The industrial Internet of things (IIoT) is revolutionizing industrial processes by facilitating massive machinetype communications among countless interconnected devices. To efficiently handle the resulting large-scale and sporadic traffic, grant-free random access protocols-especially coded random access (CRA)-have emerged as scalable and reliable solutions. At the same time, advancements in wireless hardware, including extremely large-scale MIMO arrays and high-frequency communication (e.g., mmWave, Terahertz), are pushing network operations into the near-field propagation regime, allowing for dense connectivity and enhanced spatial multiplexing. This paper proposes an innovative approach that combines near-field spatial multiplexing with the interference mitigation capabilities of CRA, utilizing an extremely large aperture array at the access point. This integration improves reliability and reduces access latency, offering a robust framework for IIoT connectivity in next-generation 6 G networks.

Massive machine-type communications are transforming the Industrial Internet of Things (IIoT) by enabling seamless connectivity among a vast number of devices. To efficiently manage the resulting sporadic and large-scale traffic, grant-free random-access protocols, particularly coded random access (CRA), have emerged as scalable and reliable solutions. Meanwhile, advancements in extremely large-scale MIMO and high-frequency communications (e.g., mmWave, THz) are pushing networks into the near-field regime, enhancing spatial multiplexing and connectivity. In this paper, we propose a novel coded spatial random access (CSRA) scheme that leverages an extremely large aperture array (ELAA) at the access point (AP) to exploit near-field spatial multiplexing for grant-free massive access in IIoT systems. Unlike conventional approaches, CSRA eliminates the need for complex channel estimation by integrating CRA with successive interference cancellation and the spatial multiplexing capabilities of the near-field regime. This enables improved reliability and scalability, making CSRA a promising solution for next-generation wireless networks.

In the context of fully distributed systems, we consider a scenario densely populated with wireless nodes which are equipped with simultaneous wireless information and power transfer (SWIPT) capabilities and can act as relays between a source and a destination. In this scenario, the probability of finding a node able to provide a useful contribution to the quality of the link tends to be high and can be exploited adopting a suitable relay selection scheme. Assuming nodes distributed following a Poisson point process and communicating only with source and destination to ensure the scalability of the system, we consider two well-known relay selection schemes, which are typically used as performance benchmarks, and derive an analytical framework to investigate the performance of the source-destination link in terms of outage probability. In our analysis we include, through the use of a simple but effective model, the non-linear effects of the energy harvesting circuitry of the devices and introduce a simple signaling mechanism between source, SWIPT nodes and destination to identify the most suitable relay among the various SWIPT devices. The impact of multiple access during the phase of relay selection is also modeled and investigated.

Future automated driving relies on two pillars, (i) ultra-low-latency and reliable communications, and (ii) accurate positioning information. In particular, the knowledge of vehicle positions is becoming fundamental with the increase of the automation level, allowing autonomous navigation of the environment. Today’s positioning techniques cannot provide the accuracy, robustness, and latency required for stringent applications, like platooning, where vehicles are expected to travel at extremely short distances. In this paper, we leverage vehicle-to-everything (V2X) sidelink communication for localization purposes, capitalizing on the near-field propagation attributes of signals generated utilizing high carrier frequencies and/or large antenna arrays. Consequently, a receiving vehicle can accurately determine the transmitting vehicle’s location through V2X sidelink packet reception, obviating the need for supplementary reference nodes or stringent synchronization. Fundamental limits on localization accuracy are derived to characterize the positioning performance in vehicular contexts. A case study based on 5G new radio (NR) V2X sidelink shows how this technique is extremely promising and capable of providing high accuracy, low latency, high update rate, and high availability of position information in realistic vehicular scenarios.

Communications in the mmWave and THz bands will be a key technological pillar for next-generation wireless networks. However, the increase in the frequency results in an increase in the path loss that must be compensated for by using large antenna arrays. This introduces challenging issues due to power consumption, signaling overhead for channel estimation, and slow beamforming procedures, which are in contrast to the requirements of next-generation wireless networks, and affect the hardware complexity. In this paper, we propose the adoption of a self-conjugate metasurface (SCM) at the user side and an iterative scheme at the base station for channel eigenvector estimation to establish a multiple-input multiple-output (MIMO) uplink communication automatically with almost zero latency, and jitter. This is done while communicating in an optimal way, without the need for ADC chains as well as without channel estimation and time-consuming beamforming schemes.

Abstract We consider a multiple‐input multiple‐output (MIMO) channel in the presence of a reconfigurable intelligent surface (RIS). Specifically, our focus is on analysing the spatial multiplexing gains in line‐of‐sight and low‐scattering MIMO channels in the near field. We prove that the channel capacity is achieved by diagonalising the end‐to‐end transmitter‐RIS‐receiver channel, and applying the water‐filling power allocation to the ordered product of the singular values of the transmitter‐RIS and RIS‐receiver channels. The obtained capacity‐achieving solution requires an RIS with a non‐diagonal matrix of reflection coefficients. Under the assumption of nearly‐passive RIS, that is, no power amplification is needed at the RIS, the water‐filling power allocation is necessary only at the transmitter. We refer to this design of RIS as a linear, nearly‐passive, reconfigurable electromagnetic object (EMO). In addition, we introduce a closed‐form and low‐complexity design for RIS, whose matrix of reflection coefficients is diagonal with unit‐modulus entries. The reflection coefficients are given by the product of two focusing functions: one steering the RIS‐aided signal towards the mid‐point of the MIMO transmitter and one steering the RIS‐aided signal towards the mid‐point of the MIMO receiver. We prove that this solution is exact in line‐of‐sight channels under the paraxial setup. With the aid of extensive numerical simulations in line‐of‐sight (free‐space) channels, we show that the proposed approach offers performance (rate and degrees of freedom) close to that obtained by numerically solving non‐convex optimization problems at a high computational complexity. Also, we show that it provides performance close to that achieved by the EMO (non‐diagonal RIS) in most of the considered case studies.

This paper addresses the exploitation of the orbital angular momentum (OAM) property of the electromagnetic waves with large intelligent surfaces (LISs) in near-field and line-of-sight propagation conditions for holographic multiple-input multiple-output (MIMO) communications. The relation-ship between OAM-carrying waves and communication modes established between intelligent surfaces is discussed, and practical strategies for exploiting OAM with LISs are then presented. Nu-merical results characterize the effectiveness of OAM compared to alternative strategies, though highlighting that OAM-based techniques constitute a particular choice of basis set that is sub-optimum with respect to the basis sets corresponding to optimal communication modes, albeit ensuring lower complexity.

Efforts are underway to finalize the fifth generation (5G) vehicle-to-everything (V2X) communication technology. Direct communication among vehicles over the sidelink interface through the autonomous selection of radio resources is among the main and more challenging capabilities of such a connectivity solution. Nonetheless the crucial enhancements conceived by the Third Generation Partnership Project (3GPP) in Release 16, the autonomous resource allocation (a.k. a. Mode 2) still suffers from collisions due to the wrong estimation of the resource occupancy status enforced by half-duplex (HD) transceivers. In this paper, we argue in favour of the usage in vehicles of in-band full-duplex (FD) transceivers, gaining momentum in the research towards sixth generation (6G) systems thanks to their simultaneous transmission and reception capability. Exploiting FD, we propose to enhance the autonomous mode by detecting collisions and triggering resource reselection procedures in a more conscious manner. Simulation results show that the conceived proposal allows sidelink V2X to achieve significant improvements in terms of reliability and timeliness when compared against the legacy Mode 2.

This paper considers a scenario where a reconfigurable intelligent surface (RIS) is deployed to allow the localization of mobile users adopting a single anchor node, even under non-line-of-sight (NLOS) channel conditions. When the RIS is large and the operating frequency is high, as in the millimeter-wave band, the system is likely to operate in the near-field propagation regime, which can be exploited to obtain robust localization. To this purpose, two practical signaling and positioning algorithms, based on an orthogonal frequency division multiplexing (OFDM) downlink system, are proposed along with methods to design the RIS time-varying reflection coefficients. In the numerical results, the two algorithms are compared in terms of performance in the presence of a synchronization mismatch and considering trade-offs between bandwidth, overhead, operating frequency, and latency. Finally, we provide an analysis of the soft-coverage capability, i.e., on the possibility of maintaining a high level of localization accuracy when in the presence of increasing levels of obstruction of the RIS.

This paper investigates theoretical limits on time delay estimation performance when the received waveform is unknown. Considering that the Cramér-Rao bound for the time delay estimation error cannot be derived in this case, the analytical expression of the Ziv-Zakai bound is provided and discussed.

Passive and semipassive ultrawideband (UWB) radio-frequency identification (RFID) technology has been recently proposed to offer high-accuracy localization capabilities in next-generation RFID systems. This technology relies on the modulation of backscattered signals, i.e., backscatter modulation, from multiple tags present in the environment. The detection of multiple tags based on backscattered signals is challenging in harsh environments with nonideal conditions such as clutter, near-far interference effects, and clock drift. This paper analyzes the detection of multiple tags employing UWB backscatter modulation and proposes practical signaling, spreading codes, and detection schemes that are robust to nonideal conditions. A case study is presented to evaluate the performance of the proposed technique for the detection of multiple tags based on impulsive backscattered signals.

Network localization enables a variety of new applications that rely on the positional information of nodes. High-accuracy network localization is challenging in harsh propagation environments (such as indoor) and is limited by power emission constraints. We devise non-regenerative ultra-wideband relaying to improve the performance of network localization in terms of coverage and accuracy. Maximum likelihood inference of nodes' position for relayed network localization is developed, with perfect and imperfect channel knowledge. Results quantify the performance improvement that non-regenerative relaying offers despite its low-complexity.

Novel non-coherent impulse communications receivers are proposed to alleviate excessive noise collection in clustered multipath channels. To this aim, a stop-and-go strategy based on energy detection in the autocorrelation receiver or in the energy detection receiver is employed. This strategy enables the selective collection of useful signal portions only, allowing the integration interval to be kept large without noise penalty. To implement this strategy, a blind method is employed, using model order selection based on information theoretic criteria, which optimizes the performance of the proposed receiver and does not require the estimation of channel parameters. The bit error probability of the proposed stop-and-go receivers is evaluated, and our results highlight the considerable performance gain at the expense of a small increase in complexity.

This paper introduces the notion of network experimentation and proposes an experimentation methodology particularly suited for cooperative wireless networks. Based on this methodology we performed extensive measurement campaigns and compare various cooperative localization techniques under a common setting. Network experiments enable (i) the quantification of cooperation benefits, (ii) the development of techniques for harnessing environmental information, and (iii) the characterization of network localization algorithms. As a case study, we consider ultrawide bandwidth cooperative location-aware networks in cluttered indoor environments and evaluate their performance based on measurements collected from network experiments.

Transmitted-reference (TR) modulation schemes have generated interest in the context of ultrawide bandwidth (UWB) communications in order to avoid complex channel estimation and synchronization. In these schemes, the length of the integration interval must be carefully chosen to achieve optimal performance. Difficulties arise since this parameter is related to the channel characteristics and to the signal-to-noise ratio (SNR). In this paper, we propose a blind method for the integration time determination, that adopts a model order selection strategy based on information theoretic criteria (ITC). Observing the received signal, without a-priori information about the channel and the SNR, the proposed technique finds an integration time closer to the channel ensemble optimum integration time, i.e., the integration time obtained a-posteriori for the considered channel model as the value that minimizes the average bit error probability (BEP) of the TR scheme for each SNR.