables can cause intermittent connection (IC) faults to occur frequently in the CAN, which will affect the dynamic behavior and the safety of the system. Hence, quantitatively evaluating the performance of the CAN under the influence of IC faults is crucial to real-time health monitoring of the system. In this paper, a novel methodology is proposed for real-time quantitative evaluation of CAN availability when considering IC faults, with the system availability parameter being calculated based on the network state transition model. First, the causal relationship between IC fault and network error response is constructed, based on which the IC fault arrival rate is estimated. Second, the states of the network considering IC faults are analyzed, and the deterministic and stochastic Petri net (DSPN) model is applied to describe the transition relationship of the states. Then, the parameters of the DSPN model are determined and the availability of the system is calculated based on the probability distribution and physical meaning of markings in the DSPN model. A testbed is constructed and case studies are conducted to verify the proposed methodology under various experimental setups. Experimental results show that the estimation results obtained using the proposed method agree well with the actual values.

Since the introduction of fifth-generation new radio (5G-NR) in Third Generation Partnership Project (3GPP) Release 15, swift progress has been made to evolve 5G with 3GPP Release 18 emerging. A critical aspect is the design of massive multiple-input multiple-output (MIMO) technology. In this line, this paper makes several important contributions: We provide a comprehensive overview of the evolution of standardized massive MIMO features from 3GPP Release 15 to 17 for both time/frequency-division duplex operation across frequency range in (FR)-1 and FR 2-1. We analyze the progress on channel state information (CSI) frameworks, beam management frameworks and present enhancements for uplink CSI. We shed light on emerging 3GPP Release 18 problems requiring imminent attention. These include advanced codebook design and sounding reference signal design for coherent joint transmission (CJT) with multiple transmission/reception points (multi TRPs). We discuss advancements in uplink demodulation reference signal design, enhancements for mobility to provide accurate CSI estimates, and unified transmission configuration indicator framework tailored for FR 2–1 bands. For each concept, we provide system level simulation results to highlight their performance benefits. Via field trials in an outdoor environment at Shanghai Jiaotong University, we demonstrate the gains of multi-TRP CJT relative to single TRP at 3.7 GHz.

Controller area network (CAN) is a widely used fieldbus protocol in various industrial applications. To understand the network behavior under errors for the optimal design of networked control systems, the message response time of the CAN network needs to be analyzed. In this study, a novel delay time distribution analysis method for the response messages is proposed when considering errors. In this method the complex message queues are decomposed into typical message patterns and cases. First, a stochastic fault model is developed, and the probability factor is defined to calculate the error distribution. Then the message delay time distribution for the single slave node configuration is analyzed based on the error distribution. Next, based on the delay time distribution analysis of typical patterns and cases, an analysis framework of message delay time distribution for the master/slave configuration is developed. The testbed is constructed and case studies are conducted to demonstrate the proposed methodology under different network configurations. Experimental results show that the delay time distributions calculated by the proposed method agree well with the actual observations

Controller area network (CAN) based fieldbus technologies have been widely used in networked manufacturing systems. As the information channel of the system, the reliability of the network is crucial to the system throughput, product quality, and work crew safety. However, due to the inaccessibility of the nodes’ internal states, direct assessment of the reliability of CAN nodes using the nodes’ internal error counters is infeasible. In this paper, a novel CAN node reliability assessment method, which uses node’s time to bus-off as the reliability measure, is proposed. The method estimates the transmit error counter (TEC) of any node in the network based on the network error log and the information provided by the observable nodes whose error counters are accessible. First, a node TEC estimation model is established based on segmented Markov chains. It considers the sparseness of the distribution of the CAN network errors. Second, by learning the differences between the model estimates and the actual values from the observable node, a Bayesian network is developed for the estimation updating mechanism of the observable nodes. Then, this estimation updating mechanism is transferred to general CAN nodes with no TEC value accessibility to update the TEC estimation. Finally, a node reliability assessment method is developed to predict the time to reach bus-off state of the nodes. Case studies are carried out to demonstrate the effectiveness of the proposed methodology. Experimental results show that the estimates using the proposed model agree well with actual observations.

Massive multiple-input-multiple-Output (Massive MIMO) is recognized as a promising technology to improve the system spectral efficiency by exploiting the massive degrees of freedom in spatial domain. However, in Massive MIMO systems, accurate channel state information (CSI) is required at transmitter, which corresponds to huge overhead of CSI measurement and feedback. In this paper, we propose a novel CSI measurement and feedback scheme to reduce the overhead in massive MIMO systems. Specifically, we propose a hierarchical CSI measurement and feedback scheme, which is comprised of two stages. At the first stage, partial CSI is measured and fed back to the transmitter. At the second stage, with the partial CSI, precoded CSI is measured and fed back. With the proposed scheme, the overhead of both CSI measurement and feedback can be significantly reduced. In addition, the analyses of CSI overhead and CSI distortion of the proposed scheme are also provided and verified by the numerical results.

This study deals with the problem of robust H ∞ finite‐time boundedness analysis and design of finite‐time H ∞ feedback control for discrete switched systems. By using sojourn probability information, a new kind of switched system model is proposed. Based on this model, sufficient conditions for the H ∞ finite‐time boundedness are obtained by using Lyapunov functional method and the corresponding controllers are also designed. Moreover, when considering partially known probabilities and unknown system uncertainties, the analysis and design methods are also given. Finally, an example is given to illustrate the efficiency of the proposed method.

Interference alignment (IA) has been well recognized as an efficient approach to reduce interference at high signal to noise ratio (SNR). However, it demands global channel state information (CSI) at both transmitters and receivers for preceder design in order to maximize the multiplexing gain. In this paper, we discuss IA with delayed differential CSI feedback for time-correlated multiple input multiple output (MIMO) block fading channels. We consider the impact of distortion caused by channel estimation errors and quantized CSI feedback delay, and thus, find an optimal feedback interval to minimize this distortion, as well as the sum rate performance. Specifically, we derive the minimum differential feedback rate. And with the feedback-channel capacity constraint, we further study the relationship between the average sum rate and the feedback interval. Analytical results are verified by simulations.

In this paper, we investigate the differential channel state information (CSI) feedback problem for a general multiple input multiple output (MIMO) system over time-correlated Rayleigh block-fading channels. Specifically, we derive the closed-form minimum differential feedback rate in the presence of channel estimation errors and quantization distortion. With the feedback-channel capacity constraint, we further study the ergodic capacity in a periodic feedback system in terms of the minimum differential feedback rate and the feedback interval. Through theoretical analysis, we find that there exists an optimal differential feedback interval to achieve the maximum ergodic capacity. Analytical results are verified by simulations in a practical periodic differential feedback system employing water-filling precoder and Lloyd's quantization algorithm.

Interference alignment (IA) has been well recognized as a promising technique to obtain large multiplexing gain in multiple input multiple output (MIMO) interference channels. Most of the existing IA schemes require global channel state information (CSI) at the transmitter to design precoding vectors, which causes high amount of feedback bits. To reduce the feedback overhead, in this paper, we investigate the IA scheme employing differential CSI feedback over time-correlated MIMO channels. Specifically, we analyze the achievable sum-rate performance, and derive the minimum differential feedback rate to preserve the maximum multiplexing gain. In addition, we use the general alternating-minimization precoder design scheme to verify the analytical results.

In this paper, we investigate the differential channel state information (CSI) feedback problem for a general multiple input multiple output(MIMO) system over time-correlated Rayleigh block-fading channels. Specifically, we first derive the analytical minimum differential feedback rate in the presence of channel estimation errors and quantization distortion. With the feedback-channel capacity constraint, in the periodic feedback system, we further study the relationship between the ergodic capacity and the feedback interval. We find that there exists an optimal feedback interval to maximize the ergodic capacity. Analytical results are verified by simulations in a practical differential feedback system employing Lloyd's quantization algorithm.

Over the last few years, Flickr has gained massive popularity and groups in Flickr are one of the main ways for photo diffusion. However, the huge volume of groups brings troubles for users to decide which group to choose. In this paper, we propose a tensor decomposition-based group recommendation model to suggest groups to users which can help tackle this problem. The proposed model measures the latent associations between users and groups by considering both semantic tags and social relations. Experimental results show the usefulness of the proposed model.