User Localization with HRIS and Backscatter Modulation for Next-Generation Networks

Hybrid reflective intelligent surfaces (HRISs) can support localization in sixth-generation (6G) networks thanks to their ability to generate narrow beams and at the same time receive and process locally the impinging signals. In this paper, we propose a novel protocol for user localization in a network with an HRIS. The protocol includes two steps. In the first step, the HRIS operates in full absorption mode and the user equipment (UE) transmits a signal that is locally processed at the HRIS to estimate the angle of arrival (AoA). In the second step, the base station transmits a downlink reference signal to the UE, and the HRIS superimposes a message by a backscatter modulation. The message contains information on the previously estimated AoA. Lastly, the UE, knowing the position of the HRIS, estimates the time of flight (ToF) from the signal of the second step and demodulates the information on the AoA to obtain an estimate of its location. Numerical results confirm the effectiveness of the proposed solution, also in comparison with the Cram\'er Rao lower bound on the estimated quantities.nd on the estimated quantities.

Scheduling for Downlink OFDMA With IRS Reconfiguration Constraints

The technical limitations of the intelligent reflecting surface (IRS) (re)configurations in terms of both communication overhead and energy efficiency must be considered when IRSs are used in cellular networks. In this paper, we investigate the downlink time-frequency scheduling of an IRS-assisted multi-user system in the orthogonal frequency-division multiple access (OFDMA) framework wherein both the set of possible IRS configurations and the number of IRS reconfigurations within a time frame are limited. We formulate the sum rate maximization problem as a non-polynomial (NP)-complete generalized multi-knapsack problem. A heuristic greedy algorithm for the joint IRS configuration and time-frequency scheduling is also proposed. Numerical simulations prove the effectiveness of our greedy solution.

Minimum-Latency Scheduling For Partial-Information Multiple Access Schemes

Partial-information multiple access (PIMA) is an orthogonal multiple access (OMA) uplink scheme where time is divided into frames, each composed of two parts. The first part is used to count the number of users with packets to transmit, while the second has a variable number of allocated slots, each assigned to multiple users to uplink data transmission. We investigate the case of correlated user activations, wherein the correlation is due to the retransmissions of the collided packets, modeling PIMA as a partially observable-Markov decision process. The assignment of users to slots is optimized based on the knowledge of both the number of active users and past successful transmissions and collisions. The scheduling turns out to be a mixed integer nonlinear programming problem, with a complexity exponentially growing with the number of users. Thus, sub-optimal greedy solutions are proposed and evaluated. Our solutions show substantial performance improvements with respect to both traditional OMA schemes and conventional PIMA.

Semi-Grant-Free Orthogonal Multiple Access with Partial-Information for Short Packet Transmissions

Next-generation internet-of-things (IoT) networks require extremely low latency, complexity, and collision probability. We introduce the novel partial-information multiple access (PIMA) scheme, a semi-grant-free (GF) coordinated random access (RA) protocol for short packet transmission, with the aim of reducing the latency and packet loss of traditional multiple access schemes, as well as more recent preamble-based schemes. With PIMA, the base station (BS) acquires partial information on instantaneous traffic conditions in the partial information acquisition (PIA) sub-frame, estimating the number of active devices, i.e., having packets waiting for transmission in their queue. Based on this estimate, the BS chooses both the total number of slots to be allocated in the data transmission (DT) sub-frame and the respective user-to-slot assignment. Although collisions may still occur due to multiple users assigned to the same slot, they are drastically reduced with respect to the slotted ALOHA (SALOHA) scheme, while achieving lower latency than both time-division multiple-access (TDMA) and preamble-based protocols, due to the extremely reduced overhead of the PIA sub-frame. Finally, we analyze and assess the performance of PIMA under various activation statistics, proving the robustness of the proposed solution to the intensity of traffic, also with burst traffic.

Downlink Clustering-Based Scheduling of IRS-Assisted Communications With Reconfiguration Constraints

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 sub-optimal 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.

Estimation of Interference Correlation in mmWave Cellular Systems

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.

Partial-Information Multiple Access Protocol for Orthogonal Transmissions

With the stringent requirements introduced by the new sixth-generation (6G) internet-of-things (IoT) use cases, traditional approaches to multiple access control have started to show their limitations. A new wave of grant-free (GF) approaches have been therefore proposed as a viable alternative. However, a definitive solution is still to be accomplished. In our work, we propose a new semi-GF coordinated random access (RA) protocol, denoted as partial-information multiple access (PIMA), to reduce packet loss and latency, particularly in the presence of sporadic activations. We consider a machine-type communications (MTC) scenario, wherein devices need to transmit data packets in the uplink to a base station (BS). When using PIMA, the BS can acquire partial information on the instantaneous traffic conditions and, using compute-over-the-air techniques, estimate the number of devices with packets waiting for transmission in their queue. Based on this knowledge, the BS assigns to each device a single slot for transmission. However, since each slot may still be assigned to multiple users, collisions may occur. Both the total number of allocated slots and the user assignments are optimized, based on the estimated number of active users, to reduce collisions and improve the efficiency of the multiple access scheme. To prove the validity of our solution, we compare PIMA to time-division multiple-access (TDMA) and slotted ALOHA (SALOHA) schemes, the ideal solutions for orthogonal multiple access (OMA) in the time domain in the case of low and high traffic conditions, respectively. We show that PIMA is able not only to adapt to different traffic conditions and to provide fewer packet drops regardless of the intensity of packet generations, but also able to merge the advantages of both TDMA and SALOHA schemes, thus providing performance improvements in terms of packet loss probability and latency.

Secret-Key-Agreement Advantage Distillation With Quantization Correction

We propose a novel advantage distillation strategy for physical layer-based secret-key-agreement (SKA). We consider a scenario where Alice and Bob aim at extracting a common bit sequence, which should remain secret to Eve, by quantizing a random number obtained from measurements at their communication channel. We propose an asymmetric advantage distillation protocol with two novel features: i) Alice quantizes her measurement and sends partial information on it over an authenticated public side channel, and ii) Bob quantizes his measurement by exploiting the partial information. The partial information on the position of the measurement in the quantization interval and its sharing allows Bob to obtain a quantized value closer to that of Alice. Both strategies increase the lower bound of the secret key rate.

On the Limits of Cross-Authentication Checks for GNSS Signals

Global navigation satellite systems (GNSSs) are implementing security mechanisms: examples are Galileo open service navigation message authentication (OS-NMA) and GPS chips-message robust authentication (CHIMERA). Each of these mechanisms operates in a single band. However, nowadays, even commercial GNSS receivers typically compute the position, velocity, and time (PVT) solution using multiple constellations and signals from multiple bands at once, significantly improving both accuracy and availability. Hence, cross-authentication checks have been proposed, based on the PVT obtained from the mixture of authenticated and non-authenticated signals. In this paper, first, we formalize the models for the cross-authentication checks. Next, we describe, for each check, a spoofing attack to generate a fake signal leading the victim to a target PVT without notice. We analytically relate the degrees of the freedom of the attacker in manipulating the victim's solution to both the employed security checks and the number of open signals that can be tampered with by the attacker. We test the performance of the considered attack strategies on an experimental dataset. Lastly, we show the limits of the PVT-based GNSS cross-authentication checks, where both authenticated and non-authenticated signals are used.

On the Optimal Spoofing Attack and Countermeasure in Satellite Navigation Systems

The threat of signal spoofing attacks against 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.