Although massive multi-input multi-output (mMIMO) systems offer higher directivity gains to mitigate propagation losses at millimeter wave (mmWave) frequencies, they present challenges in channel state information (CSI) acquisition and beam alignment, particularly in highly mobile vehicle-to-vehicle (V2V) scenarios with short channel coherence times. To address these issues, we propose a target-in-the-loop beam tracking approach that leverages GPS data and Long Short-Term Memory (LSTM) networks to select beams from predefined beamforming codebooks. By transforming GPS data into relative coordinates and extracting features such as relative velocity and orientation, our model predicts future beam states up to 500 ms in advance, enabling proactive beam selection and blockage avoidance. Using the DeepSense V2V dataset, our method achieves up to 7.2 dB power loss reduction and a 32% improvement in top-5 accuracy compared to a linear interpolation baseline. This approach highlights the potential of integrating GPS data and machine learning to enhance beam tracking in dynamic V2V mmWave networks.

Autonomous agents are increasingly deployed in dynamic environments where their ability to perform a given task depends on both individual and collective proficiency. While PSA has been studied for single agents, its extension to a team of agents remains underexplored. This letter addresses this gap by introducing a framework for team PSA in centralized settings. Specifically, we investigate two metrics for centralized team PSA: the MPB and the KS statistic. These metrics quantify the in-situ discrepancy between predicted and actual measurements. Then, we use the KL divergence as a reference metric. Simulations in a target tracking scenario demonstrate that both MPB and KS metrics accurately capture model mismatches, align with the KL divergence reference, and enable real-time proficiency assessment.

To meet the stringent requirements of next-generation wireless networks, multiple-input multiple-output (MIMO) technology is expected to become massive and pervasive. Unfortunately, this could pose scalability issues in terms of complexity, power consumption, cost, and processing latency. Therefore, novel technologies and design approaches, such as the recently introduced holographic MIMO paradigm, must be investigated to make future networks sustainable. In this context, we investigate the concept of a dynamic scattering array (DSA) as a versatile electromagnetic (EM) structure capable of performing joint wave-based computing and radiation by moving the processing from the digital domain to the EM domain. We provide a general, wideband analytical framework for modeling the DSA, which includes a power matching network and realistic reconfigurable loads. Then we introduce specific design algorithms, and apply them to various use cases. We demonstrate that some recent EM processing structures can be seen as particular cases of our general framework. The examples presented in the numerical results corroborate the potential of DSAs to reduce complexity and the number of radiofrequency (RF) chains in holographic MIMO systems while achieving enhanced EM wave processing and radiation flexibility for tasks such as beamforming and single- and multi-user MIMO, also exhibiting superdirectivity capabilities.

This paper introduces a learning-based approach to the near-field source localization problem adopting a hybrid analog-digital beamformer in an extremely large-scale multipleinput multiple-output (XL-MIMO) system. Hybrid analog-digital architectures gained significant attention in the literature due to the limited number of radio-frequency (RF) chains. However, the investigation of effective techniques tailored to partially connected hybrid beamformers for near-field localization is still missing in the literature. To this end, we leverage a Convolutional Neural Network (CNN)-based model to: (i) perform the analog beamformer design with proper training constraints; and (ii) estimate the single-user near-field position in a single snapshot. In the inference stage, the model is divided into two parts: the first accounts for the beamformer design, and the second acts as a localizing function. Simulation results demonstrate superior performance of the proposed method over existing solutions and robustness in multipath propagation conditions. In addition, our network is scalable and requires fewer RF chains than fullyconnected architectures.

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.

Radio frequency wireless power transfer enables charging low-power mobile devices without relying on wired infrastructures. Current existing wireless power transfer systems are typically designed assuming far-field propagation, where the radiated energy is steered to towards given angles, resulting in limited efficiency and possible radiation in undesired locations. An emerging technology for wireless signaling is based on dynamic metasurface antennas (DMAs), which efficiently realize electrically large arrays. When such arrays are employed at high frequencies, wireless power transfer might take place in the radiating near-field (Fresnel) region, where spherical wave propagation holds, providing more degrees-of-freedom and improved performance. In this article, we study wireless power transfer systems charging multiple devices in the Fresnel region, where the energy transmitter is equipped with a DMA, exploring how the antenna configuration can exploit the spherical wavefront to generate focused energy beams. In particular, after presenting a mathematical model for DMA-based radiating near-field wireless power transfer systems, we characterize the weighted sum-harvested energy maximization problem of the considered system, and we propose an efficient solution to jointly design the DMA weights and digital precoding vector. Then, by accounting for hardware constraints, we further extend our study to encompass practical scenarios with discrete phase shifts in DMA elements. Simulation results show that our design generates focused energy beams capable of improving energy transfer efficiency in the radiating near-field with minimal energy pollution.

Recent advancements in smart radio environment technologies aim to enhance wireless network performance through low-cost electromagnetic (EM) devices. Among these, metaprisms (MTPs)—a class of static, frequency-selective metasurfaces—stand out for their ability to create multiple beams at different frequencies without requiring channel state information (CSI) or active reconfiguration. Unlike reconfigurable intelligent surfaces (RIS), which rely on programmable elements and periodic tuning, MTPs operate passively, significantly reducing system complexity and overhead. The working principle of MTPs is specifically tailored for scenarios in which a large number of devices must be served simultaneously, each requiring low data rate and low latency, as envisioned by, e.g., Industrial Internet-of-Things (IoT). In this paper, we address the design of an ideal MTP by considering frequency-dependent reflection coefficients, and by identifying the general properties that are necessary to achieve the desired beam steering function in the angle-frequency domain. We also discuss the limitations of previous studies that employed oversimplified models, which may compromise performance. Key contributions include a detailed exploration of the equivalence of the MTP to an ideal S-parameter multiport (MP) model and an analysis of its implementation using Foster’s circuits. Additionally, we introduce a realistic MP network model that incorporates aspects overlooked by ideal scattering models, along with an ad-hoc optimization strategy for the obtained model. The performance of the proposed optimization approach and circuits implementation are validated through simulations using a commercial full-wave EM simulator, showcasing the effectiveness of the proposed method.

Wireless Sensor Networks (WSNs) play a pivotal role in diverse domains such as environmental sensing, industrial monitoring, and entertainment. This paper focuses on modeling the connectivity of the link considering the quality of service (QoS) criterion. This is a baseline for considering the probability density function (PDF) of the node’s distance from the base station (BS) to form a multi-hop wireless sensor networks (WSNs) structure. We delve into modeling the connectivity behavior in multi-hop networks, addressing scenarios involving non-homogeneous Poison Point Process (NHPPP) and homogeneous Poison Point Process (HPPP). Furthermore, we introduce closed-form expressions with reduced computational complexity. This contribution establishes a comprehensive framework for understanding and enhancing the performance of multi-hop wireless sensor networks.

The recent introduction of the smart radio environments (SREs) paradigm, facilitated by reconfigurable intelligent surfaces (RISs) and large surface antennas, has highlighted the need for physically consistent models and design tools in communication systems that integrate information theory (IT) and electromagnetic (EM) theory. In this paper, we present a comprehensive framework for characterizing and designing programmable EM environments, based on rigorous EM arguments and represented through a linear graph employing matrix operators. The framework enables the determination of the EM transfer function of the system and the channel matrix used in IT, along with their relationship as functions of the programmable parameters. Considering that the mapping of EM quantities into IT signals occurs through the presence of ports in antenna structures, using the framework, we analyze the constraints imposed by the ports in terms of potential degrees-of-freedom (DoF) and establish the fundamental limits on the DoF of large surface antennas. To demonstrate the utility and validity of the framework, we provide examples specifically related to the characterization and optimization of RISs.

Future wireless networks will integrate sensing, learning, and communication to provide new services beyond communication and to become more resilient. Sensors at the network infrastructure, sensors on the user equipment (UE), and the sensing capability of the communication signal itself provide a new source of data that connects the physical and radio frequency (RF) environments. A wireless network that harnesses all these sensing data can not only enable additional sensing services but also become more resilient to channel-dependent effects such as blockage and better support adaptation in dynamic environments as networks reconfigure. In this article, we provide a vision for integrated sensing and communication (ISAC) networks and an overview of how signal processing, optimization, and machine learning (ML) techniques can be leveraged to make them a reality in the context of 6G. We also include some examples of the performance of several of these strategies when evaluated using a simulation framework based on a combination of ray-tracing measurements and mathematical models that mix the digital and physical worlds.

Sixth generation (6G) cellular communications are expected to support enhanced wireless localization capabilities. The widespread deployment of large arrays and high-frequency bandwidths give rise to new considerations for localization applications. Emerging antenna architectures, such as dynamic metasurface antennas (DMAs), are expected to be frequently utilized thanks to the achievable high angular resolution and low hardware complexity. Further, wireless localization is likely to take place in the radiating near-field (Fresnel) region, which provides new degrees of freedom, because of the adoption of arrays with large apertures. While current studies mostly focus on the use of costly fully-digital antenna arrays, in this paper we investigate how DMAs can be applied for near-field localization of a single user. We use a direct positioning estimation method based on curvature-of-arrival of the impinging wavefront to obtain the user location, and characterize the effects of DMA tuning on the estimation accuracy. Next, we propose an algorithm for configuring the DMA to optimize near-field localization, by first tuning the adjustable DMA coefficients to minimize the estimation error using postulated knowledge of the actual user position. Finally, we propose a sub-optimal iterative algorithm that does not rely on such knowledge. Simulation results show that the DMA-based near-field localization accuracy could approach that of fully-digital arrays at lower cost.

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.

Link adaptation is fundamental in managing spectrum resources efficiently and is proven to be fundamental in the overall system operation and performance boost. The aim of this paper is to propose and characterize a novel algorithm based on the proportional-integral-derivative (PID) controller principles and block error rate (BLER) target for modulation and coding scheme (MCS) selection applied to the latest mobile telecommunication standards. Tests were conducted in a laboratory-level 5G system where, by means of a channel emulator, downlink performance for a hotspot-like scenario is evaluated. We show how the proposed PID link adaptation algorithm reacts to the downlink channel variations, and hence ensures convergence to the target BLER and boosts the system throughput, in comparison with traditional MCS selection and reference adaptation algorithms.

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.

Reconfigurable intelligent surfaces (RISs) have tremendous potential to boost communication performance, especially when the line-of-sight (LOS) path between the user equipment (UE) and base station (BS) is blocked. To control the RIS, channel state information (CSI) is needed, which entails significant pilot overhead. To reduce this overhead and the need for frequent RIS reconfiguration, we propose a novel framework for integrated localization and communications, where RIS configurations are fixed during location coherence intervals, while BS precoders are optimized every channel coherence interval. This framework leverages accurate location information obtained with the aid of several RISs as well as novel RIS optimization and channel estimation methods. Performance in terms of localization accuracy, channel estimation error, and achievable rate demonstrates the effectiveness of the proposed approach.

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.

Joint localization and communication services have received growing interest for the next 6G cellular scenarios. Therefore, this paper studies a multi-Reconfigurable Intelligent Surface (RIS) single-user Multiple Input Multiple Output (MIMO) scenario from a dual perspective. From one side, we analyze the capabilities of an Extended Kalman Filter (EKF) to track the trajectory of the user by processing the positioning information gathered by the signals backscattered from the RISs, whereas the RISs are in turn optimized accounting for the outcomes of the EKF estimator. On the other side, we analyze the impact of positioning onto the communication performance in terms of achievable rate. Numerical results have shown that it is possible to track moving nodes with high accuracy leveraging on, solely, the radio signal reflected by the RISs in the absence of a line-of-sight (LOS) path between the transmitter and the receiver ensuring, at the same time, good communications performance.

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.

Large antenna arrays and high-frequency bands are two key features of future wireless communication systems. The combination of large-scale antennas with high transmission frequencies often results in the communicating devices operating in the near-field (Fresnel) region. In this paper, we study the potential of beam focusing, feasible in near-field operation, in facilitating high-rate multi-user downlink multiple-input multiple-output (MIMO) systems. As the ability to achieve beam focusing is dictated by the transmit antenna, we study near-field signalling considering different antenna structures, including fully-digital architectures, hybrid phase shifter-based precoders, and the emerging dynamic metasurface antenna (DMA) architecture for massive MIMO arrays. We first provide a mathematical model to characterize near-field wireless channels as well as the transmission pattern for the considered antenna architectures. Then, we formulate the beam focusing problem for the goal of maximizing the achievable sum-rate in multi-user networks. We propose efficient solutions based on the sum-rate maximization task for fully-digital, (phase shifters based-) hybrid and DMA architectures. Simulation results show the feasibility of the proposed beam focusing scheme for both single- and multi-user scenarios. In particular, the designed focused beams provide a new degree of freedom to mitigate interference in both angle and distance domains, which is not achievable using conventional far-field beam steering, allowing reliable communications for uses even residing at the same angular direction.

Recently, dynamic metasurface antennas (DMAs) have emerged as a promising technology for realizing massive multiple-input multiple-output (MIMO) wireless systems. The usage of large arrays, jointly with higher transmitted frequencies, often results in the communicating devices operating in the near-field (Fresnel) region, thus requiring different considerations compared to traditional systems, assumed to operate in the far-field regime. In this paper, we study the potential of beam focusing, feasible in near-field operation, for multi-user MIMO systems, where the base station is equipped with a DMA. We introduce a mathematical model for DMA-based near-field MIMO communications. Then, we characterize the sum-rate maximization problem of the considered system, and propose an efficient solution to jointly design the DMA weights and digital precoding vector. Simulation results show that our design generates focused beams such that users residing at the same angular direction can communicate reliably without interfering, which is not achievable using conventional far-field beam steering.

In this paper, we present a low-latency direction assisted channel estimation algorithm suitable for millimeter wave (mm-Wave) systems. First, during the beam training procedure, we perform angle of departure (AoD) and angle of arrival (AoA) measurements with their corresponding variances and based on them, we design both downlink and uplink beams. We then perform signal measurements with these beams and accordingly design the sensing matrix, while also iteratively refining the angle estimation and the beams for the next measurements accordingly. Finally, exploiting both the sparseness and the intrinsic geometric nature of the mm-Wave channel, we apply compressive sensing tools so as to complete the estimation procedure. Simulations show that the corresponding estimation error decreases rapidly in comparison with other conventional approaches.

In this paper, we consider a multi-user multiple-input multiple-output (MIMO) system aided by multiple intelligent reflecting surfaces (IRSs) that are deployed to increase the coverage and, possibly, the rank of the channel. We propose an optimization algorithm to configure the IRSs, which is aimed at maximizing the network sum-rate by exploiting only the statistical characterization of the locations of the mobile users. As a consequence, the proposed approach does not require the estimation of either instantaneous channel state information (CSI) or second-order channel statistics for IRS optimization, thus significantly relaxing (or even avoiding) the need of frequently reconfiguring the IRSs, which constitutes one of the most critical issues in IRS-assisted systems. Numerical results confirm the validity of the proposed approach. It is shown, in particular, that IRS-assisted wireless systems that are optimized based on statistical position information still provide large performance gains as compared to the baseline scenarios in which no IRSs are deployed.

We study a millimeter wave (mm-wave) wireless network deployed along the roads of an urban area, to support localization and communication services simultaneously for outdoor mobile users. In this network, we propose a mm-wave initial beam-selection scheme based on localization-bounds, which greatly reduces the initial access delay as compared to traditional initial access schemes for standalone mm-wave small cell base station (BS). Then, we introduce a downlink transmission protocol, in which the radio frames are partitioned into three phases, namely, initial access, data, and localization, respectively. We establish a trade-off between the localization and communication performance of mm-wave systems, and show how enhanced localization can actually improve the data-communication performance. Our results suggest that dense BS deployments enable to allocate more resources to the data phase while still maintaining appreciable localization performance. Furthermore, for the case of sparse deployments and large beam dictionary size (i.e., with thinner beams), more resources must be allotted to the localization phase for optimizing the rate coverage. Based on our results, we provide several system design insights and dimensioning rules for the network operators that will deploy the first generation of mm-wave BSs.

In this paper, we put forth the idea of metaprism, a passive and non-reconfigurable metasurface acting as a metamirror with frequency-dependent reflecting properties within the bandwidth of the signal. We show that, with an appropriate design of the metaprism, it is possible to control that each data stream in an orthogonal frequency division multiplexing (OFDM) system is reflected in the desired direction by properly assigning subcarriers to users without the need of control channels and dedicated channel state information (CSI) estimation schemes. Furthermore, the metaprism can also be designed so that it focuses the signal towards a specific position depending on the subcarrier, provided that the user is in the near-field region of the metaprism, with consequent path-loss reduction. A critical discussion is also presented about the path-loss reduction obtainable from metaprisms and, more generally, from metasurfaces. The numerical results show that this solution is effective in extending the coverage in areas experiencing severe non line-of-sight (NLOS) channel conditions, thus making it an interesting alternative to reconfigurable metasurfaces when low-cost, no energy consumption, and backward compatibility with existing wireless standards are required.

Next 5G and beyond applications have attracted a tremendous interest towards systems using antenna arrays with an extremely large number of antennas where the technology conceived for communication might also be exploited for high-accuracy positioning applications. In this paper, we investigate the possibility to infer the position of a single antenna transmitter using a single asynchronous receiving node by retrieving information from the incident spherical wavefront. To this end, we consider the adoption of a suitable mix of processing at electromagnetic (EM) and signal levels, as a lower complexity alternative to classical massive array systems where the processing is done entirely at signal level. Thus, we first introduce a dedicated general model for different EM processing architectures, entailing the use or not of a lens that can have either a reconfigurable or a fixed phase profile, and successively we investigate their attainable positioning performance. The effect of the interference is also investigated to evaluate the robustness of the considered system to the presence of multiple simultaneous transmitting sources. Results, obtained for different apertures of the exploited lens/array, confirm the possibility to achieve interesting positioning performance using a single antenna array with a limited aperture.

This paper analyzes the fundamental communication problem involving large intelligent surfaces (LIS) starting from electromagnetic (e.m.) arguments. Since the numerical solution of the corresponding optimal eigenfunction problem is in general computationally prohibitive, simple but accurate analytical expressions for the link gain and available degrees-of-freedom (DoF) are derived. It is shown that the achievable DoF and gain offered by the wireless link are determined only by geometric factors, and that the classic Friis' formula is no longer valid in this scenario where the transmitter and receiver could operate in the near-field regime. Furthermore, results indicate that, contrarily to classic MIMO systems, when using LIS more than one DoF might be available in strong line-of-sight (LOS) channel conditions, which corresponds to a significant increase of spatial capacity density.

Next 5G of mobile wireless systems is expected to employ mmWave antenna arrays at both user-equipment (UE) and base station (BS) side, with the possibility to precisely focus the power on the desired spatial directions and boost communications-based applications at an unprecedented scale. On the other side, the initial access (IA) procedure might entail a high latency due to the need of the BS to scan the surrounding space in order to detect new UEs. In this paper we consider a stand-alone 5G system capable to exploit the memory of past UEs detection to speed-up the IA process for new UEs entering the area. In particular, it considers the creation of a knowledge database that accounts for the UE received power and for both the beamsteering and half power beamwidth (HPBW) set at the BS. Numerical results show that the proposed procedure allows to reduce the average number of scans with respect to traditional approaches adopted in the literature, while preserving the same detection performance.

This paper analyzes the optimal communication involving large intelligent surfaces (LIS) starting from electromagnetic arguments. Since the numerical solution of the corresponding eigenfunction problems is in general computationally prohibitive, simple but accurate analytical expressions for the link gain and available spatial degrees-of-freedom (DoF) are derived. It is shown that the achievable DoF and gain offered by the wireless link are determined only by geometric factors, and that the classical Friis' formula is no longer valid in this scenario where the transmitter and receiver could operate in the near-field regime. Furthermore, results indicate that, contrarily to classical MIMO systems, when using LIS-based antennas DoF larger than 1 can be exploited even in strong line-of-sight (LOS) channel conditions, which corresponds to a significant increase in spatial capacity density, especially when working at millimeter waves.

Localisation algorithms based on the estimation of the time-of-arrival of the received signal are particularly interesting when ultra-wide band (UWB) signaling is adopted for high-definition location aware applications. In this context non-line-of-sight (NLOS) propagation condition may drastically degrade the localisation accuracy if not properly recognised. We propose a new NLOS identification technique based on the analysis of UWB signals through supervised and unsupervised machine learning algorithms, which are typically adopted to extract knowledge from data according to the data mining approach. Thanks to these algorithms we can automatically generate a very reliable model that recognises if an UWB received signal has crossed obstacles (NLOS situation). The main advantage of this solution is that it extracts the model for NLOS identification directly from example waveforms gathered in the environment and does not rely on empirical tuning of parameters as required by other NLOS identification algorithms. Moreover experiments show that accurate NLOS classifiers can be extracted from measured signals either pre-classified or unclassified and even from samples algorithmically-generated from statistical models, allowing the application of the method in real scenarios without training it on real data.

Consensus among different entities is a fundamental feature of distributed systems, as it is the prerequisite for complex tasks such as distributed coordination of autonomous agents, network synchronization and localization in wireless sensor networks (WSNs). This paper introduces a novel iterative algorithm which is capable of achieving the distributed average consensus in a finite amount of time. This algorithm exploits the possibility of storing information received from neighboring nodes at each iteration. Moreover, we propose an adaptation to the distributed average consensus problem of the Tagged and Aggregated Sums (TAS) algorithm, which we introduced in a previous paper for the distributed confidence region evaluation. The performance of both algorithms is investigated through simulation and compared with state-of-the-art approaches.

In this paper, we propose optimal beamforming strategies for a millimeter wave (mmWave) system consisting of multiple users based on the localization performance bounds. We consider a single base station (BS) with prior coarse knowledge of the users' positions and formulate the optimal beamforming problem in order to minimize the localization error consisting of Cramer Rao Lower Bounds (CRLBs) of delay, angle of departure (AoD) and angle of arrival (AoA) estimation at the mobile users. We first formulate the simplified CRLB of estimation parameters, taking advantage of multiple sub-carriers, and then formulate the localization error for optimization of the beamformer. Finally, we evaluate the resulting position and orientation error bounds after optimization for several fairness strategies through Monte Carlo simulations.

We analyze a millimeter wave network, deployed along the streets of a city, in terms of positioning and downlink data-rate performance, respectively. First, we present a transmission scheme where the base stations provide jointly positioning and data-communication functionalities. Accordingly, we study the trade- off between the localization and the data rate performance based on theoretical bounds. Then, we obtain an upper bound on the probability of beam misalignment based on the derived localization error bound. Finally, we prescribe the network operator a scheme to select the beamwidth and the power splitting factor between the localization and communication functions to address different quality of service requirements, while limiting cellular outage.

In the next generation of cellular networks, it is desirable to use single access points both for communication and localization. This could be made possible thanks to the combination of femtocells, mm-wave technology and massive antenna arrays, and would overcome the problem of having an over-sized infrastructure for positioning which is, nowadays, the bottleneck for the widespread diffusion of indoor localization systems. In this context, our paper aims at investigating the localization and orientation performance limits employing massive arrays both at the access point and mobile side. To this end, we first asymptotically demonstrate the tightness of the Cramér-Rao bound (CRB) in the massive array regime and that the effect of multipath can be made negligible even for practical values of SNR levels. Successively, we propose a comparison between two different transmitter configurations, namely multiple-input multiple-output (MIMO), where orthogonal waveforms are sent, and beamforming, which takes advantage of highly correlated waveforms and directive array patterns. We also consider random weighting as a trade-off between the diversity gain of MIMO and the high directivity guaranteed by the beamforming. CRB results show the interplay between diversity and beamforming gain as well as the benefits achievable by varying the number of antennas in terms of localization accuracy and multipath mitigation.

In localization tasks, one typically assumes a statistical model of the observations, where the model quantifies the observations by exploiting interrelationships based on geometry. These models might incorporate unknown parameters that, in general, are functions of space. In this article, we propose a crowd sensing method for estimating a spatial field of a quantity (e.g., ranging biases due to line-of-sight/non-line-of-sight or path-loss parameter) allowing for improved indoor localization. Our method takes advantage of the information provided by various users that navigate the area of interest. The proposed learning approach is based on Gaussian processes and its computational cost does not increase with the number of measurements. We present numerical results that show how the proposed method estimates a spatial field of biases and how these estimates lead to much improved performance in estimation of user positions.

The presence of obstacles between a mobile user and the serving access point might determine frequent link blockages that could be expensive in terms of signaling caused by handovers and antenna beamforming, especially in the perspective of millimeter wave communications. In this paper, an analytical framework to characterize the statistics of the link lifetime of a moving user in the presence of random obstacles with different sizes is derived for two different mobility models. Using statistical geometry arguments, closed-forms of the cumulative distribution function and the average link lifetime are obtained as a function of the distance, user's speed and direction, obstacles' density and size. The analytical framework is validated through simulations and allows to get insights on the impact of system parameters on the link lifetime.

Getting confidence regions for parameter estimates obtained from data collected by a wireless sensor network (WSN) is very important to assess the performance of the estimator. The sign perturbed sums (SPS) approach has been proposed recently to defined exact confidence regions in a centralized setting even if only few measurements are available. SPS may be distributed to get confidence regions at each node of a WSN. This paper investigates a data dissemination strategy called Tagged and Aggregated Sums (TAS), exploiting the particularities of SPS, to efficiently provide each node with the information necessary to evaluate locally the confidence region. TAS and flooding (FL) algorithms have been investigated through simulations and then implemented on commercial sensor nodes. The impact of collision avoidance mechanisms at the medium access control (MAC) layer is also experimentally assessed. Performance comparisons show that TAS outperforms FL in structured networks.1

This paper considers a delay tolerant network consisting of nodes equipped with sensors, some of them producing outliers. A distributed faulty node detection (DFD) algorithm, whose aim is to help each node in estimating the status of its sensors, has been proposed recently by the authors. The aim of this paper is to analyze the robustness of the DFD algorithm to the presence of misbehaving nodes performing Byzantine attacks. Two types of attacks are considered and analyzed, each trying to mislead the other nodes in the estimation of the status of their sensors. This provides insights on the way the parameters of the DFD algorithm should be adapted to minimize the impact of misbehaving nodes. Theoretical results are illustrated with simulations considering nodes with random displacements, as well as traces of node inter-contact times from real databases.

Presents comments on the paper, “Personal mobile radars with millimeter-wave massive arrays for indoor mapping,” (Guidi, F. et al), IEEE Trans. Mobile Comput., vol. 15, no. 6, pp. 1471–1484, Jun. 2016.

This paper presents a new analytical framework based on stochastic geometry for the characterization of the reciprocal impact of device-to-device (D2D) communications and an underlaid cellular network in terms of coverage probability. We consider a random number of D2D groups, where the devices of each group are distributed according to different spatial distributions to model users' behavior. The effect of power control, users' spatial distribution, shadowing and random base station deployment are accounted for in the analysis and closed form expressions for coverage probability for both cellular and D2D networks are derived. The validity of the framework developed is assessed via simulation in the numerical results, where the effect of key system parameters as well as device spatial distribution on cellular and D2D coverage is investigated and the amount of traffic that could be offloaded through D2D communications is studied.

The adoption of massive arrays for simultaneous localization and mapping or personal radar applications enables the possibility to detect and localize surrounding objects through an accurate beamforming procedure. Unfortunately, when a classical constant false alarm rate approach accounting for ideal-pencil beam pattern is adopted, ambiguities in signal detection could arise due to the presence of side-lobes which can cause non-negligible errors in target detection and ranging. To counteract such effect, in this paper we propose a joint threshold-array design approach, where the antenna characteristics are taken into account to best set the threshold and to guarantee the desired detection and ranging performance at the non-coherent receiver section. In order to consider realistic arrays impairments, we focus our attention on the number of antenna elements and of phase shifter bits used for beamforming as key players in defining a trade-off between structural complexity, well-defined radiation pattern, and localization performance. Simulation and measurement results show that the number of bits per phase shifter can be relaxed in favor of a simpler array design, if the number of antennas is sufficiently high and the side-lobes are kept within a suitable level allowing a desired robustness to interference signals.

The adoption of millimeter-wave technology could open the possibility to integrate massive antenna arrays inside future 5G user mobile devices, with the possibility to enable new interesting applications. Within this context, in this paper we put forth the concept of a personal mobile radar operating at millimeter-waves and consisting of a massive array for accurate environmental mapping. Frequency selectivity and phase quantization effects are accounted for to characterize the achievable angle and range resolution necessary to collect environmental information. Successively, we propose an effective grid-based Bayesian mapping approach by introducing a new state-space model, which profits of the beneficial effects of the massive antenna array characteristics. Numerical results show that the idea herein investigated is feasible, and that a significant mapping performance is attainable even employing coarse antenna arrays provided that the number of antenna elements is sufficiently high.

This paper studies the impact of a device-to-device (D2D) communication on the downlink coverage of an overlaid cellular network. To limit the interference created by D2D users, and other base stations, typically power control is adopted counteracting the path loss and shadowing effects in each link. However this does not prevent cellular user from experiencing coverage limitation. Therefore we develop an analytical model to characterize the coverage probability of cellular networks in the presence of a D2D link accounting for shadowing, power control and users random locations. We assume the deployment of base stations and mobile stations are based on a Poisson point process. Finally, to validate our model, we compare our theoretical analysis with simulation results.

To guarantee its integrity, a wireless sensor network needs to efficiently detect faulty nodes producing erroneous measurements. This paper proposes a fully distributed fault detection algorithm. A node first collects the measurements of its neighborhood, processes them to decide whether they contain outliers, and broadcasts the result. Then, it decides autonomously about its functioning status. The detection algorithm is proposed in two variants, depending on the proportion of faulty nodes in the network. A theoretical analysis of the probability of error and of the convergence of the algorithm is provided. The tradeoff between false alarm probability and detection probability is characterized using simulation.

Wireless channel reciprocity can be exploited by two users willing to achieve confidential communications over a public channel as a common source of randomness for the generation of a secret key. This paper presents an analytical framework for investigating the amount of secret information that characterizes wireless multi-dimensional Gaussian channels used as source of randomness. The intrinsic secrecy content of wide-sense stationary wireless channels in frequency, time and spatial domains is derived through asymptotic analysis. Some significant case studies are presented, where single and multiple antenna eavesdroppers are considered. In the numerical results, the role of signal-to-noise ratio, spatial correlation, frequency and time selectivity, sampling frequency and imperfect channel reciprocity is investigated.

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.

Wireless channel reciprocity can be successfully exploited as a common source of randomness for the generation of a secret key by two legitimate users willing to achieve confidential communications over a public channel. This paper presents an analytical framework to investigate the theoretical limits of secret-key generation when wireless multi-dimensional Gaussian channels are used as source of randomness. The intrinsic secrecy content of wide-sense stationary wireless channels in frequency, time and spatial domains is derived through asymptotic analysis as the number of observations in a given domain tends to infinity. Some significant case studies are presented where single and multiple antenna eavesdroppers are considered. In the numerical results, the role of signal-to-noise ratio, spatial correlation, frequency and time selectivity is investigated.

This paper establishes sufficient conditions under which a memoryless channel with real, scalar and peak power limited input exhibits a capacity achieving input probability measure that is discrete with a finite number of probability mass points. A proof for the sufficiency of the proposed conditions is presented. Some examples are also illustrated as further evidence for the presented theory.

We consider the secret key generation (SKG) problem for short-range communication (SRC) systems. Specifically, we focus on the problem that secret key generation schemes relying on the entropy of the channel are not suitable for SRC systems, which are characterized by the absence of fading. To mitigate this problem, we introduce the concept of geometric secrecy and propose a new phase-based SKG which relies only on the reciprocity of the channel in order to securely generate mutual secret keys in the presence of an eavesdropper. The method is validated via a theoretical analysis which shows that for the signal-to-noise ratio (SNR) ranges typical of SRC systems, an efficient secret key generation can be achieved.

In this paper we propose a wireless sensor network (WSN) designed for landslides monitoring and risk management. The WSN is self-organizing, has fault tolerance capabilities, and its behavior is driven by the events to be monitored, to guarantee fast deployment, robustness in harsh environments, and very long lifetime. Data collected by sensors are delivered through the network to a remote unit (RU) for on-line analysis and alerting. The WSN has been installed on a landslide located in Torgiovannetto (Italy) for an experimental campaign of several months where performance metrics, such as path statistics and battery levels, have been collected. These metrics demonstrate the effectiveness of the network protocols to manage self-organization, node failures, low link quality and unexpected battery depletion. With negligible human intervention during the pilot experiment the WSN revealed a very high level of robustness, which makes it suitable to monitor landslides in critical scenarios.

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.

A new communication paradigm, namely piggyback communication, is introduced. The founding principle of piggyback communication is to recycle source of opportunity (SoO) signals, already available in the surrounding environment for other services, to establish short-range passive radio links between a certain number of wireless nodes and a receiver without the injection of additional power in the environment, thus achieving close zero-power wireless communications.

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.

Theoretical limits on time-of-arrival (equivalently, range) estimation are derived for multicarrier systems in the presence of interference. Specifically, closed-form expressions are obtained for Cramer-Rao bounds (CRBs) in various scenarios. In addition, based on CRB expressions, an optimal power allocation (or, spectrum shaping) strategy is proposed. This strategy considers the constraints not only from the sensed interference level but also from the regulatory emission mask. Numerical results are presented to illustrate the improvements achievable with the optimal power allocation scheme, and a maximum likelihood time-of-arrival estimation algorithm is studied to assess the effects of the proposed approach in practical estimators.

In this paper, we address the problem of the estimation of a spatial field defined over a two-dimensional space with wireless sensor networks. We assume that the field is (spatially) bandlimited and that it is sampled by a set of sensors which are randomly deployed in a given geographical area. Further, we impose a total bandwidth constraint which forces the quantization error in the sensor-to-FC (Fusion Center) channels to depend on the actual number of sensors in the network. With these assumptions, we derive an analytical expression of the mean-square error (MSE) in the reconstructed random field and, on that basis, an approximate closed-form expression of the optimal sensor density which attains the best trade-off in terms of observation, sampling and quantization noises. The analysis is carried out both in Gaussian and Rayleigh-fading scenarios without transmit Channel State Information (CSI). For the latter scenario, we also derive an expression of the common and constant rate at which the observations must be quantized. Computer simulation results illustrate the dependency of the optimal operating point on the variance of the observation noise or the signal-to-noise ratio in the sensor-to-FC channels, as well as the scaling law of the reconstruction MSE (which is also derived analytically) for both scenarios.

We consider an environmental monitoring application where a scalar field (e.g., atmospheric pressure) is to be sensed by randomly distributed nodes. Each node takes a sample of a l-dimensional signal in its position and sends it to a collector entity through a wireless link. The latter performs signal reconstruction based on the received samples. Because of total bandwidth constraints, the transmission rate per node is limited. Hence, sensors are supposed to reduce the amount of information to be sent through quantization of the measurements. On the one hand, an increased amount of nodes deployed results in a more accurate sampling of the signal. On the other hand, it forces each sensor to perform looser quantization to cope with the smaller fraction of bandwidth allocated. From the theory of random sampling and by accounting for quantization, we compute the mean square error (MSE) in the reconstruction of the original signal. We then show the existence of an optimal deployment density that trades off between quantization error and aliasing error due to random sampling.

The architecture of a digital On-Channel Repeater (OCR) for DVB-T/H signals is described in this paper. The presence of a coupling channel between the transmitting and the receiving antennas gives origin to one or more echoes, having detrimental effects on the quality of the repeated signal and critically affecting the overall system stability. A low-complexity echo canceller unit is then proposed, performing a coupling channel estimation based on the local transmission of low-power training signals. In particular, in this paper we focus on the stability issues which arise due to the non perfect echo cancellation. An upper bound on the probability of instability of the system is analytically found, providing useful guidelines for conservative OCR design, and some performance figures concerning different propagation scenarios are provided.

Future advanced radio-frequency identification (RFID) systems are expected to provide both identification and high-definition localization of objects with improved reliability and security while maintaining low power consumption and cost. Ultrawide bandwidth (UWB) technology is a promising solution for next generation RFID systems to overcome most of the limitations of the current narrow bandwidth RFID technology such as: reduced area coverage, insufficient ranging resolution for accurate localization, sensitivity to interference, and scarce multiple-access capability. In this paper, a survey of current progress in the application of the UWB technology for RFID systems is presented with particular attention to low-complexity solutions for high-definition tag localization.

Over the coming decades, high-definition situationally-aware networks have the potential to create revolutionary applications in the social, scientific, commercial, and military sectors. Ultrawide bandwidth (UWB) technology is a viable candidate for enabling accurate localization capabilities through time-of-arrival (TOA)-based ranging techniques. These techniques exploit the fine delay resolution property of UWB signals by estimating the TOA of the first signal path. Exploiting the full capabilities of UWB TOA estimation can be challenging, especially when operating in harsh propagation environments, since the direct path may not exist or it may not be the strongest. In this paper, we first give an overview of ranging techniques together with the primary sources of TOA error (including propagation effects, clock drift, and interference). We then describe fundamental TOA bounds (such as the CramÉr–Rao bound and the tighter Ziv–Zakai bound) in both ideal and multipath environments. These bounds serve as useful benchmarks in assessing the performance of TOA estimation techniques. We also explore practical low-complexity TOA estimation techniques and analyze their performance in the presence of multipath and interference using IEEE 802.15.4a channel models as well as experimental data measured in indoor residential environments.

We discuss the correctness of one of the main results of about the probability density function of the distance between two audible nodes in an infinite 2-dimensional scenario. We prove that result is wrong and derive a more general expression, which is valid for an infinite d-dimensional area. It is worth noting that, although the results on the distribution of the distance between two nodes are wrong, the other results and in particular the fact that the number of audible nodes in an arbitrary area is a Poisson r.v. is correct.

Ultrawide bandwidth (UWB) technology is a promising solution for next generation radiofrequency identification (RFID) systems to overcome most of the main limitations of current RFID systems such as very short operating range, insufficient ranging resolution for accurate localization, sensitivity to interference and scarce multiple access capability. In this paper, the UWB technology is applied to (semi-)passive RFID based on backscatter modulation and the potential performance is investigated in terms of range/data rate trade-off and clutter effect mitigation using experimental data.

We propose a new approach to evaluate the ultimate performance limit of time synchronization in wireless sensor networks based on the estimation theory. In particular the lower bound on the variance of the average synchronization error in a fully connected network is derived by taking into account the statistical characterization of the message delivering time.

The need for accurate positioning has gained significant interest recently, especially in cluttered environments where signals from satellite navigation systems are not reliable. Positioning systems based on ultrawide bandwidth (UWB) technology have been considered for these environments because UWB signals are able to resolve multipath and penetrate obstacles. These systems usually obtain range measurements from time-of-arrival (TOA) estimation of the first path, which can be a challenge in dense multipath environments. In this paper, we analyze and compare the performance of matched filter (MF) and energy detector (ED) TOA estimators based on thresholding in UWB dense multipath channels. The main advantage of threshold-based estimators is that they have the potential for complete analog implementation and hence they are particularly attractive for applications that require low cost battery-powered devices. Closed-form expressions for the estimator bias and mean square error (MSE) are derived as a function of the signal- to-noise ratio. A comparison with results obtained from Monte Carlo simulation confirms the validity of our analytical approach. This analysis enables us to determine the threshold value that minimizes the MSE, a critical parameter for optimal estimator design. A simple criteria to determine the threshold value is also presented. It is shown that the estimation accuracy is mainly affected by the ambiguity in the selection of the correct peak at the output of the MF or ED, caused by the fading characteristics of the first path. We also evaluate the performance loss of ED estimators with respect to MF estimators. Finally, results based on experimental measurements in an indoor residential environment are presented in order to compare the performance of TOA estimators in realistic environments.

Abstract This paper investigates the impact of diversity reception on the performance of Bluetooth (BT) packet transmission in wireless channels with fast fading and shadowing and in the presence of IEEE802.11g interference. In particular, selection diversity (SD) technique is considered and the adoption of this technique results in a coverage extension evaluated in the paper. We first derive a tight parametric exponential approximation for the instantaneous bit error probability (BEP) in additive white Gaussian noise (AWGN); then, from this expression, we derive the mean block error probability (BLEP) in Ricean fading channel by adopting a simple SD scheme. The analysis is then extended to the evaluation of the mean packet error probability (PEP) and the coverage probability (Pcov). In particular, the impact of the diversity order on the BLEP, PEP, andPcovis shown. Copyright © 2007 John Wiley & Sons, Ltd.

In this paper the problem of evaluating the statistics of the connected nodes position in a multi-hop wireless random ad hoc network is addressed. In particular, an analytical model and closed-form expressions for the distribution of the connected nodes position distribution and the probability of coverage, given a maximum number of tolerable hops, are derived. The presence of randomness in the propagation, such as shadowing effects, is accounted for in a general way. The validity of the model is confirmed by simulation results. The impact of the channel randomness on the position distribution as well as on the coverage characteristics is investigated in the numerical results.

Decentralized detection in a network of wireless sensor nodes involves the fusion of information about a phenomenon of interest (PoI) from geographically dispersed nodes. In this paper, we investigate the problem of binary decentralized detection in a dense and randomly deployed wireless sensor network (WSN), whereby the communication channels between the nodes and the fusion center are bandwidth-constrained. We consider a scenario in which sensor observations, conditioned on the alternate hypothesis, are independent but not identically distributed across the sensor nodes. We compare two different fusion architectures, namely, the parallel fusion architecture (PFA) and the cooperative fusion architecture (CFA), for such bandwidth-constrained WSNs, where each sensor node is restricted to send a I-bit information to the fusion center. For each architecture, we derive expression for the probability of decision error at the fusion center. We propose a consensus flooding protocol for CFA and analyze its average energy consumption. We analyze the effects of PoI intensity, realistic link models, consensus flooding protocol, and network connectivity on the system reliability and average energy consumption for both fusion architectures. We demonstrate that a trade-off exists among spatial diversity gain, average energy consumption, delivery ratio of the consensus flooding protocol, network connectivity, node density, and Poll intensity in CFA. We then provide insight into the design of cooperative WSNs.

In this paper, the estimation of a scalar field over a bidimensional scenario (e.g., the atmospheric pressure in a wide area) through a self-organizing wireless sensor network (WSN) with energy constraints is investigated. The sensor devices (denoted as nodes) are randomly distributed; they transmit samples to a supervisor by using a clustered network. This paper provides a mathematical framework to analyze the interdependent aspects of WSN communication protocol and signal processing design. Channel modelling and connectivity issues, multiple access control and routing, and the role of distributed digital signal processing (DDSP) techniques are accounted for. The possibility that nodes perform DDSP is studied through a distributed compression technique based on signal resampling. The DDSP impact on network energy efficiency is compared through a novel mathematical approach to the case where the processing is performed entirely by the supervisor. The trade-off between energy conservation (i.e., network lifetime) and estimation error is discussed and a design criterion is proposed as well. Comparison to simulation outcomes validates the model. As an example result, the required node density is found as a trade-off between estimation quality and network lifetime for different system parameters and scalar field characteristics. It is shown that both the DDSP technique and the MAC protocol choice have a relevant impact on the performance of a WSN.

Transmitted-Reference (TR) signaling, in conjunction with an autocorrelation receiver (AcR), offers a low- complexity alternative to Rake reception in ultrawide bandwidth systems. This paper provides a unified performance analysis of various TR schemes by developing an analytical framework based on the sampling expansion approach. Specifically, we derive the uncoded bit error probability (BEP) of different TR signaling schemes, including TR and differential TR (DTR) signaling valid for a broad class of fading channels. We consider both AcRs and modified AcRs with noise averaging. We further develop a quasi-analytical method as well as an approximate analytical method to extend the BEP analysis to include the effect of narrowband interference (NBI). We show that the approximate analytical method is particularly useful in obtaining BEP expressions that provide insight into the effect of NBI. We quantify the effects of NBI and channel power dispersion profile on the optimum integration interval of an AcR. Finally, we compare TR and DTR signaling in terms of their sensitivity to NBI.

In this paper we put forth a simple threshold-based time-of-arrival (ToA) estimator and analyze its performance in ultra-wide bandwidth (UWB) dense multipath channels. Closed-from expressions for the estimator bias and mean square error are derived as a function of signal-to-noise ratio (SNR), overcoming the limitation of conventional asymptotic analysis valid only for high SNR. A comparison with results based on Monte Carlo simulation as well as those based on experimental measurements in an office environment confirms the validity of our analytical approach. Our analysis enables us to determine the threshold value that minimizes the mean-square error, critical parameter for optimal estimator design. It is shown that the estimation accuracy mainly depends on large estimation errors due to peak ambiguities at the output of the correlator and on the fading statistics of the first path.

This paper investigates time of arrival (ToA) estimation methods for ultra-wide bandwidth (UWB) propagation signals. Different algorithms are implemented in order to detect the direct path in a dense multipath environment. In particular, suboptimal low-complex techniques based on peak detection are used to deal with partial overlap of signal paths. A comparison in terms of ranging accuracy, complexity, and parameters sensitivity to propagation conditions is carried out also considering a conventional technique based on threshold detection. The algorithms are tested on experimental data collected from a measurement campaign performed in a typical office building.

Range-only localization techniques in dense cluttered environments typically lack accuracy due, notably, to partial and complete line-of-sight (LOS) blockage. Furthermore, the quality of the range measurements degrades with distance, and the geometric configuration of the beacons also affects the localization accuracy. In this paper we derive a fundamental limit of localization accuracy for an ultra-wide bandwidth (UWB) system operating in such environments, which we call the Position Error Bound (PEB). The impact of different ranging estimation errors due to beacons distance and biases on the best positioning accuracy is investigated. The statistical characterization of biases coming from measurement campaigns can easily be incorporated into this analysis. We show that the relative importance of information coming from different beacons varies depending on the propagation conditions, such as whether the beacon is LOS or non-line-of-sight (NLOS). We show in particular that NLOS beacons can significantly improve the localization accuracy compared to the case when they are not considered, especially in dense cluttered environments.

Decentralized detection in a network of wirelesensor sensor nodes involves the fusion of information about a phenomenon of interest (POI) from geographically dispersed nodes. In this paper, we investigate a binary decentralized detection problem in a dense wireless sensor network. We consider a scenario in which sensor observations, conditioned on the alternate hypothesis, are independent but not identically distributed across the sensor nodes. We consider two different fusion architectures, namely, the parallel fusion architecture and the cooperate fusion architecture. For each architecture, we derive expressions for the probability of decision error at the fusion center. We analyze the impact of a realistic sensing model, and flooding protocol on the system reliability and energy consumption for both architectures. We demonstrate that a trade-off exists among spatial diversity gain, average energy consumption, node density, and POI intensity in the cooperative architecture.

Decentralized detection in a network of wireless sensor nodes involves the fusion of information about a phenomenon of interest (POI) from geographically dispersed sensor nodes. In this paper, we investigate a binary decentralized detection problem in a dense wireless sensor network (WSN). We assume that the strength of the POI varies spatially. We consider a fusion architecture which allows cooperation among the nodes. In order to allow the nodes to cooperate, we propose a consensus flooding protocol and analyze the average energy consumption when cooperation is present. Unlike similar works, we analyze the effect of a realistic sensing model, flooding protocol and network connectivity on the system reliability and energy consumption. We demonstrate that a trade-off exists among spatial diversity gain, average energy consumption, delivery ratio of the flooding protocol, network connectivity, node density, and POI intensity in the cooperative architecture. Consequently, we are able to determine when the additional performance gain provided by cooperation outweighs the increase in average energy consumption required to cooperate.

In this work we propose an analytical framework aiming at studying the coexistence issue between Bluetooth (BT) and IEEE802.11g in fading channels. With the goal to improve the BT performance in the presence of interference, we consider a non coherent selection diversity (SD) scheme at the receiver side. In fact, due to its simplicity, the SD scheme is fully compliant with the low-cost requirement of BT equipped devices. Through the analysis, we derive the BT performance in terms of packet error probability averaged over Ricean fading when IEEE802.11g acts as interferer, taking into account all physical and medium access control (MAC) aspects. Results show the performance improvement and the reduction of the minimum coexistence distance due to the adoption of the simple SD receiving scheme

The paper address the coexistence of Bluetooth (BT) and IEEE802.11g systems. The interference on BT is analytically evaluated as well as the performance when diversity reception in Ricean fading is considered. We firstly derive the expression of the mean block error probability in the presence of interference, then we extend the analysis to the mean packet error probability and to the coexistence distance. Due to multiple receiving antennas, results show the not negligible performance improvement and the reduction of the minimum coexistence distance.

In this paper we present the results of an intensive experimental campaign performed at IEIIT-BO/CNR, Bologna, Italy, on an indoor localization system based on wireless sensors network. Received signal strength indications have been measured and collected using real devices. The data serve as an input data-base for an off-line investigation of different localization techniques. This enables us on one side to improve location accuracy through propagation model tuning, on the other side to compare different location algorithms in term of complexity and performance. Results of these optimizations and comparisons are presented in this paper

An analytical framework for the performance evaluation of a dense energy-efficient wireless sensor network (WSN), enabling distributed collaborative environment monitoring, is developed. We address the estimation of a target multidimensional process by means of samples captured by nodes randomly and uniformly distributed and transmitted to a collector through a self-organizing clustered network. The estimation in the presence and in the absence of collaborative signal processing with different types of data interpolators are compared in terms of both process estimation error and network life-time. Our analytical model, aimed at providing useful information for WSN design, takes many aspects into account, such as distance-dependent path loss and shadowing, energy consumption, information routing, process estimation quality, node density, transmission protocol and system parameters. As an example result, fixing requirements on estimation errors and network life-time, the node density is found as a function of the system/protocol parameters.

Future wireless video transmission systems would consider OFDM (orthogonal frequency division multiplexing) as basic modulation technique due to its robustness and low complexity implementation in the presence of frequency selective channels. Recently, adaptive bit loading techniques have been applied to OFDM showing good performance gains in cable transmission systems. In this paper adaptive loading techniques are applied to an OFDM wireless system in the 5 GHz band for efficient layered multimedia traffic transmission. A low complexity scheme is introduced and compared with other solutions to realize unequal error protection both at coding and modulation level. The large impact of this technique in terms of video quality is evaluated for MPEG-4 video transmission.

This paper investigates the impact of diversity reception techniques on the performance of Bluetooth (BT) packet transmission in fading channels. We firstly derive a tight parametric exponential approximation for the bit error probability in additive white Gaussian noise depending on GFSK modulation parameters according to the BT standard. Then, from this expression we derive the mean block error probability (BLEP) for DH packets transmission in Rayleigh fading channel by adopting different diversity reception techniques, such as selection diversity and maximal ratio combining (MRC). In particular, the impact of the diversity order and combining techniques on the BLEP is shown. For the MRC technique, we also obtain a tight bound on the BLEP. Furthermore, we extend the results for MRC to Nakagami-m fading and we obtain the parameters of exponential approximation for a general GFSK modulation, although out of BT standard, showing their impact on both the performance and spectrum.

In this paper a low complexity and low overhead adaptive bit loading algorithm for wireless multicarrier schemes is proposed and analyzed. It is based on the diversity gain obtained through the ordering and selection of the more reliable subcarriers. Higher-order modulations are used to compensate for the reduced subcarrier utilization. On the contrary to other bit loading algorithms, it does not require non uniform bit and power level allocation among subcarriers, thus drastically reducing the modem hardware complexity and making it attractive as a possible extension of existing high speed WLAN standards. System performance is analyzed in different configurations and conditions, including a realistic 5 GHz propagation scenario. Comparison with optimal adapted and unadapted solutions is also made. Finally, the effect of unideal feedback of the channel state information is analyzed showing the robustness and the low overhead requirement of the new scheme.

This paper addresses indoor localization techniques through ad-hoc wireless networks, where anchors and unknown nodes are randomly positioned in a squared area. The position of unknown nodes is estimated starting from received signal strength (RSSI) measurements, since nodes are assumed to be not equipped with specialized localization hardware. The possibility to perform power measurements among any couple of nodes (either anchors or unknown nodes) enables the exploitation of collaborative localization techniques. In this case, the complexity of the optimum maximum likelihood (ML) technique becomes too huge to have any practical interest. Thus, we propose a sub-optimal but computational efficient, hierarchical algorithm to solve the ML problem. The performance in terms of mean localization error is evaluated by simulations for different scenarios and taking a realistic channel model into account. The sensitivity of the estimated position to the uncertainty on channel parameters is also evaluated.

In this letter, a low-complexity and low-overhead adaptive bit-loading algorithm for wireless multicarrier schemes is proposed and analyzed. It is based on the diversity gain obtained through the ordering and selection of the more reliable subcarriers. Higher order modulations are used to compensate for the reduced subcarrier utilization. On the contrary to other bit-loading algorithms, it does not require nonuniform bit and power level allocation among subcarriers, thus drastically reducing the modem hardware complexity and making it attractive as a possible extension of existing high-speed wireless local-area network standards. System performance is analyzed in different configurations and conditions, including a realistic 5-GHz propagation scenario. Comparison with optimal adapted and unadapted solutions is also made. Finally, the effect of unideal feedback of the channel state information is analyzed showing the robustness and the low overhead required of the new scheme.

An accurate method to analyze the joint effects of clipping and quantization in the A/D conversion in high speed WLAN receivers is presented. The model provides information about the spectral properties of the distortion noise, which allows the analytical characterization of the signal-to-distortion noise at the input of the demodulator. Oversampling, filtering, uniform and optimal non uniform quantization effects are taken into account. The optimal AGC working point is evaluated for each parameter configuration. The differences from the results obtained by the classical pseudo quantization noise model are highlighted showing that, due to the spectral characteristics, the gain introduced by oversampling is generally a few decibels lower than what foreseen by the classical theory.

In this paper, the issue of Bluetooth and IEEE802.11b coexistence in a heterogeneous environment is addressed by means of an integrated analytical approach. The methodology proposed carefully takes both physical (i.e., thermal noise, propagation, interference, modulation formats, and coding techniques) and medium access control (frequency hopping, packet structures, traffic loads) aspects into account. This model can be easily implemented when developing network simulators, thus avoiding the need of extensive bit level Monte Carlo simulations at the physical level. The mean packet error probability is evaluated as a function of the relative distance between the two systems for different conditions (e.g., propagation, packet type, traffic loading, etc). In particular, how the presence or absence of line-of-sight propagation significantly affects the coexistence distance is emphasized. Furthermore, for a fixed quality-of-service level we derive the coexistence domain of the two considered systems in terms of relative distance.

We present new exponential bounds for the Gaussian Q function (one- and two-dimensional) and its inverse, and for M-ary phase-shift-keying (MPSK), M-ary differential phase-shift-keying (MDPSK) error probabilities over additive white Gaussian noise channels. More precisely, the new bounds are in the form of the sum of exponential functions that, in the limit, approach the exact value. Then, a quite accurate and simple approximate expression given by the sum of two exponential functions is reported. The results are applied to the general problem of evaluating the average error probability in fading channels. Some examples of applications are also presented for the computation of the pairwise error probability of space-time codes and the average error probability of MPSK and MDPSK in fading channels.

We present new exponential bounds for the Gaussian Q-function or, equivalently, of the complementary error function er f c(.). More precisely, the new bound is in the form of the sum of exponential functions that, in the limit, approaches the exact value. Then, a quite accurate and simple approximated expression given by the sum of two exponential functions is reported. Moreover, some new simple bounds for the inverse er f c(.) are derived. The results are applied to the general problem of evaluating the average error probability in fading channels. An example of application to the computation of the pairwise error probability of space-time codes is also presented.

In this article the issue of Bluetooth and IEEE802.11b coexistence in a heterogeneous environment is addressed by means of an analytical approach. The methodology proposed carefully takes physical (i.e., thermal noise, propagation, interference, modulation formats and coding techniques) as well as medium access control (frequency hopping, packet structures, traffic loads) aspects into account. This model can be easily implemented when developing system simulators avoiding, thus, the need of extensive bit level Monte-Carlo simulations at the physical level. Furthermore, having preliminarily fixed a quality of service level, namely the target mean PEP, we derive the coexistence domain of the two considered systems in terms of relative distance.

In this paper the interference effect of a Bluetooth interferer on the IEEE802.11 physical interface is analytically evaluated taking into account different pulse shapes and frequency offsets. With the purpose to find simple and accurate methodologies suitable to be implemented in protocol simulators or analytical models, three different approaches are considered and compared in terms of accuracy and complexity. Results show that evaluations based on the Gaussian hypothesis, as regards the interference component, are not accurate and that the performance depends strongly on the frequency offset.

The performance in terms of the mean packet error probability (PEP) in a Rayleigh fading channel with thermal noise is analytically derived for a Bluetooth transmission interfered by IEEE 802.11b. The methodology proposed carefully takes PHY as well MAC aspects into account. Simulations are used to verify methodology assumptions. Moreover, we derive the coexistence domain, in terms of relative distances between the two systems, for a fixed quality of service, i.e., a target mean PEP.

This paper presents a reliable and low complexity acquisition and tracking technique for a DSP-based satellite CDMA modem. An analysis of the performance, in terms of false alarm probability, detection probability and mean acquisition time, is carried out as a function of the complexity and the level of interference. The proposed scheme, based on a dedicated frame format, appears able to cope with the DSP complexity constraint and high levels of interference. The signal structure can be also used for frequency tracking. A DSP implementation and numerical results, obtained by means of analytical evaluations and measurements on a real test-bed, are given.

Future wireless video transmission systems will consider OFDM (orthogonal frequency division multiplexing) as the basic modulation technique due to its robustness and low complexity implementation in the presence of frequency selective channels. Adaptive bit loading techniques have been applied to OFDM showing good performance gains in cable transmission systems. In this paper adaptive loading techniques are applied to a HIPERLAN2-like wireless system at 5 GHz for efficient multimedia traffic transmission. Moreover, the classical water-filling algorithm is extended to the multi-layer case. The semi-analytical results obtained show a large improvement respect to the non-adaptive case, also taking different channel state information up-date rates into account. The impact of this technique in terms of video quality is also evaluated for MPEG-4 video transmission.

The design of code-division multiple-access (CDMA) transmission systems for satellite communications requires an appropriate consideration of the distortion effects due to on-board nonlinear amplification. The aim of this paper is to provide an analytical framework for the evaluation of the in-band nonlinear distortion effects on the performance of CDMA systems. Both synchronous systems with orthogonal codes and asynchronous systems are considered. It is first shown that, when the users accessing the channel have the same power and their number is sufficiently large, the nonlinear distortion in the decision variables at the receiver can be simply described by a complex scale factor, which depends on the high-power-amplifier (HPA) characteristics only, and an additive noise, which is uncorrelated to the useful signal. Moreover, an analytical formulation of the bit error probability and the total degradation as a function of the output back-off and number of users is given. In the results, which are obtained for three classes of HPA models (i.e., the traveling wave tube amplifier, the solid-state power amplifier, and the amplifier with ideal predistortion), the performance and the capacity of power-limited systems is also discussed.

This paper presents an analytical model for the evaluation of nonlinear effects in the presence of Gaussian input signals with arbitrary spectrum. A simple relationship between the output signal power spectrum and the nonlinear device characteristic is given. The signal-to-distortion ratio (SDR) is also derived to show the impact of in-band and out-of-band distortion. The methodology is applied to estimate the accuracy of third and fifth-order models for a typical MMIC RF power amplifier.

This paper presents a theoretical characterization of nonlinear distortion effects in orthogonal frequency division multiplexing (OFDM) transmission systems. In the theoretical framework developed, it is shown that the effects on the decision variables of the in-band distortion introduced by a bandpass memoryless nonlinearity can be described by means of a complex gain and an additive Gaussian term with zero mean and suitable variance; analytical expressions for gain and variance are given. The conditions which allow this description are emphasized and discussed. As a consequence, a completely analytical procedure to evaluate error probability is also obtained and illustrated using OFDM/discrete multitone modulation (DMT) systems with rectangular pulse shaping; for the soft-envelope limiter nonlinearity, a closed form is derived. A comparison with simulation results is carried out to verify the accuracy of this method.

A high-speed indoor wireless communication system using coded orthogonal frequency-division multiplexing (OFDM) and working at 60 GHz is proposed and analyzed. An actual propagation environment consisting of a medium sized research laboratory, characterized by means of a ray-tracing technique, is considered for the analysis. In this contest the paper investigates and discusses the effects of frequency diversity, antenna sectorization, OFDM clustering, and different block coding strategies. Moreover, to characterize the communication between stationary indoor terminals at millimeter waves, a new definition of coverage is introduced. In order to evaluate the performance of the coded system in the actual environment, a suitable semianalytical algorithm is defined and applied. In the results the feasibility of a coded OFDM system for 155 Mbit/s packet transmission is checked. It is shown that all the line-of-sight (LOS) positions and 70% of the no LOS points can be covered in the scenario considered with a transmitted power of 10 dBm.

This paper proposes a new technique to reduce the non-linear distortion effects in orthogonal frequency division multiplexing (OFDM) systems. It exploits virtual carriers, which are modulated by using properly defined "dummy symbols", to obtain a transmitted signal with reduced envelope variations. With this method no additional redundancy is introduced, thus preserving the spectrum efficiency, and no changes at the receiver are required. To evaluate the dummy symbols some optimization criteria are investigated; an optimum algorithm and a low complexity iterative algorithm are proposed and compared from the point of view of the system's performance. The effectiveness of this technique is tested by considering some typical high power amplifier (HPA) models and by evaluating the performance degradation. A comparisons with other techniques proposed in the literature is also carried out.

The design of high quality, high speed wireless networks to connect mobile users requires large bandwidth availability. For this reason and with the aim of implementing new wireless systems, special attention has been paid to millimetre waves networks (e.g. at 60 GHz) based on short range communications. The paper presents some results concerning indoor channel characterisation. A ray tracing method has been applied to a realistic environment, with the view to define proper analytical models for propagation parameters. More precisely, large-scale received power, Rice factor, delay spread as a function of distance and small-scale variations statistics have been investigated in the presence and in the absence of room furniture: a two-state model has been proposed and checked.

A new analytical methodology for outage probability evaluation of a vehicle-to-vehicle packet radio communication system at 60 GHz, is presented. Propagation characteristics, co-channel interference and thermal noise are taken into account, in the context of an highway traffic model. Both code division and time division multiple access schemes are analysed: results as a function of offered traffic and useful link distance are discussed. The analytical procedure is general, and can also be applied to bi-dimensional cellular structures.>