We consider beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) whose elements are connected in groups and aim at optimizing their configuration to maximize the achievable rate of the cascade channel. We propose two suboptimal approaches (i.e., semidefinite programming (SDP) and projected gradient ascent (PGA) solutions) to first find the BD-RIS configuration that maximizes the composite channel trace and then locally maximizes the achievable rate by a randomization approach. We impose a constraint on the choice of the coefficients to ensure that the BD-RIS is passive, i.e., it does not emit more power than that received. Still, our solution has a high communication overhead for a large number of connections among the BD-RIS elements. We then propose a dynamic mapping between the BD-RIS configuration and a small number of control variables. The mapping is provided by the encoder part of an autoencoder, trained to minimize a suitable loss function on the optimal configurations in the specific deployment. We also design the BD-RIS configuration directly in the latent space of the autoencoder, reducing the complexity. By simulations in a typical cellular communication scenario, we show that the group-connected BD-RIS can achieve up to 95% of the rate obtained for a fully-connected BD-RIS with two orders of magnitude lower complexity, while the autoencoder compression and configuration optimization in the latent space reduces the control rate by 90% with negligible rate loss.

This paper focuses on the challenge-response physical-layer authentication (CR-PLA) scheme where a reflecting intelligent surface (RIS) is under the control of a receiving base station (BS) (Bob) who aims at checking if received messages come from a legitimate user equipment (UE) Alice or from an impersonating device (Trudy). To this end, Bob sets a random configuration of the RIS which remains secret to the attacker, and verifies that the channel estimated on the received message corresponds to the set configuration. We design the probability distribution of RIS configurations chosen by the verifier to maximize average capacity while satisfying an upper bound on missed detection (MD) probability for a given false alarm (FA) probability. The balance of communication and security metrics demonstrated by the numerical results shows the effectiveness and potential of the CR-PLA scheme.

The rise of wireless technologies has made the Internet of Things (IoT) ubiquitous, but the broadcast nature of wireless communications exposes IoT to authentication risks. Physical layer authentication (PLA) offers a promising solution by leveraging unique characteristics of wireless channels. As a common approach in PLA, hypothesis testing yields a theoretically optimal Neyman-Pearson (NP) detector, but its reliance on channel statistics limits its practicality in real-world scenarios. In contrast, deep learning-based PLA approaches are practical but tend to be not optimal. To address these challenges, we proposed a learning-based PLA scheme driven by hypothesis testing and conducted extensive simulations and experimental evaluations using Wi-Fi. Specifically, we incorporated conditional statistical models into the hypothesis testing framework to derive a theoretically optimal NP detector. Building on this, we developed LiteNP-Net, a lightweight neural network driven by the NP detector. Simulation results demonstrated that LiteNP-Net could approach the performance of the NP detector even without prior knowledge of the channel statistics. To further assess its effectiveness in practical environments, we deployed an experimental testbed using Wi-Fi IoT development kits in various real-world scenarios. Experimental results demonstrated that the LiteNP-Net outperformed the conventional correlation-based method as well as state-of-the-art Siamese-based methods.

Due to their ability to manipulate (EM) fields with high flexibility and low-cost implementation, metasurfaces have emerged as a promising technology to enhance the performance of cellular networks. We propose a novel reconfigurable antenna using transmitting metasurfaces for cellular base stations. This antenna is formed by surrounding radiating elements with multiple metasurfaces that can be configured to be transparent or absorptive to electromagnetic waves. This increases the directionality of the resulting emitted signal, improves reception, and limits interference. We present a baseband equivalent channel model for downlink transmission that incorporates the reconfigurable antenna and describes the diffraction phenomena resulting from the metasurfaces’ specific configuration. Next, we optimize the metasurface configuration, the transmit and receive beamformers, and the transmit power at multiple coordinated base stations to maximize the network sum-rate. Numerical results in a (5G) networks confirm that the proposed structure considerably increases the sum-rate compared to traditional antenna arrays.

Recent spam email techniques exploit visual effects in text messages, such as poisoning text, obfuscating words, and hidden text salting techniques. These effects were able to evade spam detection techniques based on the text. In this paper, we overcome this limitation by introducing a novel visual-based spam detection architecture, denoted as visual-based spam filter (VBSF). The multi-step process mimics the human eye's natural way of processing visual information, automatically rendering incoming emails and capturing their content as it appears on a user screen. Then, two different processing pipelines are applied in parallel. The first pipeline pertains to the perceived textual content, as it includes optical character recognition (OCR) to extract rendered textual content, followed by naive Bayes (NB) and decision tree (DT) content classifiers. The second pipeline focuses on the appearance of the email, as it analyzes and classifies the images of rendered emails through a specific convolutional neural network. Lastly, a meta classifier integrates text- and image-based classifier outputs, exploiting the stacking ensemble learning method. The performance of the proposed VBSF is assessed, showing that it achieves an accuracy of more than 98%, which is higher than the compared existing techniques on the designed dataset.

Jamming attacks pose a critical threat to wireless networks, particularly in cell-free massive MIMO systems, where distributed access points and user equipment (UE) create complex, time-varying topologies. This paper proposes a novel jamming detection framework leveraging dynamic graphs and graph convolution neural networks (GCN) to address this challenge. By modeling the network as a dynamic graph, we capture evolving communication links and detect jamming attacks as anomalies in the graph evolution. A GCN-Transformers-based model, trained with supervised learning, learns graph embeddings to identify malicious interference. Performance evaluation in simulated scenarios with moving UEs, varying jamming conditions and channel fadings, demonstrates the method’s effectiveness, which is assessed through accuracy and F1 score metrics, achieving promising results for effective jamming detection.

We study a visible light communication (VLC) system that employs a colored reconfigurable intelligent surface (CRIS) based on dichroic mirrors that reflect light at tunable frequencies. A verifier can use the CRIS to authenticate transmissions by comparing received multicolor power profiles with expected patterns. Four CRIS configuration strategies are evaluated: a deterministic cyclic pattern, static random reflectance, dynamic random reflectance, and dynamic random permutation of fixed profiles. Randomized configurations, especially dynamic ones, achieve superior authentication, enabling a novel challenge-response physical-layer authentication scheme over CRIS.

Reconfigurable intelligent surfaces (RISs) are seen as a promising technology to improve cellular network coverage, due to their ability to steer the impinging signals in desired directions. The design of the RIS can be easily addressed by assuming full channel knowledge. Nevertheless, estimating the channels to and from the RIS is a challenging problem, as it requires a huge training overhead. This paper proposes an efficient configuration optimization jointly with channel estimation by exploiting deep learning tools. In particular, we propose an algorithm that works in two steps. The first step is based on a decision tree that requires few end-to-end channel estimates with different RIS configurations. The configurations are iteratively selected based on an estimate of the mutual information between the obtained rates and the optimal configuration. The second step instead provides the minimum mean-square-error estimate of the optimal RIS configuration based on the data rates estimated on the channels obtained in the first step through a neural network (NN) trained with a supervised approach. Numerical results confirm that the proposed solution provides a configuration close to the optimal, with achievable rates approaching the upper bound obtained with perfect channel knowledge.

As drones are increasingly used in various civilian applications, the security of drone communications is a growing concern. In this context, we propose novel strategies for challengeresponse physical layer authentication (CR-PLA) of drone messages. The ground receiver (verifier) requests the drone to move to a defined position (challenge), and authenticity is verified by checking whether the corresponding measured channel gain (response) matches the expected statistic. In particular, the challenge is derived from a mixed strategy obtained by solving a zero-sum game against the intruder, which in turn decides its own positions. In addition, we derive the optimal strategy for multiround authentication, where the CR-PLA procedure is iterated over several rounds. We also consider the energy minimization problem, where legitimate users want to minimize the energy consumption without compromising the security performance of the protocol. The performance of the proposed scheme is tested in terms of both security and energy consumption through numerical simulations, considering different protocol parameters, different scenarios (urban and rural), different drone altitudes, and also in the context of drone swarms.

The identification of the devices from which a message is received is part of security mechanisms to ensure authentication in wireless communications. Conventional authentication approaches are cryptography-based, which, however, are usually computationally expensive and not adequate in the Internet of Things (IoT), where devices tend to be low-cost and with limited resources. This paper provides a comprehensive survey of physical layer-based device fingerprinting, which is an emerging device authentication for wireless security. In particular, this article focuses on hardware impairment-based identity authentication and channel features-based authentication. They are passive techniques that are readily applicable to legacy IoT devices. Their intrinsic hardware and channel features, algorithm design methodologies, application scenarios, and key research questions are extensively reviewed here. The remaining research challenges are discussed, and future work is suggested that can further enhance the physical layer-based device fingerprinting.

To protect underwater acoustic communications from interception, the exchange of encryption keys is necessary. Since underwater devices can be compromised, generating keys on site is a better option than predefined keys. In this paper, we present a solution that utilizes the characteristics of the underwater acoustic channel impulse response (CIR), which is highly variable in both space and time, while ensuring consistency between the communicating nodes (Alice and Bob). To compensate for temporal variations, the key is calculated from the CIR feature’s distribution parameters, while the hard key is determined using a K-means strategy. To achieve key agreement, we exploit the long propagation delay in the underwater CIR and let Alice and Bob transmit simultaneously while their packets fly past each other. Due to the channel’s reciprocity, this simultaneous transmission ensures that the same CIR is estimated at both ends of the communication link. Simulation and sea experiment results show that it is possible to extract at least three times as many secret bits as we would with a uniform quantizer. The results show a high matching rate between Alice and Bob and a high Hamming distance to Eve’s key. For reproducibility, we share the CIRs from the sea trials.

Underwater acoustic communications are becoming a popular solution for underwater data communications and telemetry, making the authentication of transmitted data a necessity. In this paper, we propose a physical-layer authentication strategy for underwater acoustic networks (UWANs) with mobile devices. Such a scenario is more challenging than classical authentication scenarios in static networks, because the mobility of the receiver and/or transmitter implies that channel conditions slowly change over time. Thus, we cannot rely on the statistics of channel features to be stationary. In our proposed strategy, we assume that the receiver can rely on a set of sensors. We first extract a set of channel features, to be used to track the channel evolution over time. We then develop a long short-term memory (LSTM)-based approach, where at each step the sensors predict future feature values based on a learned model and on previously observed feature values. Next, each sensor computes the prediction error and passes it on to the actual receiver, which makes a decision on the signal authenticity through a generalized likelihood ratio test (GLRT). We model different classes of attacks and test them using simulation data obtained via the Bellhop ray tracing software. Numerical results show that our authentication mechanism successfully distinguishes between legitimate and impersonating transmitters, even when considering challenging attacking scenarios where the attacker can successfully mimic the channels between the legitimate transmitter and the sensors.

Anti-spoofing techniques for current global navigation satellite systems (GNSS) authenticate signals on a single band and from a single system. However, nowadays commercial GNSS receivers commonly calculate the position, velocity, and time (PVT) solution by simultaneously utilizing signals from multiple constellations and bands, with a substantial enhancement in both accuracy and availability. Therefore, anti-spoofing techniques have recently been proposed that mix authenticated and non-authenticated signals to increase performance without sacrificing security. In this paper, we formalize the models of such signal mixture-based authentication checks. We propose a spoofing attack generating a fake signal that leads the victim to a target PVT solution, undetected. We analytically relate the degrees of freedom of the attacker in manipulating the victim’s solution to both the employed security checks and the number of open non-authenticated signals that can be tampered with by the attacker. The performance of the considered attack strategies are tested on an experimental dataset. Finally, we assess the limits of PVT-based GNSS authentication checks where both authenticated and non-authenticated signals are used.

The threat of signal spoofing attacks against global navigation satellite system (GNSS) has grown in recent years and has motivated the study of anti-spoofing techniques. However, defense methods have been designed only against specific attacks. This paper introduces a general model of the spoofing attack framework in GNSS, from which optimal attack and defense strategies are derived. We consider a scenario with a legitimate receiver (Bob) testing if the received signals come from multiple legitimate space vehicles (Alice) or from an attack device (Eve). We first derive the optimal attack strategy against a Gaussian transmission from Alice, by minimizing an outer bound on the achievable error probability region of the spoofing detection test. Then, framing the spoofing and its detection as an adversarial game, we show that the Gaussian transmission and the corresponding optimal attack constitute a Nash equilibrium. Lastly, we consider the case of practical modulation schemes for Alice and derive the generalized likelihood ratio test. Numerical results validate the analytical derivations and show that the bound on the achievable error region is representative of the actual performance.

Physical-layer authentication (PLA) mechanisms exploit signals exchanged at the physical layer of communication systems to confirm the sender of a received message. In this paper, we propose a novel challenge-response PLA (CR-PLA) mechanism for a cellular system that leverages the reconfigurability property of a reconfigurable intelligent surface (RIS) (under the control of the verifier) in an authentication mechanism. In CR-PLA, the verifier base station (BS) sets a random RIS configuration, which remains secret to the intruder, and then checks that the resulting estimated channel is modified correspondingly. In fact, for a message sent by an attacker in a different location than the legitimate user equipment (UE), the BS will estimate a different channel and the message will be rejected as fake. Such a solution reduces the communication and computational overhead with respect to higher-layer cryptographic authentication. We derive the maximum a-posteriori attack when the attacker observes a correlated channel and the reconfigurable intelligent surface (RIS) has many elements, and the attacker transmits to Bob either directly or through the RIS. Using a generalized likelihood ratio test to test the authenticity at the base station (BS), we derive approximate expressions of the false alarm and misdetection probabilities when both the BS and the UE have a single antenna each, while the RIS has a large number of elements. We also evaluate the trade-off between security and communication performance, since choosing a random RIS configuration reduces the data rate. Moreover, we investigate the impact of various parameters (e.g., the RIS randomness, the number of RIS elements, and the operating signal-to-noise ratio) on security and communication performance.

In this paper, we propose a secure unmanned aerial vehicle (UAV) communication system with the assistance of a reconfigurable intelligent surface (RIS), where UAV trajectory design and artificial noise are incorporated to prevent eavesdropping from multiple colluding curious users. To maximize the secrecy rate of the proposed system, we undertake a joint optimization process that encompasses the trajectory of the UAV, the RIS phase shifts, and the beamforming vectors for both information and artificial noise signals, considering the constraints of the UAV transmit power, UAV flying speed and the phase shifts. To address the non-convex nature of the joint problem and handle the coupling effects of multiple parameters, we conduct the problem decomposition by using the block coordinate descent (BCD) method, combined with an alternating algorithm to optimize the decomposed sub-problems. To further tackle the non-convexity in sub-problems, we apply the successive convex approximation (SCA) method to circumvent the trajectory optimization problem and to optimize the beamformers of information and artificial noise signals, while a majorization-minimization (MM) based scheme is adopted for the RIS phase shifts optimization. Numerical simulation results substantiate the convergence and effectiveness of the proposed algorithm through the comparison with benchmark methods, and our proposed scheme is proven to achieve a significant improvement in average secrecy rate across various conditions.

This paper investigates the problem of secure transmission over a two-user discrete memoryless multiple-access wiretap channel with partial rate-limited feedback (MAC-WT-PLF). The receiver can causally and securely transmit feedback to one of the transmitters at a limited rate. Three achievable rate regions and one outer bound on the secrecy capacity are presented based on three proposed coding schemes and the Sato-type bounding approach. The proposed coding schemes show that the feedback can play multiple roles, i.e., encrypting part of messages, enlarging the size of the dummy message, and increasing the correlation between the channel inputs, to enhance the secrecy performance. Of particular interest is identifying the novel role of enlarging the size of the dummy message at one of the transmitters, which enables both transmitters to benefit from the feedback significantly. In addition, the proposed achievable rate regions and outer bound are computed for the Gaussian MAC-WT-PLF, and comparative numerical results are provided under different eavesdropping cases.

Intelligent reflecting surfaces (IRSs) are being widely investigated as a potential low-cost and energy-efficient alternative to active relays for improving coverage in next-generation cellular networks. However, technical constraints in the configuration of IRSs should be taken into account in the design of scheduling solutions and the assessment of their performance. To this end, we examine an IRS-assisted time division multiple access (TDMA) cellular network where the reconfiguration of the IRS incurs a communication cost; thus, we aim at limiting the number of reconfigurations over time. Along these lines, we propose a clustering-based heuristic scheduling scheme that maximizes the cell sum capacity, subject to a fixed number of reconfigurations within a TDMA frame. First, the best configuration of each user equipment (UE), in terms of joint beamforming and optimal IRS configuration, is determined using an iterative algorithm. Then, we propose different clustering techniques to divide the UEs into subsets sharing the same suboptimal IRS configuration, derived through distance- and capacity-based algorithms. Finally, UEs within the same cluster are scheduled accordingly. We provide extensive numerical results for different propagation scenarios, IRS sizes, and phase shifters quantization constraints, showing the effectiveness of our approach in supporting multi-user IRS systems with practical constraints.

We consider a cellular network, where the uplink transmissions to a base station (BS) are interferenced by other devices, a condition that may occur, e.g., in cell-free networks or when using non-orthogonal multiple access (NOMA) techniques. Assuming that the BS treats this interference as additional noise, we focus on the problem of estimating the interference correlation matrix from received signal samples. We consider a BS equipped with multiple antennas and operating in the millimeter-wave (mmWave) bands and propose techniques exploiting the fact that channels comprise only a few reflections at these frequencies. This yields a specific structure of the interference correlation matrix that can be decomposed into three matrices, two rectangular depending on the angle of arrival (AoA) of the interference and the third square with smaller dimensions. We resort to gridless approaches to estimate the AoAs and then project the least square estimate of the interference correlation matrix into a subspace with a smaller dimension, thus reducing the estimation error. Moreover, we derive two simplified estimators, still based on the gridless angle estimation that turns out to be convenient when estimating the interference over a larger number of samples.

Reconfigurable intelligent surfaces (RISs) are a promising solution to improve the coverage of cellular networks, thanks to their ability to steer impinging signals in desired directions. However, they introduce an overhead in the communication process since the optimal configuration of a RIS depends on the channels to and from the RIS, which must be estimated. In this paper, we propose a novel fast iterative configuration (FIC) protocol to determine the optimal RIS configuration that exploits the small number of paths of millimetre-wave (mmWave) channels and an adaptive choice of the explored RIS configurations. In particular, we split the elements of the RIS into a number of subsets equal to the number of channel taps. For each subset, then an iterative procedure finds at each iteration the optimal RIS configuration in a codebook exploring a two-dimensional grid of possible angles of arrival and departure of the path at the RIS. Over the iterations, the grid is made finer around the point identified in previous iterations. Numerical results obtained using an urban channel model confirm that the proposed solution is fast and provides a configuration close to the optimal in a shorter time than other existing approaches.

Authenticating the communications among drones operating as a network (or a swarm) is crucial for the control of the network. When drones are in turn supporting communications with other ground devices (e.g., in non-terrestrial networks), all nodes in the network need to be authenticated for end-to-end security. The absence of a reliable fixed network architecture among drones, which are only connected by wireless links, calls for new authentication mechanisms that can complement or be used as alternatives to those offered by cryptography. We propose a challenge-response (CR) physical-layer authentication (PLA) mechanism, where, upon a transmission request from a transmitting drone, referred to as Alice, Bob either asks Alice to move in a specific (randomly chosen) position or moves to a (randomly chosen) position: in both cases, changes in the propagation environment are controlled by Bob. Then, the message is transmitted and Bob estimates the channel from the received signal and verifies that it is compatible with the positions assumed by Alice and Bob. Note that Bob may represent a group of drones that cooperate for authentication. We discuss several security challenges to this CR PLA mechanism and compare them with existing approaches. Preliminary results on the performance of the proposed authentication scheme are presented, showing the advantage of the CR PLA approach.

Hybrid reconfigurable intelligent surfaces (H-RISs) are panels of metamaterial elements that can be electrically reconfigured to reflect radio signals in the desired direction. At the same time, they can also act as receiving antennas. We propose to use an H-RIS to authenticate radio signals, i.e., to enable a receiver Bob to authenticate signals received by a legitimate transmitter Alice rather than an impersonating attacker Eve. Such a decision is made on the basis of the channel response estimated from the received signal, which operates as a signature in this physical-layer authentication (PLA) mechanism. We consider two attacks, where Eve can transmit signals either through the H-RIS to Bob (as she is close to Alice) or directly to Bob (as she is close to Bob). As the H-RIS can receive signals, the authentication test is performed jointly at Bob and at the H-RIS, significantly improving the distinguishability of the legitimate and attack scenarios. In particular, the optimal attack strategy and a generalized likelihood ratio test for authentication are derived.

In this paper, we propose to remove the analog stage of hybrid beamforming (HYBF) in the millimeter wave (mmWave) full-duplex (FD) systems. Such a solution is highly desirable as the analog stage suffers from high insertion loss and high power consumption. Consequently, the mmWave FD nodes can operate with a fewer number of antennas, instead of relying on a massive number of antennas, and to tackle the propagation challenges of the mmWave band we propose to use near-field intelligent reflecting surfaces (NF-IRSs). The objective of the NF-IRSs is to simultaneously and smartly control the uplink (UL) and downlink (DL) channels while assisting in shaping the SI channel: this to obtain very strong passive SI cancellation. A novel joint active and passive beamforming design for the weighted sum-rate (WSR) maximization for the NF-IRSs-assisted mmWave point-to-point FD system is presented. Results show that the proposed solution fully reaps the benefits of the IRSs, only when they operate in the NF, which leads to considerably higher gains compared to the conventional massive MIMO (mMIMO) mmWave FD and half duplex (HD) systems.

Intelligent reflecting surfaces (IRSs) are being studied as possible low-cost energy-efficient alternatives to active relays, with the goal of improving coverage in millimeter wave (mmWave) and terahertz (THz) network deployments. In the literature, these surfaces are often studied by idealizing their characteristics: notably, it is often assumed that IRSs can tune with arbitrary frequency the phase-shifts induced by their elements, thanks to a wire-like control channel to the next generation node base (gNB). Instead, in this work we investigate an IRS-aided time division multiple access (TDMA) cellular network, where the reconfiguration of the IRS entails an energy or communication cost, and we aim at limiting the number of reconfigurations over time. We propose a clustering-based heuristic scheduling, which optimizes the cell sum-rate subject to a given number of reconfigurations within the TDMA frame. To this end, we first cluster user equipments (UEs) with a similar optimal IRS configuration, determined through a novel beamforming and IRS iterative optimization algorithm. Then, we obtain a single IRS configuration for each cluster of UEs. Numerical results show that our approach is effective in supporting IRSs-aided systems with practical constraints, achieving up to 85% of the sum-rate obtained by an ideal deployment, while reducing by 50% the number of IRS reconfigurations.

Nowadays, aerial formations are frequently employed in outdoor scenarios to cooperatively explore and monitor wide areas of interest. In these applications, the vehicles are often exposed to relevant security vulnerabilities, as, for instance, the alteration of navigation signals from an attacker with map counterfeiting (if not even hijacking) purposes. In this work, we focus on an Unmanned Aerial Vehicle (UAV) formation that monitors an area, wherein navigation spoofing attacks may occur. Letting the UAVs cooperate and exploiting the redundancy in the available sensing information, a distributed procedure is proposed to$i$) detect spoofing attacks, and$ii$) support the navigation in adverse conditions. The validity of the designed approach is confirmed by numerical results. Aerial vehicles for outdoor operation are generally endowed with inertial measurements, relative ranging, and GNSS sensing capability. In this work, two cascaded estimation algorithms for concurrent GNSS spoofing detection and localization in a multi-UAV scenario is proposed, to attain robust navigation in areas subject to GNSS spoofing attacks. The attack detection leverages on information theoretic tools to provide a practical threshold test by checking the multimodal measurement consistency. The localization procedures exploit a decision logic relying on measurement reliability to combine information sources that are different in nature, for UAV self-localization in both safe and under-attack conditions. Note to Practitioners—Aerial vehicles for outdoor operation are generally endowed with inertial measurements, relative ranging, and GNSS sensing capability. In this work, two cascaded estimation algorithms for concurrent GNSS spoofing detection and localization in a multi-UAV scenario is proposed, to attain robust navigation in areas subject to GNSS spoofing attacks. The attack detection leverages on information theoretic tools to provide a practical threshold test by checking the multimodal measurement consistency. The localization procedures exploit a decision logic relying on measurement reliability to combine information sources that are different in nature, for UAV self-localization in both safe and under-attack conditions.

With the growing use of underwater acoustic communications and the recent adoption of standards in this field, it is becoming increasingly important to secure messages against eavesdroppers. In this paper, we focus on a physical-layer security solution to generate sequences of random bits (keys) between two devices (Alice and Bob) belonging to an underwater acoustic network (UWAN); the key must remain secret to a passive eavesdropper (Eve) not belonging to the UWAN. Our method is based on measuring the propagation delay of the underwater acoustic channel over multiple hops of the UWAN: this harvests the randomness in the UWAN topology and turns the slow sound propagation in water into an advantage against eavesdropping. Our key generation protocol includes a route discovery handshake, whereby all UWAN devices at intermediate hops accumulate their message processing delays. This enables Alice and Bob to compute the actual propagation delays along each route and to map such information to a sequence of bits. Finally, from these bit sequences, Alice and Bob obtain a secret key. We analyze the performance of the protocol theoretically and assess it via extensive simulations and field experiments.

Fifth generation (5G) cellular networks can operate with millimeter waves (mmWave), which require appropriate beamforming at both the base station and the user equipment (UE). In this paper we consider an automotive scenario, where the UE is mounted on a car and is using a single radio-frequency (RF) chain and a configurable analog beamformer, so that the effective firing direction of the antenna (i.e., only one beamforming angle) can be set at any given time. As the UE moves, the beamforming angle should be tracked using the reference signals transmitted in downlink by the base station. While in a basic solution all possible beamforming angles are explored and a long time is needed, we propose here the adaptive-step tracking algorithm, a procedure that learns from past channel changes which angles to explore, yielding a short tracking time. Numerical results are provided for two scenarios, where the UE either rotates (thus making the angle tracking challenging) or moves along a straight line (with variations of the received power).

Traditional link adaptation (LA) schemes in cellular network must be revised for networks beyond the fifth generation (b5G), to guarantee the strict latency and reliability requirements advocated by ultra reliable low latency communications (URLLC). In particular, a poor error rate prediction potentially increases retransmissions, which in turn increase latency and reduce reliability. In this paper, we present an interference prediction method to enhance LA for URLLC. To develop our prediction method, we propose a kernel based probability density estimation algorithm, and provide an in depth analysis of its statistical performance. We also provide a low complexity version, suitable for practical scenarios. The proposed scheme is compared with state-of-the-art LA solutions over fully compliant 3rd generation partnership project (3GPP) calibrated channels, showing the validity of our proposal.

In fifth-generation (5G) and beyond cellular networks, grant-free random access (RA) is useful to reduce latency in uplink. We consider a scenario wherein time is split into frames, divided into slots, and machine-type devices (MTDs) are assigned a slot in each frame for possible transmission. Packet generations at the MTDs are correlated, potentially increasing collisions. We propose a slot allocation scheme based on the observations of successes and collisions in previous frames, aiming at maximizing the cell throughput at each frame. The RA scheme is modeled as a hidden Markov model (HMM), taking into account the joint packet generation statistics. We then propose a greedy algorithm that iteratively assigns slots to users. We compare the performance of the proposed greedy maximum throughput (GMT) with existing literature solutions, and confirm that a high cell throughput is achieved.

In a beyond-5G (B5G) scenario, we consider a virtual private mobile network (VPMN), i.e., a set of user equipments (UEs) directly communicating in a device-to-device (D2D) fashion, and connected to the cellular network by multiple gateways. The purpose of the VPMN is to hide the position of the VPMN UEs to the mobile network operator (MNO). We investigate the design and performance of packet routing inside the VPMN. First, we note that the routing that maximizes the rate between the VPMN and the cellular network leads to an unbalanced use of the gateways by each UE. In turn, this reveals information on the location of the VPMN UEs. Therefore, we derive a routing algorithm that maximizes the VPMN rate, while imposing for each UE the same data rate at each gateway, thus hiding the location of the UE. We compare the performance of the resulting solution, assessing the location privacy achieved by the VPMN, and considering both the case of single hop and multihop in the transmissions from the UEs to the gateways.

Spoofing attacks in global navigation satellite systems (GNSSs) aim at inducing the estimation of a fake position at the victim receiver. Many devices, including smartphones, are nowadays equipped with both a GNSS receiver and an inertial measurement unit (IMU), which also provides location/movement information, while being immune from GNSS attacks. We propose a spoofing detection technique based on the comparison between GNSS and IMU measurements. The detection is performed through a generalized likelihood ratio test (GLRT), which is efficiently implemented by a matrix multiplication approach. In particular, the device a) estimates its orientation from magnetometer and gyroscope measurements, b) estimates its position, acceleration, and velocity by a maximum likelihood approach, and c) performs the GLRT for spoofing detection. The performance of the proposed GLRT is compared with the Kalman filter innovation test and with the direct comparison method (DCM), both in terms of false alarm/missed detection probabilities and computational complexity.

In fifth-generation (5G) cellular networks, users feed back to the base station the index of the precoder (from a codebook) to be used for downlink transmission. The precoder is strongly related to the user channel and in turn to the user position within the cell. We propose a method by which an external attacker determines the user position by passively overhearing this unencrypted layer-2 feedback signal. The attacker first builds a map of fed back precoder indices in the cell. Then, by overhearing the precoder index fed back by the victim user, the attacker finds its position on the map. We focus on the type-I single-panel codebook, which today is the only mandatory solution in the 3GPP standard. We analyze the attack and assess the obtained localization accuracy against various parameters. We analyze the localization error of a simplified precoder feedback model and describe its asymptotic localization precision. We also propose a mitigation against our attack, wherein the user randomly selects the precoder among those providing the highest rate. Simulations confirm that the attack can achieve a high localization accuracy, which is significantly reduced when the mitigation solution is adopted, at the cost of a negligible rate degradation.

In this paper, we propose a novel channel quality reporting approach for cellular communication systems. The proposed approach features a differential coding scheme in stationary propagation conditions and a detector of non-stationary propagation conditions, which further triggers a channel-quality predictor for the non-stationary environment based on a machine learning method. In particular, the machine learning engine learns about the specific large variations of the channel quality by collecting signaling information from mobile terminals in a given region. Our simulations in a controlled urban environment with vehicular users show that the proposed solution can effectively replace the 4-bit channel-quality reporting scheme of LTE and NR standards with a 2-bit one, providing correct channel-quality indication in non-stationary conditions with high probability.

Millimeter wave (mmWave) wideband channels in a multiple-input multiple-output (MIMO) transmission are described by a sparse set of impulse responses in the angle-delay, or space-time (ST), domain. These characteristics will be even more prominent in the THz band used in future systems. We consider two approaches for channel estimation: compressed-sensing (CS), exploiting the sparsity in the angular/delay domain, and low-rank (LR), exploiting the algebraic structure of channel matrix. Both approaches share several commonalities, and this paper provides for the first time i) a comparison of the two approaches, and ii) new versions of CS and LR methods that significantly improve performance in terms of mean squared error (MSE), computational complexity, and latency. We derive the asymptotic MSE bound for any estimator of the ST-MIMO multipath channels with invariant angles/delays and time-varying fading, with unknown angle/delay diversity order: the bound also accounts for the degradation introduced by sub-optimal separable channel models. We will show that in the considered scenarios both CS and LR approaches attain the bound. Our performance assessment over ideal and 3rdgeneration partnership project (3GPP) channel models, suitable for the fifth-generation (5G) and beyond of cellular networks, shows the trade-off obtained by the methods over various metrics: i) CS methods are converging faster than the LR methods, both attaining the asymptotic MSE bound; ii) the CS methods depend on the array manifold, while LR methods are independent of the array calibration; iii) CS solutions are more complex than LR solutions.

Fixed wireless access has been spreading recently as a complement to wired or fiber solutions, and its implementation on millimeter waves has attracted attention for its potentially high data rates, achievable also in densely populated areas. New hardware and software solutions are needed to overcome various technical issues at those frequencies. We propose a novel modular hybrid beamforming (MHB) architecture, whereby, in receive mode, each module comprises a set of antennas connected to fixed analog beamformers, in turn connected by configurable switches to a smaller set of radio frequency chains. The outputs of all modules are then jointly processed by a digital beamformer. In particular, an MHB performing discrete Fourier transform beamforming for uniform linear arrays is studied. We address the problems of a) switch configuration, b) power allocation and digital beamformer design, and c) channel estimation. For both a) and b) we target the maximization of the total weighted spectral efficiency (WSE) under power and per-user average spectral efficiency (SE) constraints, and we propose greedy efficient solutions. For c) we propose a multistage scheme. We assess the MHB performance in terms of WSE, estimation accuracy, estimation overhead, and computational complexity, and compare them with existing solutions in literature.

In-region location verification (IRLV) in wireless networks is the problem of deciding if user equipment (UE) is transmitting from inside or outside a specific physical region (e.g., a safe room). The decision process exploits the features of the channel between the UE and a set of network access points (APs). We propose a solution based on machine learning (ML) implemented by a neural network (NN) trained with the channel features (in particular, noisy attenuation values) collected by the APs for various positions both inside and outside the specific region. The output is a decision on the UE position (inside or outside the region). By seeing IRLV as an hypothesis testing problem, we address the optimal positioning of the APs for minimizing either the area under the curve (AUC) of the receiver operating characteristic (ROC) or the cross entropy (CE) between the NN output and ground truth (available during the training). In order to solve the minimization problem we propose a two-stage particle swarm optimization (PSO) algorithm. We show that for a long training and a NN with enough neurons the proposed solution achieves the performance of the Neyman-Pearson (N-P) lemma.

In-region location verification (IRLV) aims at verifying whether a user is inside a region of interest (ROI). In wireless networks, IRLV can exploit the features of the channel between the user and a set of trusted access points. In practice, the channel feature statistics is not available and we resort to machine learning (ML) solutions for IRLV. We first show that solutions based on either neural networks (NNs) or support vector machines (SVMs) with typical loss functions are Neyman-Pearson (N-P)-optimal at learning convergence for sufficiently complex learning machines and large training datasets. For a finite training, ML solutions are more accurate than the N-P test based on estimated channel statistics. Then, as estimating channel features outside the ROI may be difficult, we consider one-class classifiers, namely auto-encoder NNs and one-class SVMs which, however, are not equivalent to the generalized likelihood ratio test (GLRT), typically replacing the N-P test in the one-class problem. Numerical examples support the results in realistic wireless networks, with channel models including path-loss, shadowing, and fading.

We consider the problem of power allocation for the down-link of a 5G cellular system operating in the mm-wave band and serving two sets of users: fix-rate (FR) users (transmitting data at fixed rate), typically seen in device-to-device communications, and variable-rate (VR) users (that can change their transmission data rate), typically requiring high data rate services. The power allocation objective is the maximization of the spectral efficiency of VR users while ensuring that FR users get the required rate. In contrast with the existing literature on power allocation, we exploit the sparsity of the virtual mm-wave channel matrix, obtained by applying fixed discrete-Fourier transform beamformers at both the transmitter and the receiver. Exploiting the channel partial orthogonality, users are first grouped based on the mutual interference and then the power is allocated among and within groups.

With the growing use of underwater acoustic communications (UWAC) for both industrial and military operations, there is a need to ensure communication security. A particular challenge is represented by underwater acoustic networks (UWANs), which are often left unattended over long periods of time. Currently, due to the physical and performance limitations, the UWAC packets rarely include encryption, leaving the UWAN exposed to external attacks faking legitimate messages. In this paper, we propose a new algorithm for message authentication in a UWAN setting. We begin by observing that, due to the strong spatial dependency of the underwater acoustic channel, an attacker can attempt to mimic the channel associated with the legitimate transmitter only for a small set of receivers, typically just for a single one. Taking this into account, our scheme relies on trusted nodes that independently help a sink node in the authentication process. For each incoming packet, the sink fuses beliefs evaluated by the trusted nodes to reach an authentication decision. These beliefs are based on the estimated statistics of the channel parameters, which are chosen to be the most sensitive to the transmitter-receiver displacement. Our simulation results show accurate identification of an attacker's packet. We also report results from a sea experiment demonstrating the effectiveness of our approach.

One of the key features of the fifth-generation (5G) cellular network is non-orthogonal multiple access (NOMA) which improves the spectrum efficiency and increases the network connectivity. A second key ingredient is device to device (D2D) communication which increases spectrum efficiency and off-loads the cellular network. A proper exploitation of both NOMA and D2D requires adequate resources allocation algorithms to manage the interference. Moreover, to support various quality of service (QoS) requirements, other key metrics beyond the rate should be taken into account, such as queue stability and head of line (HoL) packet delay. In this paper, we consider resource block (RB) allocation and power control for both uplink NOMA and D2D communications. An overlay spectrum sharing paradigm is adopted, where an RB is exclusively allocated to either the cellular or D2D communications. The solution uses the modified largest weighted delay first (MLWDF) scheduling discipline and reduces the HoL packet delay, with negligible reduction of the achieved sum rate with respect to the pure maximum-rate solution in typical cellular scenarios.

User authentication (UA) supports the receiver in deciding whether a message comes from either the claimed transmitter or an impersonating attacker. Information-theoretically secure authentication can be implemented by using either a secret (symmetric key) shared between both the legitimate users or the transmission medium over which the message is transmitted [physical-layer authentication (PLA)]. We analyze these solutions when the physical-layer channel is the unique randomness source for either generating the key or performing PLA. For the symmetric-key-based UA approach, we resort to a secret key agreement. Moreover, we also consider an asymmetric-key-based UA based on the public-key (proven to be semantically secure), where the channel is used as an entropy source at one device only. We define the secure authentication rate at which the probability that the UA attack succeeds goes to zero as the number of independent and identically distributed variables describing how the channel goes to infinity. Both passive and active attacks are considered, and by numerical results, we compare the various UA schemes.

Cloud radio access network (C-RAN) is a promising technology for fifth-generation (5G) cellular systems. However the burden imposed by the huge amount of data to be collected (in the uplink) from the radio remote heads (RRHs) and processed at the base band unit (BBU) poses serious challenges. In order to reduce the computation effort of minimum mean square error (MMSE) receiver at the BBU the Gaussian message passing (MP) together with a suitable sparsification of the channel matrix can be used. In this paper we propose two sets of solutions, either centralized or distributed ones. In the centralized solutions, we propose different approaches to sparsify the channel matrix, in order to reduce the complexity of MP. However these approaches still require that all signals reaching the RRH are conveyed to the BBU, therefore the communication requirements among the backbone network devices are unaltered. In the decentralized solutions instead we aim at reducing both the complexity of MP at the BBU and the requirements on the RRHs-BBU communication links by pre-processing the signals at the RRH and convey a reduced set of signals to the BBU.

We consider the problem of scheduling and power allocation for the downlink of a 5G cellular system operating in the millimeter wave (mmWave) band and serving two sets of users: fix-rate (FR) users typically seen in device-to-device (D2D) communications, and variable-rate (VR) users, or high data rate services. The scheduling objective is the weighted sum-rate of both FR and VR users, and the constraints ensure that active FR users get the required rate. The weights of the objective function provide a trade-off between the number of served FR users and the resources allocated to VR users. For mmWave channels the virtual channel matrix obtained by applying fixed discrete-Fourier transform (DFT) beamformers at both the transmitter and the receiver is sparse. This results into a sparsity of the resulting multiple access channel, which is exploited to simplify scheduling, first establishing an interference graph among users and then grouping users according to their orthogonality. The original scheduling problem is solved using a graph-coloring algorithm on the interference graph in order to select sub-sets of orthogonal VR users. Two options are considered for FR users: either they are chosen orthogonal to VR users or non-orthogonal. A waterfilling algorithm is then used to allocate power to the FR users.

Many security techniques working at the physical layer need a correct channel state information (CSI) at the transmitter, especially when devices are equipped with multiple antennas. Therefore such techniques are vulnerable to pilot contamination attacks (PCAs) by which an attacker aims at inducing false CSI. In this paper we provide a solution to some PCA methods, by letting two legitimate parties to compare their channel estimates. The comparison is made in order to minimize the information leakage on the channel to a possible attacker. By reasonable assumptions on both the channel knowledge by the attacker and the correlation properties of the attacker and legitimate channels we show the validity of our solution. An accurate analysis of possible attacks and countermeasures is provided, together with a numerical evaluation of the attainable secrecy outage probability when our solution is used in conjunction with beamforming for secret communications.

We consider a cellular Internet of things (CIoT) network where many source nodes aim at exchanging messages with a single concentrator node. To this end, they are assisted by anchor nodes that are trusted and securely connected with the concentrator node. In this context, we aim at providing a message authentication scheme based on the characteristics of the channel between the source nodes and the anchor nodes. According to this approach, the anchor nodes estimate the channel to source nodes in an initially externally authenticated fashion, while forthcoming messages are authenticated by comparing the current channel estimate with the initial estimate. Moreover, assuming that the anchor nodes have a limited energy availability, we derive suitable scheduling policies for the activation of the anchor nodes for authentication purposes. In particular, we aim at maximizing the anchors lifespan while guaranteeing given false alarm and missed detection probabilities of the authentication process. The performance of the proposed authentication protocols is evaluated in a typical CIoT scenario.

We consider a wiretap channel with an eavesdropper (Eve) and an honest but curious relay (Ray). Ray and the destination (Bob) are full-duplex (FD) devices. In order to prevent Ray from getting information on the secret message, we consider the scaled compute-and-forward (SCF) where scaled lattice coding is used in the transmission by both the source (Alice) and Bob in order to allow Ray to decode only a linear combination of the two messages. At the same time Ray transmits artificial noise (AN) to confuse Eve. When Ray relays the decoded linear combination, Alice and Bob are transmitting AN against Eve. With respect to existing literature the innovations of this paper are: a) Bob and Ray are FD devices; b) Alice, Ray and Bob transmit also AN; and c) the channel to Eve is not known to Alice, Bob and Ray. For this scenario we derive bounds on both the secrecy outage probability and the achievable secrecy-outage rates.

We consider a broadcast communication over parallel channels, where the transmitter sends K + 1 messages: one common message to all users, and K confidential messages to each user, which need to be kept secret from all unintended users. We assume partial channel state information at the transmitter, stemming from noisy channel estimation. Our main goal is to design a power allocation algorithm in order to maximize the weighted sum rate of common and confidential messages under a total power constraint. The resulting problem for joint encoding across channels is formulated as the cascade of two problems, the inner min problem being discrete, and the outer max problem being convex. Thereby, efficient algorithms for this kind of optimization program can be used as solutions to our power allocation problem. For the special case K = 2, we provide an almost closed-form solution, where only two single variables must be optimized, e.g., through dichotomic searches. To reduce computational complexity, we propose three new algorithms, maximizing the weighted sum rate achievable by two suboptimal schemes that perform per-user and per-channel encoding. By numerical results, we assess the performance of all proposed algorithms as a function of different system parameters.

Distributed generators (DGs), coupled with suitable control and communication infrastructures, are expected to play a key role in improving the efficiency of electricity grids. In this paper, we focus on low-voltage and single-phase microgrids exploring the interplay of distributed power loss reduction and communication. We select representative power-loss reduction algorithms from the state of the art and provide design rules for the required networking strategies in the presence of lossy communication links, assessing the impact of communication as well as electrical grid features. Toward this end, we devise a novel statistical cosimulation (electricity grid, communication, and control) framework that faithfully mimics the characteristics of real-world microgrids in terms of communication and grid topologies, power demand, and distributed generation from solar sources. Our numerical results highlight the role of communication procedures and the differences among the selected optimization techniques for power loss reduction, assessing their convergence rate and quantifying the impact of communication failures, line impedance estimation error, communication and electricity grid topologies, network size, and number of DGs.

The wireless medium offers many opportunities for broadcast communications. However, it also opens the possibility for attackers to eavesdrop the broadcast data or to pretend to be another node or device. These two attacks define the protection goals, namely, confidentiality and authenticity. Traditionally, both are solved by cryptographic approaches exploiting knowledge available in the surrounding infrastructure. The novel communication paradigms for the Internet of Things or cyber-physical systems do not scale with the standard cryptographic approach. Instead it is possible to exploit properties of the underlying physical channel to provide countermeasures against eavesdropping and impersonation attacks. Thereby, the random fading channel induces uncertainty which is detrimental but at the same time also helpful. In this paper, we review and describe a generalized model for physical-layer-based confidential data transmission and wireless authentication. A key role is played by the channel uncertainty and available design dimensions such as time, frequency, and space. We show that wireless authentication and secret-key generation can work in multicarrier and multiple-antenna systems and explain how even outdated channel state information can help to increase the available secure degrees of freedom. This survey focuses on the system design of wireless physical-layer confidentiality and authenticity under channel uncertainty. The insights could lead to a design of practical systems which are preparing the ground for confidentiality and authenticity already on the physical layer of the communication protocol stack.

The articles in this special issue highlight recent advances along with the remaining challenges in the field of physical-layer communications security.

For a physical layer message authentication procedure based on the comparison of channel estimates obtained from the received messages, we focus on an outer bound on the type I/II error probability region. Channel estimates are modeled as multivariate Gaussian vectors, and we assume that the attacker has only some side information on the channel estimate, which he does not know directly. We derive the attacking strategy that provides the tightest bound on the error region, given the statistics of the side information. This turns out to be a zero mean, circularly symmetric Gaussian density whose covariance matrices can be obtained by solving a constrained optimization problem. We propose an iterative algorithm for its solution: starting from the closed-form solution of a relaxed problem, we obtain, by projection, an initial feasible solution; then, by an iterative procedure, we look for the fixed-point solution of the problem. Numerical results show that for cases of interest the iterative approach converges, and perturbation analysis shows that the found solution is a local minimum.

We consider the distillation phase of the secret key agreement (SKA) channel model for users connected through parallel additive white Gaussian noise fading channels. Alice sends binary phase shift keying modulated random bits to Bob who selects the subset of bits that have a log-likelihood ratio higher than a given threshold, i.e., they are sufficiently reliable. Alice has either full or partial channel state information (CSI) on her channel to the eavesdropper Eve. The main contributions of this paper are: 1) the derivation of the expression of outage probability when partial CSI is available; 2) the introduction of (outage) secret key throughput (SKT) as a metric in the full (partial) CSI scenario; 3) the derivation of SKT bounds; 4) the proposal of a new power allocation and threshold choice algorithm that maximizes the SKT under an outage probability constraint; and 5) the derivation of a suboptimal version of the allocation algorithm amenable for practical implementation obtained by approximating the objective functions with a closed-form expression. Moreover, we show that when power allocation and thresholds are optimized, per-channel and joint SKA are equivalent.

A transmission between two agents, Alice and Bob, over a set of parallel sub-channels is overheard by a third agent Eve, through a second set of parallel sub-channels. All subchannels are flat with random and independent gains and additive white Gaussian noise (AWGN). Alice splits the total amount of available power among the sub-channels, with the purpose of maximizing the communication rate to Bob, under reliability and secrecy constraints. To this end, two schemes are considered. In one case the secret message is encoded with a single wiretap code and then split among the sub-channels. In the latter case the secret message is first split into a number of sub-messages, each separately encoded and transmitted on a different sub-channel. The achievable secrecy rates under a constraint on the secrecy outage probability (SOP) are derived and closed form expressions for Rayleigh fading sub-channels are obtained. In order to limit the complexity of resources optimization (power and rates) we also consider suboptimal solutions based on the selection of active sub-channels over which power is split either equally or according to a waterfilling algorithm with respect to the Alice-Bob channel.

Secure transmission between two agents, Alice and Bob, over block fading channels can be achieved similarly to conventional hybrid automatic repeat request (HARQ) by letting Alice transmit multiple blocks, each containing an encoded version of the secret message, until Bob informs Alice about successful decoding by a public error-free return channel. In existing literature each block is a differently punctured version of a single codeword generated with a Wyner code that uses a common randomness for all blocks. In this paper instead we propose a more general approach where multiple codewords are generated from independent randomnesses. The class of channels for which decodability and secrecy is ensured is characterized, with derivations for the existence of secret codes. We show in particular that the classes are not a trivial subset (or superset) of those of existing schemes, thus highlighting the novelty of the proposed solution. The result is further confirmed by deriving the average achievable secrecy throughput, thus taking into account both decoding and secrecy outage.

We consider a system where an agent (Alice) aims at transmitting a message to a second agent (Bob) over a set of parallel channels, while keeping it secret from a third agent (Eve) by using physical layer security techniques. We assume that Alice perfectly knows the set of channels with respect to Bob, but she has only a statistical knowledge of the channels with respect to Eve. We derive bounds on the achievable outage secrecy rates, by considering coding either within each channel or across all parallel channels. Transmit power is adapted to the channel conditions, with a constraint on the average power over the whole transmission. We also focus on the maximum cumulative outage secrecy rate that can be achieved. Moreover, in order to assess the performance in a real life scenario, we consider the use of practical error correcting codes. We extend the definitions of security gap and equivocation rate, previously applied to the single additive white Gaussian noise channel, to Rayleigh distributed parallel channels, on the basis of the error rate targets and the outage probability. Bounds on these metrics are also derived, considering the statistics of the parallel channels. Numerical results are provided, that confirm the feasibility of the considered physical layer security techniques.

We consider a scenario where agent Alice aims at transmitting a message to agent Bob, while keeping it secret from a third eavesdropper agent Eve. The transmissions occur on block-fading channels, and Alice only has a statistical channel state information (CSI) on both Bob and Eve channels. In this paper, we add secrecy features to hybrid automatic repeat request (HARQ) in what becomes a secure HARQ (S-HARQ) scheme. In particular, Alice encodes the secret message and splits the codeword into blocks. Then, she transmits one block at a time and after each transmission Bob feeds back an acknowledge (ACK) (not acknowledge (NACK)) packet, indicating he was (was not) able to decode the secret message. Upon an ACK Alice stops transmission, while upon a NACK Alice re-encodes the secret message into a new codeword and transmits it block by block, waiting for a new feedback. The process is iterated until either Bob decodes the message or a maximum number of codewords has been transmitted. We characterize the set of channels for which there exists a sequence of codes that ensure both vanishing error probability to Bob and vanishing rate of information leakage to Eve in the limit of infinitely long codewords. We also analyze the secrecy and decodability outage probabilities, providing closed form expressions for the case of additive white Gaussian noise channels with Rayleigh fading. The tradeoff between the number of blocks per codeword and the maximum number of codewords to be transmitted is also discussed.

For a cellular system where mobile terminals transmit in the uplink to base stations (BSs) using single carrier-frequency division multiple access (SC-FDMA), we consider multicell processing among BSs. Received signals are first quantized on a per-subcarrier basis and then forwarded to the serving BS on a backhaul with limited rate. With the aim of maximizing the network throughput we a) design an efficient composite signal representation and b) propose a rate allocation algorithm for the backhaul. Using a closed-form expression of the achievable throughput in the presence of quantization noise, an iterative greedy algorithm for the backhaul rate allocation is developed, where at each iteration we select the signal to be exchanged as the one providing the maximum network throughput increase per backhaul bit. In order to determine how many quantization bits are used for each received signal, we consider either a static bit allocation with a fixed number of bits, or a dynamic bit allocation (which ensures a predetermined network percentage throughput loss with respect to the unquantized case). In an LTE scenario, it is seen that the proposed bit allocation methods flexibly adapt to channel and backhaul conditions and yield similar performance, hence the static approach is preferred due to its lower complexity.

We consider the uplink of a cellular system where base stations (BSs) cooperate for decoding signals transmitted by mobile terminals (MTs). Assuming thatMTs transmit on orthogonal channels, each BS demodulates the signal coming from each MT, obtaining the log likelihood ratio (LLR) of each encoded bit. LLRs are quantized and quantization indices are forwarded on a backhaul to the radio network controller (RNC), where the reconstructed values are summed, and decoding takes place. BS-RNC links have a constraint on the maximum supported bit rate. We design the uniform quantizers in order to maximize the generalized mutual information (GMI) on the combined LLR over all MTs under the backhaul constraint. To this end, we derive the probability mass distribution (PMD) of the quantized LLR conditioned on the value of the transmitted bit, and we compute the GMI. We then propose a greedy scheduling algorithm for the choice of the number of bits used for the representation of each quantized signal exchanged on the backhaul.

We consider a wireless network where multiple nodes transmit to an access point (AP) with the assistance of relays. Nodes are assumed to be mobile, thus both relays and AP have only a partial knowledge of the channel on the links with nodes. Relays instead are fixed, so a perfect channel knowledge of AP-relays links can be assumed. Transmissions are organized in packets, with the use of hybrid automatic repeat request (HARQ) over many frames. At each frame we a) schedule transmission of nodes, and b) assign relays to nodes, i.e., decide which relay forwards data to the AP for each node. Both scheduling and assignment are made by computing the average capacity of the link between the nodes and the relays, based only on the knowledge of the second order statistics of the channel. The contribution of this paper is twofold. First, we derive analytically the constrained capacity for the correlated single input-multiple output (SIMO) channels. Then, we solve the allocation problem by a greedy approach.

Digital video broadcasting (DVB-C2) and other modern communication standards increase diversity by means of a symbol-level interleaver that spans over several codewords. De-interleaving at the receiver requires a large memory, which has a significant impact on the implementation cost. In this paper, we propose a technique that reduces the de-interleaver memory size. By quantizing log-likelihood ratios with bit-specific quantizers and compressing the quantized output, we can significantly reduce the memory size with a negligible increase in computational complexity. Both the quantizer and compressor are designed via a GMI-based maximization procedure. For a typical DVB-C2 scenario, numerical results show that the proposed solution enables a memory saving up to 30%.

Cooperative routing has been shown to be an effective technique to improve the throughput/delay performance of multi-hop wireless ad hoc networks. In addition, suitable cooperation selection policies also allow for a reduction of the overall energy expenditure. In a previous study, we proposed a centralized algorithm to obtain optimal cooperation selection policies in multi-hop networks with the aim of minimizing a linear combination of energy and delay costs. In this paper, we look at this problem from a different angle, devising three online and fully distributed algorithms which only exploit local interactions for the selection of the cooperators. The first technique selects at each hop a fixed number of nodes having the minimum distance with respect to the destination. The second one adopts a look-ahead strategy, which selects a fixed number of nodes at each hop, according to their expected advancement toward the destination. The third technique utilizes a more refined look-ahead strategy, which dynamically adjusts the number of nodes that cooperate at each hop. Numerical results are thus presented for the proposed techniques, comparing them against the optimal centralized strategy and competing algorithms from the literature. These results indicate that our techniques improve upon existing distributed approaches and achieve close-to-optimal performance.

In this paper we consider a downlink multi-cell scenario where a central processor is connected by a finite-throughput backhaul to base stations (BSs) employing beamforming and QAM constellations. Both the serving BS and auxiliary BSs transmit a signal that combines at the mobile terminal (MT) to provide a QAM symbol while achieving a diversity gain. In order to reduce backhaul occupation, auxiliary BSs receive from the central processor only a quantized version of the QAM symbols to be forwarded to MTs. We formalize the problem of maximizing the network spectral efficiency on air for all the MTs within an area illuminated by the cooperative BSs optimizing a) the QAM constellation size, b) the quantization rate dictated by the finite-throughput backhaul and c) the power allocated by each BS. Since the resulting optimization is a mixed integer programming problem, we investigate a suboptimal solution where the same power is allocated to each MT and obtain a simple iterative algorithm for the rate optimization. Numerical results show that for typical cellular scenarios the suboptimal approach yields a network spectral efficiency close to the theoretical limit of Slepian-Wolf encoding.

In a wide band and multipath rich environment, precise channel estimation allows authenticating the source and protecting the integrity of a message at the physical layer without the need of a pre-shared secret key. This allows also a reduction of the burden on the authentication protocols at higher layers. In this paper we develop an authentication scheme in the framework of hypothesis testing that suits a multiple wiretap channels environment with correlated fading, as is the case of multiple input multiple output (MIMO) systems and/or orthogonal frequency division multiplexing (OFDM) modulation. By allowing some degree of correlation among the channels, we formulate the optimal attack strategy for the cases of both single attempt and multiple repeated trials. For the latter scenario, due to the complexity of the optimal solution, we also develop a simpler suboptimal attack strategy. The performance of the proposed methods is evaluated in a MIMO/OFDM scenario and numerical results show the merits of the proposed approaches that can be adopted as a layer one authentication mechanism.

In a cooperative multi-cell network the uplink signal coming from each mobile terminal (MT) is simultaneously demodulated by multiple base stations (BSs). Both backhaul capacity and BS processing capabilities limit the number of demodulating BSs. In order to fit the information exchange among BSs to backhaul resources we minimize the average number of demodulating BSs, under a constraint on the average outage probability. The BS selection problem becomes more complicated when error control configurations as automatic repeat request (ARQ) and hybrid ARQ (HARQ) with chase combining or incremental redundancy are considered. Multi-cell processing is implemented both by decoding the packet at each BS and by a joint decoding among BSs. We first derive the outage probability as a function of the number of cooperating BSs and the error control strategy. A heuristic approach for BS selection is then developed, to find at each frame which BSs perform demodulation and share the information in the backhaul. Lastly, we show that backhaul usage can be reduced up to 64% with respect to an unoptimized solution.

In orthogonal frequency division multiplexing (OFDM) communication systems mobility results in time-variations of the channel, which yield intercarrier interference (ICI), especially when large OFDM blocks are employed in order to achieve a high spectral efficiency. In this letter we focus on systems with very long OFDM blocks, where many of the existing ICI mitigation techniques can not be applied due to complexity constraints. To mitigate ICI we propose a pre-equalizer, operating on sub-blocks of the received OFDM block, whose aim is to force all sub-blocks to have almost the same equivalent channel. In other words, the pre-equalizer combats only time variations of the channel. Next, after OFDM demodulation, the classical equalizer compensates frequency selectivity of the target channel. Performance of the proposed scheme, together with a suitable channel estimate implemented on a per sub-block basis, is evaluated for a digital video broadcasting scenario, according to the DVB-T2 standard, where the OFDM block size may be 32k, and its possible extension to hand-held devices in a next-generation DVB-H.

A cooperative network where the transmission between two nodes is assisted by many half-duplex relays over parallel Gaussian channels is considered. The parallel channel model is suitable for a broadband system, such as orthogonal frequency division multiplexing or a block fading channel. For the decode-and-forward protocol, an optimization problem for joint power, time and subchannel allocation under per-node power constraints is formulated to maximize the total transmission rate between the source and the destination. To solve this optimization problem, first the optimal power allocation for a given subchannel allocation is found. Then a greedy algorithm that jointly allocates subchannels and power is described. Finally, the time allocation is optimized by a numerical search procedure. The limiting case where the number of subchannels goes to infinity is also studied. Numerical results reveal that the achieved rate for the infinite number of subchannels is an upper bound for the finite subchannel case and the proposed greedy algorithm results in rates close to those for infinite number of subchannels when the number of subchannels is sufficiently large. Furthermore, most of the cooperative gains can be achieved by the use of a small number of relays.

In this paper we consider wireless cooperative multihop networks, where nodes that have decoded the message at the previous hop cooperate in the transmission toward the next hop, realizing a distributed space-time coding scheme. Our objective is finding optimal cooperator selection policies for arbitrary topologies with links affected by path loss and multipath fading. To this end, we model the network behavior through a suitable Markov chain and we formulate the cooperator selection process as a stochastic shortest path problem (SSP). Further, we reduce the complexity of the SSP through a novel pruning technique that, starting from the original problem, obtains a reduced Markov chain which is finally embedded into a solver based on focused real time dynamic programming (FRTDP). Our algorithm can find cooperator selection policies for large state spaces and has a bounded (and small) additional cost with respect to that of optimal solutions. Finally, for selected network topologies, we show results which are relevant to the design of practical network protocols and discuss the impact of the set of nodes that are allowed to cooperate at each hop, the optimization criterion and the maximum number of cooperating nodes.

In a cooperative multi-cell network we propose to simultaneously demodulate the uplink signal coming from mobile terminals (MTs) with multiple base stations (BSs) for a joint decoding of the data packets. However, limited backhaul capacity and BS demodulation capabilities limits the number of cooperating BSs. In this paper we consider MTs using a hybrid automatic repeat request (HARQ) protocol for error control, as in 3G and 4G cellular systems. In order to limit the exchange of information among BSs we aim at minimizing the number of demodulating BSs at each HARQ retransmission, under a constraint on the outage probability after a pre-set number of retransmissions. A greedy approach is developed for the system using HARQ, which determines at each retransmission which BSs must perform demodulation and share the information in the backhaul. Numerical results compare the performance of the proposed algorithm with existing solutions, showing that backhaul usage can be reduced up to 38% in a usual 3G scenario.

In recent years single carrier modulation (SCM) has again become an interesting and complementary alternative to multicarrier modulations such as orthogonal frequency division multiplexing (OFDM). This has been largely due to the use of nonlinear equalizer structures implemented in part in the frequency domain by means of fast Fourier transforms, bringing the complexity close to that of OFDM. Here a nonlinear equalizer is formed with a linear filter to remove part of intersymbol interference, followed by a canceler of remaining interference by using previous detected data. Moreover, the capacity of SCM is similar to that of OFDM in highly dispersive channels only if a nonlinear equalizer is adopted at the receiver. Indeed, the study of efficient nonlinear frequency domain equalization techniques has further pushed the adoption of SCM in various standards. This tutorial paper aims at providing an overview of nonlinear equalization methods as a key ingredient in receivers of SCM for wideband transmission. We review both hybrid (with filters implemented both in time and frequency domain) and all-frequency-domain iterative structures. Application of nonlinear frequency domain equalizers to a multiple input multiple output scenario is also investigated, with a comparison of two architectures for interference reduction. We also present methods for channel estimation and alternatives for pilot insertion. The impact on SCM transmission of impairments such as phase noise, frequency offset and saturation due to high power amplifiers is also assessed. The comparison among the considered frequency domain equalization techniques is based both on complexity and performance, in terms of bit error rate or throughput.

The real time estimation of the period of signals that are periodic over short time intervals requires fast algorithms. In this letter, the maximum likelihood (ML) period estimator is derived for a periodic signal with additive white Gaussian noise. A low complexity approximation is then proposed, and compared with the state of the art of the estimation techniques in a practical scenario for the remote estimation of human heart rate using an ultra wide band radar.

In an OFDM system using pilots for channel estimation, time interpolation among pilots of different OFDM symbols is commonly used to improve the estimate. The estimated channel impulse response may be also windowed to further reduce noise and disturbances. However, for a transmission over a time-varying channel, suboptimal time interpolation, implemented with a filter having only a few taps not matched to the maximum Doppler frequency, degrades channel estimation. In this paper we provide an analysis of the effects of pilot time interpolation over time-varying channels. We show in particular that suboptimal time interpolation yields aliases in the estimated channel impulse response and we derive a closed-form expression of the aliases¿ variance. As aliases can lead to an erroneous estimate of channel length and consequent errors in windowing, we propose a technique to detect aliases and correct the channel length estimate. Parameters of the detection techniques are optimized by an analysis that provides closed-form expressions of the false alarm and miss detection probabilities. Numerical results show the merits of the proposed techniques in a mobile transmission of the terrestrial digital video broadcasting standard (DVB-T).

CoopMAC has been recently proposed as a possible implementation of cooperation protocols in the medium access control (MAC) layer of a wireless network. However, some nodes may refrain from cooperation for selfish purposes, e.g. in order to save energy, in what is called selfish behavior or misbehavior. This protocol violation worsens other nodes' performance and can be avoided if other nodes detect and punish (e.g. banning from the network) misbehaving nodes. However, fading and interference may prevent nodes from cooperating even if they are willing, therefore it is not trivial to identify misbehaving nodes. In a fading scenario where an automatic repeat request (ARQ) protocol is used, we propose a mechanism that allows to detect misbehaving nodes. Two approaches, either based on the uniformly most powerful (UMP) test or on the sequential probability ratio test (SPRT) are considered. The two techniques are characterized and compared in terms of their average detection delay and resulting network performance.

In wireless cooperative transmissions, nodes may deviate from the cooperative protocol to reduce energy consumption while still reaping the benefits of other nodes' cooperation. Misbehavior is implemented by refraining from responding to cooperation request, mimicking adverse channel conditions. From time to time (with a given percentage) cooperations requests are accepted in order to avoid being detected as selfish. In this paper, we propose a technique for detecting misbehavior of nodes in an ad hoc network using carrier sense multiple access (CSMA) and automatic repeat request (ARQ) protocol. Each node can detect control packets of ARQ among source, destination and cooperating nodes, and collect statistics on their decoding probability. Selfish behavior is detected based on uniformly most powerful (UMP) test which yields the minimum miss detection probability for a given false alarm probability.

We propose two new receiver architectures for a ultra wide band (UWB) system based on the IEEE 802.15.4a standard. The design objective is robustness against strong multiple access interference (MAI). The first proposed structure models MAI as an additive white Gaussian noise (AWGN) whose power is estimated at each frame, rather than on average, in such a way to take account of the impulsive nature of interference. The second approach aims at jointly optimizing demodulation and decoding, and, in this case, MAI is modeled as a generalized Gaussian mixture process. In both cases, the maximum likelihood receiver is derived. Numerical results in a IEEE 802.15.4a scenario show that the AWGN receiver with local power estimate provides a performance comparable to the best existing techniques, while requiring a much lower computational complexity. The joint optimization of demodulation and decoding provides a further gain, especially at low packet error rates, at the cost of an additional signal processing effort. Still, low complexity solutions holding the performance gap are identified in this latter class.

We consider a network with an arbitrary number of nodes, where transmission of data packet is enhanced by a medium access control protocol that allows cooperation among nodes and solves transmission failures by an automatic repeat request (ARQ) protocol. Nodes operate in half-duplex mode and may interfere with each other as no coordination is assumed. In this scenario, we first derive the outage probability for a given number of interfering nodes and then relate the interference level to the single node behavior. We analyze the network behavior with a steady state analysis that matches the number of interfering nodes with the number of ARQ retransmissions. Two alternatives for cooperation are considered: decode and forward (DF) cooperation and multiple input-single output (MISO) cooperation, where for each packet transmission either one node transmits at a given time or two cooperating nodes transmit simultaneously. In our steady state analysis we also include an opportunistic version of DF, where cooperation is activated only when the quality of the cooperator-destination link is better than that of the source-destination link. Moreover, we investigate cooperator selection based on its distance to the destination.

We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. Within this framework the paper contains two main contributions. Firstly we provide joint conditions on the channel coherence bandwidth and the FB rate per RB that allow for a simpler quantization of the RB channel matrix (space-frequency) by a space vector, causing negligible performance loss in terms of system achievable throughput. This is accomplished after deriving a new metric for codebook design in RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.

We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. The paper has two main contributions: firstly we show conditions on the coherence bandwidth of the channel and the FB rate per RB that allow for a simpler characterization of the RB channel matrix by a space vector, causing negligible performance loss. This is accomplished after deriving a new performance metric for RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.

We design new receiver structures suited for the ultra wide band (UWB) standard IEEE 802.15.4a. The design objective is a receiver robust to multiuser access interference (MAI), which is a particular severe impairment in simple wireless personal area networks (W-PAN). Unlike most approaches of the literature that focus on the optimisation of decoding, we jointly optimize both demodulation and decoding, deriving new maximum likelihood (ML) schemes with enhanced capabilities in MAI rejection. In particular, a generalized Gaussian mixture model is assumed for the description of MAI, which includes as sub-cases the Gaussian and Laplacian models but has the potential to describe much more general scenarios. Simulations carried out on the IEEE 802.15.4a standard and including channel estimation show that the proposed approach significantly outperforms existing solutions in various channel and interference scenarios.

In a cellular system with partial channel state information, i.e. with limited feedback, and multiple antennas, we consider scheduling of downlink transmissions at the base station using beamforming and orthogonal frequency division multiplexing. As the complexity of optimal scheduling for throughput maximization under quality of service constraints grows exponentially with the number of subcarriers, in this paper we propose two low complexity suboptimal techniques. The first is a greedy iterative strategy that at each step selects one user with the aim of maximizing the weighted sum rate (WSR), without the need of recomputing the beamformer. We next propose a pre-selection strategy that removes from the selection process users that do not provide an increase in the WSR, thus speeding the search. Both complexity and performance of the proposed techniques are evaluated and compared with existing solutions in a long-term evolution 3GPP scenario.

For a network where each node has multiple antennas, we propose a transmission mode and a cooperation protocol, with the aim of maximizing the network throughput. The distinctive feature of the work is that the focus in both the design and the evaluation is at the network level, rather than on a single link. To this end, we propose the use of spatial multiplexing and code division multiple access (CDMA) to increase the parallelism of transmissions in the network, thus improving throughput. Cooperation is also implemented by spatial multiplexing and CDMA, together with an adaptive hybrid automatic repeat request mechanism that adapts the retransmissions to the actual channel conditions. Spatial multiplexing allows frame-asynchronous transmissions and a flexible cooperation protocol that minimizes the signaling overhead. The resulting scheme is named layered coded cooperative system (LCCS). We propose an implementation of LCCS based on linear erasure packet codes, where cooperation is transparent to the receiver, and we assess the performance of LCCS both by analyzing a simple network with three nodes and by simulating a more complex network.

We consider the uplink transmission of multimedia services in a cellular network where multiple access is implemented by code division multiple access (CDMA) and the base station performs successive interference cancellation (SIC) to enhance performance. We propose a cross-layer optimization technique that operates both at the physical layer, by selecting the detection order at the SIC receiver, and at the medium access control layer, by selecting the power/rate for each mobile terminal. The optimization objective is the maximization of the overall weighted network throughput with the satisfaction of the quality of service criteria for multimedia communications. The resulting problem turns out to be NP-complete and we resort to a discrete stochastic approximation (DSA) approach for its solution. Concerning DSA, an efficient implementation is proposed in order to reduce memory occupation and improve the convergence of the algorithm. In a UMTS cellular environment, numerical results show that the optimization provides a significant performance advantage over existing techniques at the cost of an increase of computational complexity and memory occupation.

For a cellular system based on frequency division duplexing where the base station (BS) is equipped with multiple antennas and the mobile terminals (MTs) have one antenna each, we propose joint techniques to a) feed back channel state information from MTs to the BS, b) design the beamformer and c) schedule downlink transmissions. We propose that both BS and MT predict channel variations, and the feedback (FB) information from MT to BS is given by the prediction error. For the beamformer design we both consider a zero forcing approach and investigate a new solution based on the minimum mean square error criterion, which takes into account the quantization error. By exploiting the FB information, we derive approximated expressions of the signal to noise ratio relative to each MT, used at BS to perform scheduling with an efficient greedy algorithm. Performance assessment on realistic 3GPP channel models show that the proposed techniques provide a significant improvement of the network throughput at a lower FB rate than existing solutions.

In this paper we design a network based on cooperative spatial multiplexing (SM), capable to adaptively support terminals with multiple antennas and multiple cooperating nodes. Our proposal overcomes limitations of existing cooperative networks based on space-time block codes (STBC), i.e., their need for symbol synchronization and signalling overhead for cooperation setup. Furthermore, the presented cooperation scheme is designed with the aim of improving the overall network performance, while most of the proposals in the literature focus on single link performance. SM is integrated with decision- feedback multiuser receivers for both the non-cooperative and the cooperative phases in order to maximize the use of radio resources. The cooperation efficiency is further enhanced by using a hybrid automatic repeat request (ARQ) mechanism for error control, implemented with linear erasure packet codes. Also in this case, the packet-based coding allows to have no signalling overhead for cooperation. Extensive results are provided, obtained by simulation of the complete PHY and MAC layers for a realistic network scenario with several nodes.

We derive the expressions of the outage probability for a wireless network that integrates hybrid automatic repeat request (HARQ) and coded cooperation among nodes. The medium access control (MAC) provides a HARQ protocol where the source node, upon a decoding failure at the destination node, transmits additional coded bits for the same data packet. If a neighbor node is able to decode the first transmission, it cooperates with the source by sending additional coded bits. In order to keep nodes simple, we assume half-duplex, single band asynchronous transmissions, and receivers with single user detection techniques. Various configurations of cooperation are considered and the analysis includes key characteristics of wireless communications and interference.

For a cooperative wireless network using delay diversity, the equivalent channel seen at the receiver is multipath and time-varying, as each transmitter has a local oscillator with a random frequency offset. The authors propose to use orthogonal frequency division multiplexing (OFDM) modulation, in order to efficiently implement equalization in the frequency domain; inter-carrier interference arising from multiple frequency offsets is instead compensated by a linear equalizer. For the estimate of the time-varying channel parameters a new technique was proposed that reduces the number of parameters to be estimated and exploits the multiple frequency-offsets.

In a broadband uplink code-division multiple-access transmission, the interference among users, depending on the correlation of specific channels and codes, may be significant. Hence, when successive interference cancellation (SIC) is performed at the base station, the minimization of power consumption at the mobile terminals is achieved if a joint optimization of power control and ordering (JOPCO) of user detection is carried out. In this paper, we first investigate a closed-form solution to JOPCO, based on the assumption of perfect interference cancellation and complete knowledge of channel correlation among users. By describing the JOPCO problem as an optimization on a suitable graph, it is seen that the optimum solution is NP-hard, and we approximate it by a greedy algorithm. For a practical implementation, we then model JOPCO as a discrete stochastic optimization problem, and we derive a discrete stochastic approximation (DSA) algorithm that iteratively adapts the transmit powers and the SIC detection order. The DSA solution removes the hypothesis on perfect cancellation and explicit knowledge of the users' correlation. Moreover, by a suitable description of the problem, we obtain a simplified DSA algorithm having reduced requirements in both computational complexity and memory. Performance of the various algorithms is assessed by simulations in a universal mobile telecommunications system scenario

Code-division multiple-access (CDMA) schemes based on block spreading implement the spreading of entire data blocks rather than single symbols, thus achieving a higher robustness against the frequency selectivity of the channel and allowing the use of efficient modulation/equalization schemes operating in the frequency domain (FD). In this paper, we present a new block CDMA (B-CDMA) system where a single cyclic prefix (CP) is used at the end of each spread block. This provides a higher spectral efficiency with respect to existing schemes. By observing that complete orthogonality among users is achievable only for half-loaded systems on dispersive channels, we introduce new criteria for the design of spreading and despreading sequences, which aim at minimizing the mean-square error at the output of the despreader. For the equalization of the received signal, we propose an iterative block decision feedback equalizer, which iterates between equalization and decoding. Equalization filters are designed to minimize the mean-square error and take into account the residual interference due to the nonorthogonality of the spreading sequences. The performance of B-CDMA is evaluated in an uplink wireless scenario and compared to existing CDMA schemes.

In this paper, we consider a MAC protocol for ad hoc networks where nodes are equipped with multiple antennas, and communications are spatially multiplexed using the Bell labs LAyered space time (BLAST) system. The contribution of this paper is twofold. First, we introduce two different analytical models aimed at predicting the propagation of detection errors within the BLAST receiver, the first based on a Gaussian approximation of the detection errors, and the second on the weighed enumeration of error configurations. A simplification of the latter, with lower complexity, is also obtained and compared to the original model. We then use these analytical tools to assess the performance of a cross–layer MAC protocol, and compare it with fully detailed simulations. Since the analytical tools replace the simulation of the physical layer, the proposed semianalytical approach is much faster than the bit-by-bit simulations. Numerous results are provided for the network performance assessment, showing that our semianalytical approach is able to predict network behavior with very good accuracy, but much lower complexity.

Orthogonal frequency division multiple access (OFDMA) and multicarrier code division multiple access (MC-CDMA) are possible candidates for the next generation of mobile wireless systems. However, when applied to an uplink broadband communication, MC-CDMA suffers from multiuser access interference, which can be reduced by using successive interference cancellation (SIC) at the base station. With this regard, here we propose an optimization of the MC-CDMA receiver that jointly determines power control and user detection ordering based on a discrete stochastic approximation algorithm. For OFDMA, we consider instead interleaved transmission and optimization of transmission power for each user. A comparison of OFDMA and MC-CDMA with SIC is then given in a multiuser uplink scenario in terms of sum-power for a required signal to noise ratio at the detection point.

In this paper, we consider a layered space-time multiuser detection technique and propose an analytical approximation for its performance. Our work is useful in two different stages of network design. On one hand, the approximation may be used to evaluate the bit and packet error performance of communications among a group of terminals making use of multiuser detection. On the other hand, it can also be seen as a very valuable tool from the networking point of view, as it may help in designing radio access control protocols based on multiuser detection, as analytical formulas are very fast to evaluate, in contrast to bit-level simulations that may need a long time to complete. Thus, an analytical formulation is important, because it helps discriminating among different protocol alternatives, speeding up considerably the protocol design phase and the development of new radio access policies for multiuser networks.

We consider the application of spatial multiplexing to ad hoc networks where nodes have multiple antennas. At the physical level, we suppose that layered space-time multiuser detection (LAST-MUD) is applied to separate multiple streams arriving at the receiver simultaneously. Our contributions here consist first in the reproduction of the multiuser detection process performance by a simple analysis, where we also specify when the analytical results are expected to be accurate and why. Second, we use this approximation to perform a cross-layer design of a MIMO ad hoc network where physical layer and medium access control strategies are integrated to maximize the network throughput. We finally corroborate our conclusions, by comparing analysis with simulation results both at the link and the network level

Existing cooperative diversity techniques for wireless ad hoc networks mostly consider space-time block codes for cooperation. In this paper we propose a cross-layer design of ad hoc wireless networks based on spatial multiplexing (SM). Each node is equipped with multiple antennas and the spatial dimensions of the channel are exploited to support multiple simultaneous transmissions. Diversity is then provided only for failed transmissions by means of selective cooperation among nodes that still use SM for transmission. Moreover, to increase the efficiency of the system, a hybrid automatic repeat request (HARQ) protocol integrated with packet coding is used at the medium access control layer. We analyze the proposed network architecture with a Markov chain description of the decoding process and we derive a closed form expression for the achieved throughput in Rayleigh fading channels.

In this paper we propose a new multiple user architecture for broadband wireless communications based on code division multiple access, denoted block CDMA (B-CDMA). The B-CDMA transmitter spreads the data on a block basis and a single cyclic prefix is used at the end of each spread block. We investigate the orthogonality of spreading sequences for B-CDMA, for an uplink broadband transmission and we design sequences that minimize the power of multiuser access interference. Equalization of the received signal is performed through an iterative block decision feedback equalizer (IBDFE). The B-CDMA system is compared to existing block spreading schemes in terms of achievable throughput for a wireless broadband uplink transmission

Successive interference cancellation (SIC) for code division multiple access (CDMA) systems, together with a suitable power control, is an attractive technique to reduce multiuser access interference in uplink transmissions. In this paper we propose a receiver design which minimizes the system transmit power while ensuring a constant signal to noise plus interference ratio (SNIR) at each user detection point by using a suitable order of user detection. Indeed, the problem is a joint optimization of power control and ordering of user detection and its optimum solution is NP-hard. Hence, we derive both a suboptimal greedy algorithm and a randomized search which explores many solutions. All these approaches are evaluated in an uplink multiuser scenario for the UMTS-TDD standard in terms of bit error rate and power consumption.

In this paper we propose a non linear equalization structure operating in the frequency domain (FD) for broadband wireless transmission. As a distinctive feature this equalizer does not require any block transmission format. By applying the feedforward filter in the FD with an overlap and save technique on blocks of the received signal, a bandwidth efficient decision feedback FD equalizer is derived, denoted extension-less FD-DFE (EL-FD-DFE). In order to reduce the inter-symbol (ISI) and inter-block (IBI) interference which affect the equalized signal, a IBI canceller is used among blocks, while the equalizer filters are designed taking into account the ISI due to the absence of the extension. A comparison with orthogonal frequency division multiplexing (OFDM) and existing equalizers is provided, showing that the EL-FD-DFE has a significantly higher achievable throughput

Error-propagation phenomena and computational complexity of the filters' design are important drawbacks of existing decision-feedback equalizers (DFE) for dispersive channels. In this paper, we propose a new iterative block DFE (IBDFE) which operates iteratively on blocks of the received signal. Indeed, a suitable data-transmission format must be used to allow an efficient implementation of the equalizer in the frequency domain, by means of the discrete Fourier transform. Two design methods are considered. In the first method, hard detected data are used as input of the feedback, and filters are designed according to the correlation between detected and transmitted data. In the second method, the feedback signal is directly designed from soft detection of the equalized signal at the previous iteration. Estimators of the parameters involved in the IBDFE design are also derived. From performance simulations on a wireless dispersive fading channel, we observed that the IBDFE outperforms existing DFEs. Moreover, the IBDFE exhibits a reduction of the computational complexity when compared against existing schemes, both in signal processing and in filter design.

In wireless broadband communications using code division multiple access (CDMA), interference cancellation (IC) techniques have been proposed to reduce multiuser access interference (MAI); however, their performance is limited by complexity constraints that still favor the use of rake receivers. In this paper, we propose an IC architecture that makes use of a block decision feedback equalizer (DFE) to remove intersymbol interference (ISI) and whose overall complexity is much lower than equivalent (in terms of performance) existing structures. In fact, by making use of a particular block data transmission format, all filters are implemented in the frequency domain (FD), and in particular, the DFE is iteratively designed according to the reliability of the detected data in the previous iteration. Due to the strong interaction of the FD-IC and the block DFE, error propagation in the receiver is reduced by simply interleaving (INT) chips before transmission. Simulations performed for an uplink communication on a wireless multipath channel show that the combination of FD-IC, block DFE, and chip INT provides an efficient solution with good performance for CDMA systems in dispersive channels.

In mobile reception, the reliability of orthogonal frequency division multiplexing (OFDM) is limited because of the time-varying nature of the channel. This causes intercarrier interference (ICI) and increases inaccuracies in channel tracking. We model the ICI using derivatives of the channel amplitude. This allows us to design a relatively simple receiver scheme that iteratively cancels the ICI. The design of the canceler aims at maximizing the signal-to-noise-plus-ICI ratio at the detector input. We also propose a new channel estimator, and we show that it achieves reliable mobile reception in practical situations that are relevant to terrestrial Digital Video Broadcasting (DVB-T). Extensive simulations for a receiver with one or two antennas show that a small number of iterations between ICI cancellation and channel estimation allow a reliable reception at vehicle speeds above 100 km/h.

In broadband code division multiple access (CDMA) communications, it has been shown that receivers based on successive interference cancellation (SIC) provide an effective reduction of multiuser access interference at an affordable complexity. We propose an optimization of CDMA systems by using power control and a suitable order of user detection at the SIC receiver. The aim is to minimize the total transmit power, while ensuring equal signal to noise plus interference ratio (SNIR) at the detection point for all users. Performance evaluation in an uplink multiuser scenario for the UMTS-TDD standard shows that the proposed algorithm provides energy saving of up to 7 dB in the absence of scrambling and up to 3 dB in the presence of scrambling, with respect to existing architectures based on SIC.

The filtered multitone (FMT) modulation requires both equalization of the transmission channel and of the transmit subchannel filters. Since decision feedback equalization is affected by error propagation and yields a greater complexity when combined with coding, in this paper we consider the use of pre-coding for FMT. However, by observing that precoding disrupts partially the subchannel orthogonality, we propose a new fractionally spaced pre-coding scheme, and consequently a novel subchannel filter design method based on a MSE criterion. The resulting scheme restores the subchannel orthogonality and it is also simpler than previous architectures. By simulations performed on an indoor broadband wireless transmission scenario we show that in general precoding schemes outperform equalization schemes. Furthermore, the fractionally spaced pre-coding scheme outperforms classical pre-coding schemes by about 2 dB.

The reception of the DVB-T signal on a mobile equipment is strongly affected by Doppler spread. Most of the current proposals require the use of two or more antennas at the receiver and a computationally expensive signal processing. In this paper for a DVB-T receiver with a single antenna we propose new schemes based on the interference cancellation principle. With respect to previously studied techniques, our solution is able to deliver DVB-T services at higher speeds, while a more flexible architecture allows a wider range of trade-off between complexity and performance. In order to improve the performance in terms of maximum achievable speed, an iterative scheme is proposed which performs both the interference cancellation and the channel estimation. A decoding and re-encoding of the inner convolutional code is inserted into the iteration process in order to boost the performance. Moreover, by applying the interference cancellation principle also for the estimation of the channel parameters, we obtain a scheme with a reasonable complexity for the DVB system. Simulation results for various DVB-T modes, constellations and code rates show that the proposed schemes allow the correct reception of DVB-T for moderate and high speeds.

Most comparisons between single carrier and multicarrier modulations assume frequency-domain linear equalization of the channel. We propose a new frequency-domain decision feedback equalizer (FD-DFE) for single carrier modulation, which makes use of a data block transmission format similar to that of the orthogonal frequency-division multiplexing with cyclic prefix (OFDM). The scheme is a nonadaptive DFE where the feedforward part is implemented in the frequency domain, while feedback signal is generated by time-domain filtering. Through simulations in a HIPERLAN-2 scenario, we show that FD-DFE yields a capacity very close to that of OFDM. This result is also confirmed by analytical derivations for a particular case. Furthermore, when no channel loading is considered, FD-DFE performs closely to OFDM for the same averaged frame error rate in a coded transmission. Design methods of the FD-DFE are investigated and a reduced complexity technique is developed, with the result that FD-DFE and OFDM have a similar computational complexity in signal processing.

Multicarrier systems are adopted in several standards for their ability to achieve optimal performance in very dispersive channels. In particular, orthogonal-frequency division multiplexing (OFDM) and filtered multitone (FMT) systems are two examples where the modulation filter has an ideal rectangular amplitude characteristic in time and frequency domains, respectively. In this letter, we propose new equalization schemes for FMT and compare their performances with OFDM. In general, FMT has a greater spectral efficiency than OFDM, due to the absence of the cyclic prefix and a reduced number of virtual carriers. However, it exhibits a higher distortion per subchannel, due to the imperfect equalization of the transmit filters. As a performance comparison, we considered both the achievable bit rate (ABR) and the bit error rate (BER) in a multipath Rayleigh fading channel. We note that while ABR gives a theoretical bound on the system bit rate, assuming the knowledge of the channel at the transmit side, the BER refers to an uncoiled system with a fixed modulation. Although FMT requires a fixed structure with a higher computational complexity than OFDM, it turns out that FMT, even with the simplest one tap per subchannel adaptive equalizer, yields a better performance than OFDM, both in terms of ABR and BER. Hence, FMT can be a valid alternative to OFDM for broadband wireless applications, also.

Approximations to the union bound performance of sequence detection in the presence of colored noise and an algorithm to compute bit error and error event probabilities are presented and compared to bit-by-bit simulation results. These computations, which are very accurate at bit error probabilities /spl les/10/sup -3/, are then used to analyze the performance of standard and reverse concatenated Reed-Solomon(RS)/modulation coding schemes for generalized partial-response channels corrupted by colored noise. The analysis is used to determine the optimum RS code rate for recording systems that are of current interest.