The evolution of industrial intelligent manufacturing necessitates wireless communication systems capable of replacing conventional wired infrastructures, offering superior flexibility, scalability, and reduced maintenance overhead. While 5 G New Radio (NR) Ultra-Reliable Low-Latency Communication (uRLLC) standards (Release 15-17) have shown promise for mission-critical applications, current implementations remain constrained by their unidirectional optimization paradigm, unable to simultaneously satisfy the dual imperatives of sub-millisecond latency ($\lt 1$ms) and 99.9999% reliability demanded by industrial control systems. To address these challenges, we present a transformative subband full-duplex (SBFD) network architecture that ensures persistent time-domain spectral availability for concurrent uplink/downlink operations, thereby eliminating direction-switching latency. Our solution introduces three key innovations: (1) an interference-aware SBFD resource allocation framework that strategically isolates UL/DL subbands to minimize cross-link interference (CLI), (2) a dual-optimization algorithm that jointly maximizes spectral efficiency while guaranteeing channel-adaptive reliability thresholds, and (3) a practical implementation scheme compatible with existing 5G NR physical layer specifications. Extensive simulations under realistic factory channel models demonstrate 58.3% reduction in aggregate CLI and 41.2% improvement in control command decoding accuracy compared to legacy half-duplex systems. This research establishes a new paradigm for wireless industrial networks, effectively closing the performance gap between 5G URLLC specifications and the exacting demands of Industry 4.0 applications.

The integrated sensing and communication (ISAC) attracts growing interest in 6G due to the extension of radar capability. This paper devotes to the resource allocation problem in ISAC system design. Both static and dynamic resource allocation schemes are comprehensively investigated, with the primary distinction lying in the allocation of resources to either communication or sensing services, or their shared utilization. We construct two-class multi-server queues of each scheme, respectively, where communication and sensing services are modeled as Poisson processes with distinct arrival and service rates. To derive the steady-state probabilities of the two models, we present proofs of reversibility. Additionally, key matrices are derived for performance measurement purposes. Numerical results demonstrate the superiority of the dynamic allocation scheme while also providing insights into resource investment and division.

Ultra-reliable and low latency (uRLLC) plays an important role in the context of automatic driving, in terms of the road safety, which mainly depends on fast data transmission and precise positioning. However, handling this data and positioning efficiently faces a significant challenge, because of high data volume and vehicles' mobility. To support the high rate of sensing data and positioning information sharing between vehicles and base stations, mmWave communication technology, featured by high frequency and bandwidth, is identified as an potential solution. In addition, constrained by the strong directionality of mmWave, to improve the performance of high reliability, low latency and precise sensing, realtime mmWave beam direction regulation is urgently needed. In this paper, based on the multi-source sensing information, we propose a joint design of fast and robust communication and sensing 3D mmWave beam tracking (MSI-ISACBT) algorithm for two kinds of dynamic motions. In detail, for the case of low dynamic motion, the beam direction can be updated by using historical state information and reflected echo signal strength, while it can be adjusted according to the image information acquired by the camera for the case of high dynamic motion. Simulations validate the effectiveness and correctness of the proposed MSI-ISACBT. Compared with other popular methods, MSI-ISACBT achieve a stable throughput of 2.8Gbps and more smooth beam angle control with 16ms delay.

Wireless communication enabled integrated sensing and communication (ISAC) attracts growing interest recently. This paper investigates the sensing ability of OFDM and OTFS signals. We derive the expression of their ambiguity functions, and show that the ambiguity surface can be shaped by the information carried. To this end, we then develop a Zak-transform based ambiguity function synthesis method and deduce the corresponding information sequence in the l2-norm case. Finally, we present the ambiguity surface of it, and compare it with the Zaddoff-Chu and gold sequences that are widely used in LTE and NR systems. Simulations validate the dependency of sensing performance on the designed sequence and the size of the time-frequency resource.

The orthogonal time frequency space (OTFS) modulation as a promising signal representation attracts growing attention for integrated sensing and communication. This paper devotes to MIMO-OTFS based channel parameter estimation. Inspired by the insight that superimposed signals can be composed iteratively and processed separately, we develop the Space-Alternating Generalized Expectation-Maximization (SAGE) algorithm to support the resolution of multiple paths with modest complexity. Besides, we derive the Cramer-Rao lower bound (CRLB) of the variance of channel parameters as the fundamental limit of sensing in the OTFS modulation scheme as well as the baseline of the performance evaluation. Simulations in various cases demonstrate the feasibility.