To provide reliable real-time control in the centralized CAV control system is challenging due to the dependency on channel conditions during the transmission of control commands. The transmission delay and packet loss may significantly impair the control performance. In this work, we aim to provide real-time communications and reliable control for a centralized CAV control network, where a joint packetized predictive control (PPC) and open-loop communications (OLC) scheme is proposed. A mathematical framework is developed to analyze the communication and control performance of the proposed scheme. The Pareto Frontier to balance the spectrum efficiency (SE) and Age of Information (AoI) is achieved using the Nondominated Sorting Genetic Algorithm II (NSGA-II).

This paper investigates a bi-static integrated sensing and communication (ISAC) system for multi-target scenarios using impulse radio ultra-wideband (IR-UWB) signals, which offer fine temporal resolution, low power consumption, and strong resistance to multipath interference. Two typical modulation schemes, namely pulse position modulation (PPM) and binary phase shift keying (BPSK), are considered for communication over the delay and phase domains, respectively. An innovative differential decoupling strategy is proposed, which eliminates the need for pilot symbols by leveraging the known starting symbol position. The sensing performance under various modulation and demodulation schemes is analyzed and compared with the conventional pilot-based (time-delay) decoupling strategy under current UWB standards. A key contribution of this work is the development of a unified analytical framework based on the Fisher information matrix (FIM), which characterizes the fundamental coupling between communication and sensing in both delay and Doppler domains. This coupling is examined through the singularity structure of the FIM, providing new insights into the joint performance limits of UWB-ISAC systems. Performance evaluation is conducted using the Cramer-Rao Lower Bound (CRLB) for sensing and the data transmission rate for communication, offering theoretical insights into choosing suitable data signal processing methods in real-world applications.

Due to the advantages in hardware implementation and spectrum efficiency, the integration of sensing and commu-nications (ISAC) has been attractive so far. In this paper, the inherent tradeoffs between sensing and communications (S&C) in frequency division multiplexing and waveform integration systems are analyzed, based on the high time resolution impulse radio ultra wideband (IR-UWB) signals. More specifically, we introduce two resource allocation schemes from the power and bandwidth perspective, to show the corresponding performance metrics including the Cramer Rao Bound (CRB) and Shannon limits for S&C. Lastly, the latest UWB standards are introduced as constraints, to perform evaluations.

Ultra wideband (UWB) systems have received great interest again due to the high range resolution, flexible data transmission capability, and low power consumption. In this paper, we develop a practical asynchronous integrated sensing and communication (ISAC) system using impulse radio UWB signals. This system operates within a joint mono-bistatic sensing network, accommodating multiple static and dynamic targets. To achieve simultaneous communication and target sensing, a reliable soft information based decouple solution is proposed to perform data demodulation in the typical UWB modulation waveforms. The data transmission can benefit from proper channel sensing, to about 2-3 dB gain, by exploiting the multipath components for demodulation. In addition to the demodulated data bits at the bi-static receiver, the environmental target distance and Doppler shift can also be achieved at both mono- and bi-static receivers, respectively. We then evaluate the sensing capability of the ISAC UWB system, by extensive simulations and practical experiments. The target tracking accuracy can be achieved within 20 cm at over 80% confidence, with commercial UWB devices according to practical measurements.

In this paper, we construct a totally asynchronous integrated sensing and communication (ISAC) system using impulse radio ultra-wideband (IR-UWB) signals. In a typical bistatic network in the presence of several static and dynamic targets, both line-of-sight (LOS) and multi-path components (MPCs) are considered. The transmitted data symbols demodulation and the Doppler measurement of targets within the environment could be achieved simultaneously, using a low complexity sequential estimation algorithm. In addition, the data transmission could achieve about 1.5 dB gain from the channel sensing, due to the fact that the extra MPC energy could be collected for data demodulation in this framework.

The integrated sensing and communication (ISAC) where both sensing and communication may share resources from multiple domains, has become a key point in future 6G wireless networks. One fundamental problem to ISAC is to discuss the essential tradeoff between sensing and communications. In this paper, we try to exploit this issue using the estimation theory, since transmitted symbols and channel characterizations are essentially unknown parameters to be jointly estimated. The Fisher information matrix (FIM) and Cramer Rao lower bound (CRB) are both used to give the ISAC performance benchmarks. The impulse radio ultra wideband (IR-UWB) signals are adopted for the case study. We first give the general models on the UWB ISAC system. We then compare the CRBs of sensing only, to ISAC systems, to illustrate the information coupling between sensing and communications. After proper decoupling operations such as pilots, we can see the inevitable performance degradation in ISAC, where uncertainties are essentially introduced by transmitted symbols. Furthermore, we also perform the energy optimization between pilots and data bits, to verify the tradeoff between sensing and communications.

Ultra wideband (UWB) signals, with their high time resolution, large bandwidth, and low energy consumption, hold great promise as candidates for future integrated sensing and communication (ISAC) systems. In this article, we attempt to explore the tradeoff between communication and sensing by estimating the unknown parameters of transmitted symbols and channel characteristics. We utilize the Fisher Information Matrix (FIM) and Cramr-Rao Bound (CRB) to quantify the performance. Firstly, due to the coupling between channel parameters and transmitted symbols, a differential decoupling approach is proposed. Subsequently, we conducted a comparative analysis of sensing performance across various decoupling methods. We can see that the transmitted symbols have noticeable degrading effects under typical channel parameters. Numerical results are provided, to show the decouple performance degradation on different decoupling schemes.

Due to the high time resolution, large bandwidth and low energy consumption, impulse radio ultra wideband (IRUWB) signals have been promising candidates for the forthcoming integrated sensing and communication (ISAC) systems. In this paper, we employ the parameter estimation theory as a methodology to demonstrate the inherent interdependence between channel parameters and transmitted symbols. Specifically, we introduce the Equivalent Fisher Information Matrix (EFIM) to show the implicit coupling between these two functions. According to proper decoupling operations such as pilots, we can see that the estimation performance of typical channel parameters, such as the propagation delay and Doppler shift of every multipath component (MPC) will be evidently degraded due to the unknown transmitted symbols. Finally, the influence on sensing performance of two main stream IR-UWB signal modulation schemes-the pulse position modulation (PPM) and binary phase shift keying (BPSK) in the ISAC system are then evaluated for decoupling analysis.

Integrated communication and localization (ICAL) is of significant importance for a variety of applications in beyond 5G and 6G networks. Meanwhile, strict and high-precision clock synchronization is difficult to realize in realistic networks. This paper proposes two decoupling strategies for asynchronous ICAL networks in which positioning can be realized with phase modulated symbols. We first illustrate the coupling relationship between communication and localization based on Cramer-Rao lower bound (CRLB) and then pilot-based and differential-based decoupling strategies are given. Furthermore, we analyze the localization performance between positioning-only and ICAL signals. Simulations show that the proposed strategies are able to simultaneously achieve reliable data transmission and accurate localization.

Proper resource allocation can improve the positioning accuracy, as well as the energy efficiency of wireless localization networks. Most existing investigations are carried out based on the Cramer Rao Lower Bound (CRLB), which is not always achievable, especially in low signal to noise ratio (SNR) regimes. In this paper, we mainly focus on the mean square error (MSE) achieved directly from various localization algorithms. Due to the fact that, MSE can not be handled in a closed form, learning based frameworks are thus provided. Aiming at the exponential increased state space in the multi-agent-scenario, low complexity alternating solutions are provided. In addition, a robust scheme is given considering the measurement error, which provide the solution for ranging links with clock deviation or obstruction. Numerical results including both simulations and practical experiments validate our analysis, and show great improvements of the proposed frameworks.