This paper presents a lightweight neural architecture for efficient direction-of-arrival (DoA) estimation, built upon a novel Ghost Squeeze-and-Excitation Residual Block (GSERB). The proposed block integrates Squeeze-and-Excitation (SE) attention directly into the Ghost feature generation process, enabling selective channel enhancement while minimizing redundant feature computation. Unlike conventional attentionaugmented convolutional networks, the GSERB amplifies informative ghost feature channels prior to fusion with intrinsic representations, thereby improving feature discrimination and representational efficiency. Experimental results showcase that this integration enhances the model's ability to capture spa-tial-spectral dependencies while maintaining a compact design. The resulting network, named GSERB-DoANet, achieves an effective balance between accuracy, scalability, and computational efficiency for real-time multi-source DoA estimation in wireless sensing applications.

This paper explores the application of Temporal Fusion Transformers (TFTs) to target recognition and multi-horizon tracking, with a particular emphasis on enhancing Direction of Arrival (DoA) estimation in complex signal environments. By leveraging the advanced temporal modeling capabilities and dynamic feature selection mechanisms inherent to the TFT architecture, we adapt and optimize the model for improved performance in antenna signal processing, leading to a more accurate and robust estimation framework. Our analysis underscores the architectural strengths of TFTs, especially their capacity to model long-range temporal dependencies and to dynamically prioritize sensor-derived features—capabilities that are essential for precise target tracking and recognition. We train and evaluate the model under diverse conditions, including multi-horizon forecasting and varying prediction latencies across models. The proposed method is benchmarked against state-of-the-art algorithms, including recurrent neural networks and standard transformer-based models. Extensive experimental results demonstrate that the TFT-based approach consistently outperforms existing techniques in forecasting accuracy, multi-target recognition, and computational complexity, highlighting its potential to advance the field of DoA estimation.

As virtual reality (VR) and 360° video applications continue to gain traction, multi-quality tile-based 360° video streaming has emerged as a flexible and adaptive solution for delivering high-quality immersive content while optimizing bandwidth usage. However, the presence of mixed quality levels within a single 360° video frame can adversely affect users' perceived quality. In this work, we investigate the impact of spatial quality variations across tiles and within users' viewports, and provide improved perceptual quality modeling for tiled 360° videos. To realize this goal, we introduce the Subjective Tile based Assessment for 360° Videos (STAV360) dataset, which includes six source 360° videos, each encoded using twelve tile based configurations, subjective ratings from 27 participants, and corresponding viewing trajectories. Based on this dataset, we propose novel tile-based and viewport-aware 360° video quality assessment (360° VQA) models that incorporate tile-level quality information and user interaction data. Experimental results show that our models outperform conventional full-frame methods by more accurately predicting perceived quality. This work provides key insights for designing perceptually-driven quality metrics and lays the foundation for more efficient and adaptive tile-based 360° video streaming strategies.

Programmable Wireless Environments (PWEs) leverage Reconfigurable Intelligent Surfaces (RISes) to actively shape electromagnetic (EM) propagation, enabling advanced control over wireless channels. Beyond improved performance in B5G/6G networks, this control also introduces new security capabilities. Exploiting this, we propose RF-Fencing: a service that selectively suppresses EM signals toward eavesdroppers while preserving reliable communication for legitimate users, thereby significantly enhancing network covertness. Building on that, in this paper, we introduce SHIELD, the first RF-Fencing algorithm that partitions the PWE into Signal Suppression Areas (SSAs) and Signal Delivery Areas (SDAs) through on-the-fly merging of RIS configurations. Extensive EM analysis confirms SHIELD’s effectiveness in preventing wardens from intercepting critical information and achieving covert communications with minimal impact on legitimate users. Moreover, SHIELD can serve also as a jamming-mitigation mechanism and is applicable across various frequency bands and RIS designs.

Software-Defined Metasurfaces (SDMs) have ad-vanced from basic theoretical ideas to a key enabler for next generation wireless systems. When massively deployed in a wireless environment, they can realize precise, software-defined propagation of signals and wireless channel customizations. A plethora of studies have thoroughly investigated the physical design of the SDMs and their wireless channel engineering capa-bilities. This work introduces a novel architecture and associated processes for integrating SDMs into existing networked wireless systems. First, the integration architecture and the according complex underlying physics of the SDMs are presented. Then the software abstractions are proposed that enable the interaction of the surfaces in a physics-agnostic manner. These software abstractions require an SDM profile to operate in real-time, i.e., a database that accurately describes the capabilities of a given metasurface. Thus, the manufacturing time workflows are suggested to produce such a profile. The proposed solutions are evaluated in an actual physical setup/testbed.

Programmable, intelligent surfaces can manipulate electromagnetic waves impinging upon them, producing arbitrarily shaped reflection, refraction and diffraction, to the benefit of wireless users. Moreover, in their recent form of HyperSurfaces, they have acquired inter-networking capabilities, enabling the Internet of Material Properties with immense potential in wireless communications. However, as with any system with inputs and outputs, accurate sensing of the impinging wave attributes is imperative for programming HyperSurfaces to obtain a required response. Related solutions include field nano-sensors embedded within HyperSurfaces to perform minute measurements over the area of the HyperSurface, as well as external sensing systems. The present work proposes a sensing system that can operate without such additional hardware. The novel scheme programs the HyperSurface to perform compressed sensing of the impinging wave via simple one-antenna power measurements. The HyperSurface can jointly be programmed for both wave sensing and wave manipulation duties at the same time. Evaluation via simulations validates the concept and highlight its promising potential.

Metasurfaces, ultrathin and planar electromagnetic devices with sub-wavelength unit cells, have recently attracted enormous attention for their powerful control over electromagnetic waves, from microwave to visible range. With tunability added to the unit cells, the programmable metasurfaces enable us to benefit from multiple unique functionalities controlled by external stimuli. In this review paper, we will discuss the recent progress in the field of programmable metasurfaces and elaborate on different approaches to realize them, with the tunability from global aspects, to local aspects, and to software-defined metasurfaces.

Tunable metasurfaces are ultra-thin, artificial electromagnetic components that provide engineered and externally adjustable functionalities. The programmable metasurface, the HyperSurFace, concept consists in integrating controllers within the metasurface that interact locally and communicate globally to obtain a given electromagnetic behaviour. Here, we address the design constraints introduced by both functions accommodated by the programmable metasurface, i.e., the desired metasurface operation and the unit cells wireless communication enabling such programmable functionality. The design process for meeting both sets of specifications is thoroughly discussed. Two scenarios for wireless intercell communication are proposed. The first exploits the metasurface layer itself, while the second employs a dedicated communication layer beneath the metasurface backplane. Complexity and performance trade-offs are highlighted.

Machine-type communication (MTC) provides a potential playground for deploying machine-to-machine (M2M), IP-enabled `things' and wireless sensor networks (WSNs) that support modern, added-value services and applications. 4G/5G technology can facilitate the connectivity and the coverage of the MTC entities and elements by providing M2M-enabled gateways and base stations for carrying traffic streams to/from the backbone network. For example, the latest releases of long-term evolution (LTE) such as LTE-Advanced (LTE-A) are being transformed to support the migration of M2M devices. MTC-oriented technical definitions and requirements are defined to support the emerging M2M proliferation. ETSI describes three types of MTC access methods, namely a) the direct access, b) the gateway access and c) the coordinator access. This work is focused on studying coverage aspects when a gateway access takes place. A deployment planar field is considered where a number of M2M devices are randomly deployed, e.g., a hospital where body sensor networks form a M2M infrastructure. An analytical framework is devised that computes the average number of connected M2M devices when a M2C gateway is randomly placed for supporting connectivity access to the M2M devices. The introduced analytical framework is verified by simulation and numerical results.

Nanonetworks comprise numerous wireless nodes, assembled at micro-to-nano scale. The unique manufacturing challenges and cost considerations of these networks make for minimal complexity solutions at all network layers. From a networking aspect, packet retransmissions should be kept minimal, while ensuring communication between any two nanonodes. In addition, assigning unique addresses to nanonodes is not straightforward, since it can entail a prohibitively high number of packet exchanges. Thus, efficient data routing is considered an open issue in nanonetworking. The present paper proposes a routing system which can be dynamically deployed within a nanonetwork. Static, dense topologies with numerous, identical nodes are examined. These attributes are especially important in the context of recently proposed applications of nanonetworks. The proposed scheme incurs a trivial setup overhead and requires integer processing capabilities only. Once deployed, it operates efficiently, inducing lower packet retransmission rates than related schemes.