Achieving accurate and flexible localization in global navigation satellite system (GNSS)-denied underground spaces is critical for Internet of Things (IoT)-enabled logistics and personnel operations. To this end, this paper proposes a scalable multimodal localization framework requiring only a single ultra-wideband (UWB) transmitter connected to a distributed antenna system, avoiding the deployment of multiple additional anchors. An adjacency-masked, change-point-aware hidden Markov model (AC-HMM) is developed for region identification using only two-path UWB measurements, which avoids full channel impulse response (CIR) processing and reduces computational complexity. A multi-scale factor-graph maximum a posteriori inference method (MS-FGM) is then proposed for dynamic localization by fusing UWB and magnetic-field residuals with region and motion constraint factors. Multi-scale temporal aggregation is further introduced to mitigate motion-induced fluctuations and improve localization accuracy and stability. Experiments conducted along the roadways of an underground parking lot demonstrate an average region classification accuracy of 96.81% and a mean positioning error of 0.88 m, outperforming existing methods by up to 42.19%.

To achieve seamless and continuous positioning for smartphones in tunnels, where the Global Navigation Satellite System (GNSS) signals are unavailable, this paper proposes a new method that leverages the existing leaky coaxial cable (LCX) infrastructure from public land mobile networks to introduce the GNSS signals directly from outside the tunnels. This approach introduces three key innovations. First, a continuous hybrid GNSS-LCX channel is proposed which uses a waveguide-to-wireless model to provide continuous GNSS signal coverage via existing 5G LCX without requiring dedicated hardware. Based on this model, a bidirectional clock bias cancellation mechanism is designed for GNSS signals inside the tunnel. This method establishes a quantitative mapping between the position in the tunnel and the pseudorange observations incorporating clock bias, enabling the residual latency from smartphones and wired transmission in the tunnel to be modeled as a function of signal propagation distance and user tracks within the tunnel environment. Furthermore, a 5G-enhanced factor graph optimization (FGO) method is proposed, which integrates 5G measurements and tunnel topology to suppress positioning fluctuations caused by multipath effects in tunnels, while mitigating GNSS positioning latency and ambiguity induced by 5G cell handovers. Field tests in a 150-m tunnel show 1.21 m median accuracy, achieving 46% higher accuracy than fingerprinting and 3.2×faster convergence than conventional methods. This solution reuses 5G-LCX infrastructure for cost-effective and consistent tunnel positioning that bridges the gap between open-sky and underground tunnel environments.

The global navigation satellite system (GNSS) fails in indoor environments, leading to a growing demand for indoor positioning, ranging from above-ground buildings to under-ground parking lots. Existing indoor positioning technologies face challenges balancing low cost, low latency, and high accuracy, particularly in large underground parking lots (LUPLs). This paper proposes a sparsely deployed Bluetooth and magnetic (SBM) fusion positioning system for LUPL scenarios. Specifically, the spatial characteristics of the received signal strength indicator (RSSI) from sparsely deployed Bluetooth and the magnetic field strength are analyzed. Static and dynamic algorithms are designed for the SBM system by utilizing Bluetooth's area division and coarse positioning, combined with the high precision of magnetic field positioning. Experimental results from a real LUPL deployment demonstrate that, under a sparse beacon distribution (1 beacon per 294 m2), the proposed positioning algorithms achieve static accuracy of 1.32 m, dynamic accuracy of 0.75 m, and low latency on consumer-grade devices.

In the sixth generation (6G) Internet of Things (IoT), integrated sensing and communication (ISAC) emerges as a key technology, which is expected to significantly enhance the perception capabilities and spectrum efficiency of base stations (BSs). It holds potential for applications in unmanned aerial vehicle (UAV) monitoring, vehicle positioning, and crowd detection. However, developing an integrated waveform that efficiently conserves spectrum resources while maintaining lower complexity remains challenging. This paper designs an ISAC system that utilizes orbital angular momentum (OAM) waves generated by a uniform circular array (UCA), which enhances communication and sensing capabilities by allocating distinct modes. This paper proposes a multimode multiplexing communication scheme based on a single UCA and an OAM-circular reception method (OAM-CRM) for the two-dimensional direction-of-arrival (DOA) estimation of targets, encompassing both azimuth and elevation angles. Additionally, an OAM-different modes (OAMDM) algorithm is designed to optimize communication and sensing performance across various mode sets. Simulation results verify the effectiveness of the OAM ISAC system and demonstrate the superior performance of the proposed algorithms compared to conventional methods.

Orbital angular momentum (OAM) multiplexing techniques have great potential in high-speed and high-capacity short-range wireless communication. However, the divergence angle of OAM waves changes with mode and frequency, increasing the receiver complexity. This paper proposes a Bessel constraint method for generating OAM waves with the same divergence angle. Specifically, this paper first analyzes the factors affecting the divergence angle by combining two uniform circular arrays (UCAs) as uniform concentric circular arrays (UCCAs). Then, this paper defines the intensity proportion between the two UCAs to analyze constraint conditions. Additionally, two algorithms are designed to generate multimode OAM waves with equal divergence angles, considering scenarios with and without multiple frequency bands. Simulation results demonstrate the effectiveness of these algorithms in generating OAM waves with matching maximum strength ring radii, enabling the receiver to fully receive OAM waves of multiple modes and frequencies with just one UCA. Furthermore, the proposed approach facilitates the adjustment of OAM waves with different modes and frequencies by flexibly modifying the intensity proportion without necessitating alterations to the antenna radius.