Communication Co-design Research Articles

Smart Sensing and Communication Co-Design for IIoT-Based Control Systems

Smart Sensing and Communication Co-Design for IIoT-Based Control Systems

LDM-Enhanced Computation and Communication Co-Design in Unmanned Aerial Vehicle Networks

LDM-Enhanced Computation and Communication Co-Design in Unmanned Aerial Vehicle Networks

Lifetime Reliability Aware Distributed Estimation and Communication Co-Design for IIoT Systems

Lifetime Reliability Aware Distributed Estimation and Communication Co-Design for IIoT Systems

Periodic Event-Triggered CACC and Communication Co-design for Vehicle Platooning

Cooperative Adaptive Cruise Control (CACC) based vehicle platooning can increase the safety and efficiency of traffic. This work looks into the communication and control problems of vehicle platooning, and proposes a control and communication co-design for CACC. First, an integrated radar system is presented. This system integrates sensing of relative position, speed, and communication between a predecessor and its follower. Second, a working scheme for the integrated radar system is presented. This scheme allows the radar systems to switch periodically between different working modes without interferences from other modes. Therefore, the relative position, speed, and communication can be asynchronously periodically updated to the controller. Third, a periodic event-triggered control approach is presented. This approach allows asynchronous periodic sampling of the output, and is deeply co-designed with the radar system and its working scheme. Delays are also considered in the control approach. The co-design CACC approach can guarantee the vehicle platoons to be string stable. A numerical example has shown the feasibility of the approach.

Task-Oriented Prediction and Communication Co-Design for Haptic Communications

Prediction has recently been considered as a promising approach to meet low-latency and high-reliability requirements in long-distance haptic communications. However, most of the existing methods did not take features of tasks and the relationship between prediction and communication into account. In this paper, we propose a task-oriented prediction and communication co-design framework, where the reliability of the system depends on prediction errors and packet losses in communications. The goal is to minimize the required radio resources subject to the low-latency and high-reliability requirements of various tasks. Specifically, we consider the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">just noticeable difference</i> (JND) as a performance metric for the haptic communication system. We collect experiment data from a real-world teleoperation testbed and use <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">time-series generative adversarial networks</i> (TimeGAN) to generate a large amount of synthetic data. This allows us to obtain the relationship between the JND threshold, prediction horizon, and the overall reliability including communication reliability and prediction reliability. We take 5G New Radio as an example to demonstrate the proposed framework and optimize bandwidth allocation and data rates of devices. Our numerical and experimental results show that the proposed framework can reduce wireless resource consumption up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$77.80\%$</tex-math></inline-formula> compared with a task-agnostic benchmark.

Input to state stabilization of networked systems under a specified packet dropout rate

This paper studies an input to state stabilizing control of networked control systems (NCSs) under a specified packet dropout rate. By considering packet dropouts in the NCSs, the transmission intervals are categorized by small delay intervals (packet-dropout-free case) and large delay intervals (packet-dropout case). Based on such classifications, we establish the concept of average packet dropout rate (ADR) to characterize the quality of service (QoS) for networks. Then, a switched systems approach is used to derive the ISS (input to state stability) conditions by exploiting Lyapunov theory and input delay approach for a specified ADR. In what follows, the controller design method for the NCSs under a specified ADR is reached by solving linear matrix inequalities (LMIs). According to the proposed results, a control and communication co-design method is developed such that one can design the controller gain according to QoS. Finally, simulations on self-steering control of autonomous vehicles are presented to verify the effectiveness of the proposed co-design method.

An overview on integrated localization and communication towards 6G

while the fifth generation (5G) cellular system is being deployed worldwide, researchers have started the investigation of the sixth generation (6G) mobile communication networks. Although the essential requirements and key usage scenarios of 6G are yet to be defined, it is believed that 6G should be able to provide intelligent and ubiquitous wireless connectivity with Terabits per second (Tbps) data rate and sub-millisecond (sub-ms) latency over three-dimensional (3D) network coverage. To achieve such goals, acquiring accurate location information of the mobile terminals is becoming extremely useful, not only for location-based services but also for improving wireless communication performance in various ways such as channel estimation, beam alignment, medium access control, routing, and network optimization. On the other hand, the advancement of communication technologies also brings new opportunities to greatly improve the localization performance, as exemplified by the anticipated centimeter-level localization accuracy in 6G by extremely large-scale multiple-input multiple-output (MIMO) and millimeter wave (mmWave) technologies. In this regard, a unified study on integrated localization and communication (ILAC) is necessary to unlock the full potential of wireless networks for dual purposes. While there are extensive studies on wireless localization or communications separately, the research on ILAC is still in its infancy. Therefore, this article aims to give a tutorial overview on ILAC towards 6G wireless networks. After a holistic survey on wireless localization basics, we present the state-of-the-art results on how wireless localization and communication inter-play with each other in various network layers, together with the main architectures and techniques for localization and communication co-design in current two-dimensional (2D) and future 3D networks with aerial-ground integration. Finally, we outline some promising future research directions for ILAC.

UAV Trajectory and Communication Co-Design: Flexible Path Discretization and Path Compression

The performance optimization of UAV communication systems requires the joint design of UAV trajectory and communication efficiently. To tackle the challenge of infinite design variables arising from the continuous-time UAV trajectory optimization, a commonly adopted approach in the existing literature is by approximating the UAV trajectory with piecewise-linear path segments connected via a finite number of waypoints in three-dimensional (3D) space. However, this approach may still incur prohibitive computational complexity in practice when the UAV flight period/distance becomes long, as the distance between consecutive waypoints needs to be kept sufficiently small to retain high approximation accuracy. To resolve this fundamental issue, we propose in this paper a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">new</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">general</i> framework for UAV trajectory and communication co-design with flexible number of waypoint optimization variables (called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">designable</i> waypoints) or their <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sub-path</i> representations. First, we propose a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">flexible path discretization</i> scheme that optimizes only a number of selected waypoints (designable waypoints) along the UAV path for complexity reduction, while all the designable and non-designable waypoints are used in calculating the approximated communication utility along the UAV trajectory for ensuring high trajectory discretization accuracy. Next, we propose a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">path compression</i> scheme, which treats the UAV trajectory as a signal and compresses its path representation based on the basis decomposition. Specifically, the UAV 3D path is first decomposed into three one-dimensional (1D) sub-paths and each sub-path is then approximated by superimposing a number of selected basis paths (which are generally less than the number of designable waypoints) weighted by their corresponding path coefficients, thus further reducing the path design complexity. Finally, we provide a case study on UAV trajectory design for aerial data harvesting from distributed sensors, and numerically show that the proposed flexible path discretization and path compression schemes can significantly reduce the UAV trajectory design complexity yet achieve favorable rate performance as compared to conventional path/time discretization schemes.

Predictive Control and Communication Co-Design via Two-Way Gaussian Process Regression and AoI-Aware Scheduling

This article studies the joint problem of uplink-downlink scheduling and power allocation for controlling a large number of control systems that upload their states to remote controllers and download control actions over wireless links. To overcome the lack of wireless resources, we propose a machine learning-based solution, where only one control system is controlled, while the rest of the control systems are actuated by locally predicting the missing state and/or action information using the previous uplink and/or downlink receptions via a Gaussian process regression (GPR). This GPR prediction credibility is determined using the age-of-information (AoI) of the latest reception. Moreover, the successful reception is affected by the transmission power, mandating a co-design of the communication and control operations. To this end, we formulate a network-wide minimization problem of the average AoI and transmission power under communication reliability and control stability constraints. To solve the problem, we propose a dynamic control algorithm using the Lyapunov drift-plus-penalty optimization framework. Numerical results corroborate that the proposed algorithm can stably control <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times$ </tex-math></inline-formula> more number of actuators compared to an event-triggered scheduling baseline with Kalman filtering and frequency division multiple access, which is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$18\times$ </tex-math></inline-formula> larger than a round-robin scheduling baseline.

Control Communication Co-Design for Wide Area Cyber-Physical Systems

Wide Area Cyber-Physical Systems (WA-CPSs) are a class of control systems that integrate low-powered sensors, heterogeneous actuators, and computer controllers into large infrastructure that span multi-kilometre distances. Current wireless communication technologies are incapable of meeting the communication requirements of range and bounded delays needed for the control of WA-CPSs. To solve this problem, we use a Control Communication Co-design approach for WA-CPSs, that we refer to as the C 3 approach, to design a novel Low-Power Wide Area (LPWA) MAC protocol called Ctrl-MAC and its associated event-triggered controller that can guarantee the closed-loop stability of a WA-CPS. This is the first article to show that LPWA wireless communication technologies can support the control of WA-CPSs. LPWA technologies are designed to support one-way communication for monitoring and are not appropriate for control. We present this work using an example of a water distribution network application, which we evaluate both through a co-simulator (modeling both physical and cyber subsystems) and testbed deployments. Our evaluation demonstrates full control stability, with up to 50% better packet delivery ratios and 80% less average end-to-end delays when compared to a state-of-the-art LPWA technology. We also evaluate our scheme against an idealised, wired, centralised, control architecture, and show that the controller maintains stability and the overshoots remain within bounds.

Sensing and Communication Co-Design for Status Update in Multiaccess Wireless Networks

The sensing and communication layers are both integral parts of the Internet-of-Things. Most of recent studies on sensory status update treat the information sensing and sensory data communication problems separately (i.e., a decoupled approach) and optimize specific latency metrics such as age of information relying on simplified models of communication networks or sensory traffic. In this paper, we propose a deeply integrated sensing and communication scheduling (S2) framework based on status-error-triggered update, focusing specifically on multiaccess wireless networks. We first analyze a motivating example consisting of two-state Markov sensors, showing that when both optimized, S2 outperforms the decoupled approach significantly. For sensors with random-walk state transitions, the closed-form Whittle's index with arbitrary status tracking error functions is presented and the indexability is established. Furthermore, a mean-field approach is applied such that the decentralized status update medium access control design is solved explicitly, for both homogeneous nodes and heterogeneous nodes in terms of status transition behaviors. According to the numerical results, the performance of the proposed S2 scheme is close to the optimum and better than the decoupled approach. In addition, a potential application of dynamic Channel State Information (CSI) update is presented, with CSI generated by a commercial ray-tracing simulator.

AoI-Aware Control and Communication Co-Design for Industrial IoT Systems

A mass of data generated by the widespread smart devices is transmitted through wireless communication networks for estimation and control in the Industrial-Internet-of-Things (IIoT) systems. The frequent data transmission needs to meet the high reliability and real-time demand of IIoT applications because the freshness of status updates influences the system performance. In this work, we use the Age of Information (AoI) to characterize the information freshness since it is a powerful metric to capture the randomness of state updates. Meanwhile, AoI is very useful in the control and communication co-design to improve the control performance considering communication disturbance. In order to analyze the control cost, we first derive the specific expression average AoI under the packet loss with finite retransmission times. Then, we investigate the influence of average AoI on control performance and obtain the joint cost combining communication energy consumption and control cost. According to the certainty equivalent principle, we design the optimal control law separately. Besides, we prove that the optimal joint infinite horizon cost is bounded by the linear function of average AoI. The communication policy, including the data interarrival rate and code length, is designed by optimizing the mixed-integer nonlinear programming (MINP) problem. Finally, simulation results reveal that, by employing the optimal data interarrival rate and code length, the joint control and communication cost is significantly reduced.

Minimal Feedback Optimal Control of Linear-Quadratic-Gaussian Systems: No Communication is also a Communication

We consider a linear-quadratic-Gaussian optimal control problem where the sensor and the controller are remotely connected over a communication channel. The communication of the measurement from the sensor to the controller requires a certain cost which is augmented with the quadratic control cost. We formulate a control and communication co-design problem where we solve for the joint optimal pair of controller and transmitter. We emphasize on the fact that absence of measurement communication at any time instance also conveys certain information to the controller, and such implicit information should be taken into account while designing a controller. We decompose the problem into two subproblems to construct the optimal controller and the optimal transmitter. While the optimal controller can be constructed by solving a certain Riccati equation, the optimal transmitter can be found solving a certain dynamic programming problem. We first characterize a sub-optimal solution for this dynamic program and then design an iterative algorithm to further improve the sub-optimal solution.

Prediction and Communication Co-Design for Ultra-Reliable and Low-Latency Communications

Ultra-reliable and low-latency communications (URLLC) are considered as one of three new application scenarios in the fifth generation cellular networks. In this work, we aim to reduce the user experienced delay through prediction and communication co-design, where each mobile device predicts its future states and sends them to a data center in advance. Since predictions are not error-free, we consider prediction errors and packet losses in communications when evaluating the reliability of the system. Then, we formulate an optimization problem that maximizes the number of URLLC services supported by the system by optimizing time and frequency resources and the prediction horizon. Simulation results verify the effectiveness of the proposed method, and show that the tradeoff between user experienced delay and reliability can be improved significantly via prediction and communication co-design. Furthermore, we carried out an experiment on the remote control in a virtual factory, and validated our concept on prediction and communication co-design with the practical mobility data generated by a real tactile device.

Network Association in Machine-Learning Aided Cognitive Radar and Communication Co-Design

In order to beneficially exploit the scarce wireless spectral resources, spectrum sharing between communication and radar systems has become a promising research topic. However, traditional network association strategies may not result in efficient hybrid communication and radar systems. We circumvent this problem by formulating a partially observable Markov decision processes (POMDP) aided network association scheme, where the radar user acts as the primary user (PU), while the cognitive communication user is the secondary user (SU). For maximizing the network throughput, whilst minimizing the interference imposed on the radar user, the communication user is configured for adaptively selecting its underlay or overlay access mode. Moreover, a low-complexity near-optimal reinforcement learning algorithm is proposed for the co-design by considering both its complexity and feasibility. Finally, we quantify the performance of our proposed POMDP based network association scheme.

Analysis and Design of Actuation–Sensing–Communication Interconnection Structures Toward Secured/Resilient LTI Closed-Loop Systems

This paper considers the analysis and design of resilient/robust decentralized control systems. Specifically, we aim to assess how the pairing of sensors and actuators lead to architectures that are resilient to attacks/hacks for industrial control systems and other complex cyber-physical systems. We consider inherent structural properties such as internal fixed modes of a dynamical system depending on actuation, sensing, and interconnection/communication structure for linear discrete time-invariant dynamical systems. We introduce the notion of a resilient fixed-modes free system that ensures the nonexistence of fixed modes when the actuation–sensing–communication structure is compromised due to attacks by a malicious agent on actuators, sensors, or communication components and natural failures. Also, we provide a graph-theoretical characterization for the resilient structurally fixed modes that enables to capture the nonexistence of resilient fixed modes for almost all possible systems’ realizations. Additionally, we address the minimum actuation–sensing–communication codesign ensuring the nonexistence of resiliently structurally fixed modes, which we show to be NP-hard. Notwithstanding, we identify conditions that are often satisfied in engineering settings and under which the codesign problem is solvable in polynomial-time complexity. Furthermore, we leverage the structural insights and properties to provide a convex optimization method to design the gain for a parameterized system and satisfying the sparsity of a given information pattern. Thus, exploring the interplay between structural and nonstructural systems to ensure their resilience. Finally, the efficacy of the proposed approach is demonstrated on a power grid example.

Toward Ultrareliable Low-Latency Communications: Typical Scenarios, Possible Solutions, and Open Issues

Ultrareliable low-latency communications (URLLC) is one of three emerging application scenarios in 5G new radio (NR) for which physical layer design aspects have been specified. With 5G NR, we can guarantee reliability and latency in radio access networks. However, for communication scenarios where the transmission involves both radio access and wide-area core networks, the delay in radio access networks contributes to only a portion of the end-toend (E2E) delay. In this article, we outline the delay components and packet loss probabilities in typical URLLC scenarios and formulate the constraints on E2E delay and overall packet loss probability. Then, we summarize possible solutions in the physical, link, and network layers as well as the cross-layer design. Finally, we discuss open issues in prediction and communication codesign for URLLC in wide-area, largescale networks.

Selective strong structural minimum-cost resilient co-design for regular descriptor linear systems

This paper addresses the problem of minimum-cost resilient actuation–sensing–communication co-design for regular descriptor systems ensuring selective (i.e., under uncertain zero, non-zero and possible zero parameters) strong structural system’s properties. Towards this goal, we extend the strong structural systems’ theory to cope with the selective structure that captures resiliency properties and uncertainty properties of regular descriptor system’s model. We provide necessary and sufficient conditions for this property to hold and show how these conditions can be leveraged to determine the minimum-cost resilient placement of actuation–sensing–communication technology ensuring feasible solutions. Finally, we illustrate the applicability of the main findings on an electric power grid example.

Control and communication co-design: Analysis and practice on performance improvement in distributed measurement and control system based on fieldbus and Ethernet

In this paper, improving control performance of a networked control system by reducing DTD in a different perspective was investigated. Two different network architectures for system implementation were presented. Analysis and improvement dealing with DTD for the experimental control system were expounded. Effects of control scheme configuration on DTD in the form of FB were investigated and corresponding improvements by reallocation of FB and re-arrangement of schedule table are proposed. Issues of DTD in hybrid network were investigated and corresponding approaches to improve performance including (1) reducing DTD in PLC or PAC by way of IEC61499 and (2) cascade Smith predictive control with BPNN-based identification were proposed and investigated. Control effects under the proposed methodologies were also given. Experimental and field practices validated these methodologies.

An Online Optimization Approach for Control and Communication Codesign in Networked Cyber-Physical Systems

Networked cyber-physical systems (NCPS), where control and communication are closely integrated, have been envisioned to have a large number of high-impact applications. In this paper, a joint optimization framework is presented, which combines the objective of control as well as other relevant system objectives and constraints such as communication errors, delays and the limited capabilities (e.g., energy capacities) of devices. The problem is solved by an online optimization approach, which consists of a communication protocol and a simulated annealing based control algorithm. Meanwhile, by taking into account the communication cost, we optimize the control intervals by integrating two kinds of acceptances, i.e., cyber and physical acceptances, into the control algorithm. Numerical results show the effectiveness of the proposed approach.