In this paper, we propose a novel multi-user orthogonal frequency division multiplexing (OFDM)-based sensing and inherent communication (MOSAIC) technique as a potential off-the-shelf integrated sensing and communication (ISAC) framework for 6G mobile networks. The MOSAIC framework facilitates joint user equipment (UE) localization and uplink communication by embedding information-bearing orthogonal sequences (OSs) into a standard commercial OFDM waveform, thereby ensuring compatibility with existing infrastructure and requiring minimal modifications to the physical layer of current 5G standards. Each uplink UE maps its communication bits to a sequence index, while the base station (BS), equipped with a uniform linear array (ULA), estimates the UE’s distance and angle of arrival (AoA) using the correlation properties of the received signal. To accommodate a wide range of 6G service scenarios, the MOSAIC framework supports two primary modes of operation: grant-based and grant-free. In the grant-based mode, OSs are pre-assigned to UEs to ensure collision-free access, assuming that the number of active UEs is known. In the grant-free mode, the MOSAIC framework utilizes an unsourced multiple access-inspired parity-aided approach, where all UEs transmit parity-embedded sequences from a shared pool across multiple blocks without prior knowledge of the number of active UEs. This approach allows the BS to disambiguate overlapping sequences and reliably recover user messages without prior knowledge of UE activity. To reflect practical wireless channel characteristics, including non-line-of-sight (NLoS) conditions, a local scattering channel model is adopted, and clustering and oversampling techniques are applied at the BS to improve localization accuracy. Through extensive simulations, we demonstrate that the proposed MOSAIC framework achieves robust communication and sensing performance across both grant-based and grant-free operation modes. With its OFDM-compatible structure and efficient signaling design, the MOSAIC framework can be readily integrated into existing commercial mobile infrastructures such as 3GPP long-term evolution (LTE) and 5G New Radio (NR), providing a scalable and practical ISAC solution aligned with the objectives of future 6G standardization.

In this paper, we address security threats in an uplink wireless communication network comprising a single base station (BS), multiple legitimate user equipment (UEs), and potential eavesdroppers (EVEs). In this scenario, the EVEs may unintentionally intercept the uplink transmissions of legitimate UEs, posing significant risks to confidentiality. To overcome these threats, we propose novel analytical two-step opportunistic feedback (TOF) strategies to enhance physical-layer security (PLS) under the assumption that each legitimate UE has local channel state information (CSI). The TOF strategy consists of two stages: in the first stage, legitimate UEs perform conservative feedback for user scheduling, assuming all potential EVEs are eavesdropping. If no UE meets the feedback condition, the conventional opportunistic feedback (OF) mechanism is applied in the second stage, where legitimate UEs with channel gains above a predefined threshold send feedback to the BS. We mathematically analyze the secrecy outage probability (SOP) and effective secrecy throughput (EST) of the proposed TOF strategies. Simulation results demonstrate that the TOF strategies significantly outperform the conventional OF approach, achieving lower SOP and higher EST across various scenarios.

In this paper, we propose a novel uplink signal phase inversion-based non-orthogonal multiple access (SPIN-NOMA) technique to effectively suppress mutual interference in integrated sensing and communication (ISAC) systems. Specifically, we consider an ISAC system where a base station (BS) operates as a monostatic radar to sense targets while simultaneously receiving communication signals from multiple user equipments (UEs). We identify limitations in the conventional SPIN-NOMA approach and introduce technical advancements to support high-order modulation schemes and an arbitrary number of UEs. Additionally, we theoretically derive the generalized bit-error rate (BER) performance as a function of modulation order and the number of UEs, employing linear zero-forcing beamforming. Extensive simulations confirm that the proposed SPIN-NOMA technique significantly outperforms the conventional approach in terms of both sensing and communication performance. Furthermore, the simulation results align closely with the derived theoretical BER expressions, confirming their accuracy.

This letter proposes a novel space-time line-coded over-the-air computation technique (STLC-AirComp) for massive Internet-of-Things (IoT) sensing networks. The STLC-AirComp technique enables efficient computation of objective functions by exploiting a simple linear channel inversion structure between IoT sensors and an access point (AP) in single-input multiple-output (SIMO) networks. In particular, this technique enhances the performance of function computation, including metrics such as mean squared error (MSE), without the need for global channel state information (CSI) at the access point (AP). Additionally, STLC-AirComp allows function computation to be performed in a one-shot manner, eliminating the need for complex learning or optimization processes. We perform a rigorous analysis to derive the exact MSE performance of STLC-AirComp, providing fundamental insights into computational reliability for massive IoT networks. Within the STLC-AirComp framework, we show that the MSE approaches zero as the SNR increases sufficiently. Finally, Monte Carlo simulations validate our mathematical analysis, demonstrating strong agreement between the analytical and simulation results.

To meet the growing demand for high-capacity wireless communications, orbital angular momentum (OAM) multiplexing has garnered significant attention due to the orthogonality between OAM modes, which enables enhanced channel capacity. In this work, we propose and experimentally demonstrate a metasurface-based OAM mode-division multiplexing (OAM-MDM) system operating in the E-band. The system employs Fabry–Perot cavity meta-atoms that offer high transmission efficiency and precise phase control, enabling metasurfaces capable of multiplexing and demultiplexing two distinct OAM modes. We establish an electromagnetic-based effective channel model that characterizes the magnitude and phase variations between transmitted and received OAM modes from the radiated electric field. Specifically, the proposed effective wireless channel model captures not only the desired mode-to-mode transmission but also the inter-mode interference and represents these effects in a mathematically tractable form suitable for communication-theoretic analysis. Furthermore, the system performance is comprehensively evaluated by comparing the achievable rates derived from both simulations and experimental measurements under varying input power levels. Experimental results demonstrate that an achievable rate of up to 41.8 bits/s/Hz is attained at an input power of 4.9 dBm. This metasurface-based OAM-MDM system presents a promising approach for future high-capacity free-space communication.

In this paper, we investigate an active Reconfigurable Intelligent Surface (RIS)-assisted unmanned aerial vehicle base station (UAV-BS) system for disaster communication networks. To mitigate the cascaded path loss in the UAV-RIS-user equipment (UE) link, an active RIS capable of amplifying reflected signals is employed. The coverage performance is evaluated and compared with three benchmark architectures: UAV-BS-only, passive RIS-assisted, and amplify-and-forward (AF) relay-assisted systems. Simulation results demonstrate that the active RIS significantly improves the coverage probability and effectively restores the coverage of the failed base station in disaster environments.

This paper proposes a user scheduling algorithm to mitigate the critical cross-link interference (CLI) problem in in-band full duplex (IBFD) systems. In the proposed scheme, downlink (DL) user equipments (UEs) acquire effective CLI channel information from the beamformed pilot signals of scheduled uplink (UL) UEs. This allows the DL UEs to design receive beamformers that actively suppress CLI before the base station performs DL scheduling based on the mitigated interference. Simulation results demonstrate that our algorithm significantly improves the DL sum rate compared to conventional CLI measurement based schemes.

This article introduces a novel uncrewed aerial vehicles (UAV) chasing system designed to track and chase unauthorized UAVs, significantly enhancing their neutralization effectiveness. The system utilizes a multidimensional swarm flight strategy, employing deep reinforcement learning (DRL) to dynamically adapt the tracking unit's movements based on the received signal strength indicators emitted by unauthorized UAVs. Asynchronous learning techniques involving multiple agents are implemented to expedite the system's learning process. A key feature of our approach is the coordinated use of a swarm of UAVs, which circumvents the considerable size burden associated with mounting multiple antennas on a single UAV. We further refine the asynchronous DRL framework by integrating advanced channel modeling techniques, such as spatial correlation and Doppler shift, to augment the robustness and adaptability of the system. Performance evaluations confirm the system's efficacy under varying channel conditions and operational scenarios. Key contributions include the integration of tracking and chasing functionalities into a unified system, the employment of realistic channel models to enhance system adaptability, and a comprehensive analysis of the relationship between channel sampling frequency and chasing performance. This research advances the field of UAV regulation and control, offering an effective solution to the escalating security challenges posed by unauthorized UAVs.

In this paper, we propose a novel orthogonal frequency-division multiplexing (OFDM)-based interleave-division multiple access (IDMA) technique for non-terrestrial Internet-of-Things (IoT) networks utilizing low Earth orbit (LEO) satellites. Specifically, considering the direct links between LEO satellites and IoT devices, we tailor the IDMA framework by incorporating repetition to ensure stable performance even under severe path loss conditions. Furthermore, in accordance with the adoption of OFDM, which is expected to play a key role in sixth-generation (6G) mobile communications, we conducted practical simulations incorporating channel coding to verify the applicability of IDMA to non-terrestrial networks (NTNs). To enhance the reliability of performance evaluation, channel modeling was established based on standard-compliant NTN specifications. The comprehensive performance analysis confirms that IDMA provides stable and reliable multiple access, indicating its potential as a promising solution for future 6G non-terrestrial IoT networks.

Addressing the limitations of traditional sensor-based systems vulnerable to environmental constraints and trust issues, this article introduces a blockchain-assisted maximum evacuation framework in zero trust hiking trail and mountainous terrain using Internet of Things (IoT) devices that leverages blockchain technology for enhanced security and reliability. We devise three innovative algorithms that are designed to maximize the activation of evacuation nodes, ensuring rapid and efficient disaster response. By updating safe areas and evacuation routes dynamically in real-time IoT environment, the developed algorithms aim to significantly improve emergency response capabilities in challenging terrains. Also, the extensive simulations are achieved to demonstrate the performances of the proposed schemes with discussions for obtained outcomes.

Recently, wireless security has been highlighted as one of the most important techniques for 6G mobile communication systems. Many researchers have tried to improve the Physical-Layer Security (PLS) performance such as Secrecy Outage Probability (SOP) and Secrecy Energy-Efficiency (SEE). The SOP indicates the outage probability that the data transmission between legitimate devices does not guarantee a certain reliability level, and the SEE is defined as the ratio between the achievable secrecy-rate and the consumed transmit power. In this paper, we consider a Multi-User Multi-Input Single-Output (MU-MISO) downlink cellular network where a legitimate Base Station (BS) equipped with multiple transmit antennas sends secure information to multiple legitimate Mobile Stations (MSs), and multiple potential eavesdroppers (EVEs) equipped with a single receive antenna try to eavesdrop on this information. Each potential EVE tries to intercept the secure information, i.e., the private message, from the legitimate BS to legitimate MSs with a certain eavesdropping probability. To securely receive the private information, each legitimate MS feeds back its effective channel gain to the legitimate BS only when the effective channel gain is higher than a certain threshold, i.e., the legitimate MSs adopt an Opportunistic Feedback (OF) strategy. In such eavesdropping channels, both SOP and SEE are analyzed as performance measures of PLS and their closed-form expressions are derived mathematically. Based on the analytical results, it is shown that the SOP of the OF strategy approaches that of a Full Feedback (FF) strategy as the number of legitimate MSs or the number of antennas at the BS increases. Furthermore, the trade-off between SOP and SEE as a function of the channel feedback threshold in the OF strategy is investigated. The analytical results and related observations are verified by numerical simulations.

In this paper, we propose a novel digital over-theair computation (AirComp) framework employing space-time line codes (STLC) to achieve optimal spatial diversity gain with only local channel state information (CSI) at transmitters in uplink scenarios. The proposed technique alleviates the overhead of conventional AirComp, where the access point (AP) must acquire global CSI from all sensors, and is tailored to compute target functions under peak power constraints. Each sensor uniformly quantizes its measurement, applies bit slicing with low-order modulation, and transmits STLC-encoded symbols over two time slots. The AP subsequently performs linear combining of the received signals to detect the superimposed symbols and reconstruct the target sum. Simulation results demonstrate that the proposed technique achieves lower normalized mean-squared error than conventional analog and digital AirComp approaches.

A novel opportunistic non-orthogonal random access (O-NORA) technique is proposed for multi-channel systems in sixth-generation (6G) massive connection scenarios, such as Internet of Things (IoT) networks. In this letter, K IoT devices (IDs) independently transmit their packets to a single access point (AP) over one of M available channels. To meet the low-complexity requirements of IoT applications, all nodes are assumed to operate with a single antenna. Specifically, the optimal simultaneous non-unique decoding (SND) technique is leveraged at the AP to enhance network reliability. A rigorous mathematical analysis of the outage probability and channel utilization for the proposed O-NORA technique is provided. The accuracy of our analytical results is validated through simulations. The proposed O-NORA with SND demonstrates a significant performance gain over conventional schemes in terms of outage probability and throughput for 6G multi-channel uplink IoT networks.

In this paper, we propose a novel sequence index grouping-based multiple access (SIGMA) technique for multi-user orthogonal frequency division multiplexing-based integrated sensing and communication (OFDM-ISAC) systems. The proposed technique ensures collision-free access by performing a pre-assignment of orthogonal sequences (OSs) between the base station (BS) and each user equipment (UE), where each UE modulates its communication data onto the allocated sequence index and transmits it to the BS. By exploiting the autocorrelation property of the received sequences, the BS estimates the distance to each UE, while the direction of each user is obtained using a uniform linear array (ULA) antenna equipped at the BS. Furthermore, to achieve accurate localization even in non-line-of-sight (NLoS) multipath environments, a clustering algorithm and an oversampling technique are incorporated. Extensive simulation results demonstrate that the proposed system achieves robust localization and communication performance in multi-user scenarios.