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Emanuele Grossi

Publications and source records attributed to Emanuele Grossi.

At least 19 recordsLinked to original sources

Joint Detection and Velocity Estimation in OFDM-ISAC Cell-Free Massive MIMO Networks

This paper develops a sensing framework for cell-free massive MIMO (CF-mMIMO) networks operating under orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC). The framework explicitly incorporates the 3D bistatic Doppler geometry across distributed access points (APs) into a generalized likelihood ratio test (GLRT) detector. To address system scalability, a user-target-centric AP association approach is utilized. The 3D velocity vector of the target is estimated, and several search and optimization strategies, including coarse grid search, gradient-based refinement, and particle swarm optimization (PSO), are developed and evaluated. Simulation results demonstrate that the proposed PSO-aided detector achieves the most favorable accuracy-complexity trade-off, while Doppler mismatch can cause substantial sensing signal-to-noise ratio (SNR) degradation in high-mobility scenarios. Additionally, leveraging more OFDM subcarriers enhances frequency-domain diversity and yields further sensing-SNR gains.

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Parameter estimation of range-migrating targets using OTFS signals from LEO satellites

This study investigates a communication-centric integrated sensing and communication system that utilizes orthogonal time-frequency space (OTFS) modulated signals emitted by low Earth orbit (LEO) satellites to estimate the initial-range, range-rate, and amplitude of point-like targets experiencing range migration under a first-order range model over the OTFS frame. Leveraging the signal samples produced by off-the-shelf OTFS demodulators, we derive the delay-Doppler-domain input-output relationship governing the target echo under both ideal and rectangular shaping filters. The target response exhibits a sparse structure in the delay-Doppler domain, whose support is determined by the target initial-range and range-rate. Exploiting this sparse model, we derive a lower-complexity approximation of the maximum-likelihood estimator for the target parameters. The proposed method first obtains coarse estimates of the target initial-range and range-rate using block orthogonal matching pursuit; then, a bank of matched filters focused on a smaller initial-range/range-rate region refines these two estimates and computes the amplitude estimate. The single-target procedure is extended to multiple targets via iterative estimation, reconstruction, and cancellation of dominant echoes. Finally, numerical examples are provided to evaluate the estimation performance.

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A Comparison Between Co-Located and Distributed MIMO Deployments in OFDM-ISAC Networks

This paper investigates network-level integrated sensing and communication (ISAC) under two fundamentally different topology configurations: cell-free massive MIMO (CF-mMIMO) and multi-cell massive MIMO (MC-mMIMO). A unified OFDM-based waveform is adopted for both architectures as the key enabler for ISAC functionalities. The CF system exploits distributed access points (APs) and a scalable user-target-centric operation, whereas the MC system relies on co-located transmit-receive arrays with conventional cell-centric deployment. For both architectures, we derive a GLRT-based sensing detector and the corresponding sensing SNR expressions. We then examine a series of case studies investigating how the number of OFDM subcarriers, the transceiver allocation strategy, and the antenna/node distribution across the network affect the sensing performance. The results consistently demonstrate that CF-mMIMO provides more robust and higher sensing performance across most tested scenarios, particularly when transmit resources or antenna elements are spatially distributed. These findings highlight the inherent advantages of CF deployments for next-generation ISAC networks.

cs.IT

Waveform Index Modulation for Backscatter Communications in RIS-Based MIMO Radars

This paper studies a symbiotic system in which a reconfigurable intelligent surface (RIS) assists a radar transmitter while conveying information to a reader via backscattering. The RIS is partitioned into subarrays that redirect the radar signal toward the angular sector under inspection and superimpose a slow-time modulation using orthogonal phase codes, thereby implementing MIMO radar functionalities. Communication is achieved by encoding information in the selection of an unordered subset of orthogonal codewords, without altering the RIS transmit beampattern. At the reader, the proposed index modulation scheme enables low-complexity detection without requiring channel state information. Numerical results demonstrate the effectiveness of the proposed backscatter communication approach.

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Beampattern Design for Transmit Architectures Based on Reconfigurable Intelligent Surfaces

In this work, we tackle the problem of beampattern design for a transmit system employing a large reconfigurable intelligent surface (RIS) to redirect radio frequency signals emitted by a few active antennas (sources). We begin by establishing a convenient signal model and discussing the impact of signal bandwidth, source-RIS channel, and system geometry on our derivations. Subsequently, we propose a joint optimization of the waveform emitted by each source and the phase shifts introduced by the RIS. The objective is to match a desired space-frequency distribution of the far-field radiation pattern, relevant to both radar and communication applications. We present a sub-optimal solution to this problem, subject to a constraint on the total power radiated by the sources and, optionally, on the constant modulus of the waveforms. The provided example demonstrates the effective beampattern shaping capabilities of this RIS-based transmit architecture. Specifically, for the same array size and the same desired radiation pattern, the resulting approximation error is comparable to that obtained with a fully-digital MIMO array, especially when constant-modulus waveforms are enforced, and significantly smaller than that of a phased array.

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RIS-Enabled Transmitter Design for Joint Radar and Communication

Achieving efficient and cost-effective transmit beampattern control for integrated sensing and communication (ISAC) systems is a significant challenge. This paper addresses this by proposing a dual-function radar communication (DFRC) transmitter based on a reconfigurable intelligent surface (RIS) illuminated by a limited number of active sources. We formulate and solve the joint design of source waveforms and RIS phase shifts to match a desired space-frequency radiation pattern, and we evaluate the resulting ISAC system's performance in terms of radar detection probability and data transmission rate. Numerical results demonstrate the promising capabilities of this RIS-enabled transmitter for ISAC applications.

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STAR-RIS Transceivers: Integrated Sensing and Communication with Pulsed Signals

This study examines an integrated sensing and communication (ISAC) transceiver featuring a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and a receiver equipped with a passive electronically scanned array (PESA) and a single digital channel. By utilizing a periodic pulsed signal emitted by a feeder, we introduce at the STAR-RIS a space modulation to illuminate two angular directions observed by the radar receiver, one in each half-space, and a time modulation to distinguish the corresponding echoes from prospective moving targets and embed communication messages. The proposed time modulation employs orthogonal binary codebooks with different trade-offs in transmission and error rates, while having minimal impact on the radar performance, evaluated by probability of detection and root mean square error in the radial velocity estimation.

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Track-before-detect in RIS-aided Integrated Sensing and Communication

This study considers a base station equipped with sensing and communication capabilities, which serves a ground user and scans a portion of the sky via a passive reconfigurable intelligent surface. To achieve more favorable system tradeoffs, we utilize a multi-frame radar detector, comprising a detector, a plot-extractor, and a track-before-detect processor. The main idea proposed here is that user spectral efficiency can be enhanced by increasing the number of scans jointly processed by the multi-frame radar detector while maintaining the same sensing performance. A numerical analysis is conducted to verify the effectiveness of the proposed solution and to evaluate the achievable system tradeoffs.

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Integrated Communication and RIS-aided Track-Before-Detect Radar Sensing

This paper investigates an integrated sensing and communication system where the base station serves multiple downlink users, while employing a passive reconfigurable intelligent surface to detect small, noncooperative airborne targets. We propose a method to design the two-way beampattern of the RIS-assisted monostatic radar, which allows controlling the sidelobe levels in the presence of eavesdroppers, jammers, and other scattering objects and avoiding any radar interference to the users. To obtain more favorable system tradeoffs, we exploit the correlation of the target echoes over consecutive scans by resorting to a multi-frame radar detector, which includes a detector, a plot-extractor, and a track-before-detect processor. A numerical analysis is provided to verify the effectiveness of the proposed solutions and to assess the achievable tradeoffs. Our results show that, by increasing the number of scans processed by the radar detector (and therefore its implementation complexity), we can reduce the amount of power dedicated to the radar function while maintaining the same sensing performance (measured in terms of probability of target detection and root mean square error in the estimation of target position); this excess power can be reused to increase the user sum-rate.

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STAR-RIS-based Pulse-Doppler Radars

In this study, we consider a pulse-Doppler radar relying on a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) for scanning a given volume; the radar receiver is collocated with the STAR-RIS and aims to detect moving targets and estimate their radial velocity in the presence of clutter. To separate the echoes received from the transmissive and reflective half-spaces, the STAR-RIS superimposes a different slow-time modulation on the pulses redirected in each half-space, while the radar detector employs a decision rule based on a generalized information criterion (GIC). Two scanning policies are introduced, namely, simultaneous and sequential scanning, with different tradeoffs in terms of radial velocity estimation accuracy and complexity of the radar detector.

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Semi-Blind Multi-Tag Ambient Backscatter Communications Using Radar Signals

In this work, we consider a backscatter communication system wherein multiple asynchronous sources (tags) exploit the reverberation generated by a nearby radar transmitter as an ambient carrier to deliver a message to a common destination (reader) through a number of available subchannels. We propose a new encoding strategy wherein each tag transmits both pilot and data symbols on each subchannel and repeats some of the data symbols on multiple subchannels. We then exploit this signal structure to derive two semi-blind iterative algorithms for joint estimation of the data symbols and the subchannel responses that are also able to handle some missing measurements. The proposed encoding/decoding strategies are scalable with the number of tags and their payload and can achieve different tradeoffs in terms of transmission and error rates. Some numerical examples are provided to illustrate the merits of the proposed solutions.

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Beampattern design for radars with reconfigurable intelligent surfaces

We consider a radar architecture where an illuminator composed of few sources is used as a feeder for a (passive) reconfigurable intelligent surface (RIS), so as to mimic the behavior of a multiple-input multiple-output (MIMO) radar composed of as many active elements as the RIS. In this framework, we study the problem of beampattern design in the space-frequency domain, and we propose to choose the source signals and the RIS adjustable phases in order to minimize the weighted squared error between the desired (amplitude) beampattern and the synthesized one. A low complexity iterative algorithm is proposed to solve the resulting non-convex least square problem. An example is provided to show the merits of the proposed approach.

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Radar-enabled ambient backscatter communications

In this work, we exploit the radar clutter (i.e., the ensemble of echoes generated by the terrain and/or the surrounding objects in response to the signal emitted by a radar transmitter) as a carrier signal to enable an ambient backscatter communication from a source (tag) to a destination (reader). The proposed idea relies on the fact that, since the radar excitation is periodic, the radar clutter is itself periodic over time scales shorter than the coherence time of the environment. Upon deriving a convenient signal model, we propose two encoding/decoding schemes that do not require any coordination with the radar transmitter or knowledge of the radar waveform. Different tradeoffs in terms of transmission rate and error probability can be obtained upon changing the control signal driving the tag switch or the adopted encoding rule; also, multiple tags can be accommodated with either a sourced or an unsourced multiple access strategy. Some illustrative examples are provided.

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Subspace-Based Detection and Localization in Distributed MIMO Radars

In this paper, we consider a distributed multiple-input multiple-output (MIMO) radar which radiates waveforms with non-ideal cross- and auto-correlation functions and derive a novel subspace-based procedure to detect and localize multiple prospective targets. The proposed solution solves a sequence of composite binary hypothesis testing problems by resorting to the generalized information criterion (GIC); in particular, at each step, it aims to detect and localize one additional target, upon removing the interference caused by the previously-detected targets. An illustrative example is provided.

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Spatial Diversity in Radar Detection via Active Reconfigurable Intelligent Surfaces

Active reconfigurable intelligent surfaces (RISs) are a novel and promising technology that allows controlling the radio propagation environment while compensating for the product path loss along the RIS-assisted path. In this letter, we consider the classical radar detection problem and propose to use an active RIS to get a second independent look at a prospective target illuminated by the radar transmitter. At the design stage, we select the power emitted by the radar, the number of RIS elements, and their amplification factor in order to maximize the detection probability for a fixed probability of false alarm and a common (among radar and RIS) power budget. An illustrative example is provided to assess the achievable detection performance, also in comparison with that of a radar operating alone or with the help of a passive RIS.

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MIMO OFDM Dual-Function Radar-Communication Under Error Rate and Beampattern Constraints

In this work we consider a multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system, which senses multiple spatial directions and serves multiple users. Upon resorting to an orthogonal frequency division multiplexing (OFDM) transmission format and a differential phase shift keying (DPSK) modulation, we study the design of the radiated waveforms and of the receive filters employed by the radar and the users. The approach is communication-centric, in the sense that a radar-oriented objective is optimized under constraints on the average transmit power, the power leakage towards specific directions, and the error rate of each user, thus safeguarding the communication quality of service (QoS). We adopt a unified design approach allowing a broad family of radar objectives, including both estimation- and detection-oriented merit functions. We devise a suboptimal solution based on alternating optimization of the involved variables, a convex restriction of the feasible search set, and minorization-maximization, offering a single algorithm for all of the radar merit functions in the considered family. Finally, the performance is inspected through numerical examples.

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Foundations of MIMO Radar Detection Aided by Reconfigurable Intelligent Surfaces

A reconfigurable intelligent surface (RIS) is a nearly-passive flat layer made of inexpensive elements that can add a tunable phase shift to the impinging electromagnetic wave and are controlled by a low-power electronic circuit. This paper considers the fundamental problem of target detection in a RIS-aided multiple-input multiple-output (MIMO) radar. At first, a general signal model is introduced, which includes the possibility of using up to two RISs (one close to the radar transmitter and one close to the radar receiver) and subsumes both a monostatic and a bistatic radar configuration with or without a line-of-sight view of the prospective target. Upon resorting to a generalized likelihood ratio test (GLRT), the design of the phase shifts introduced by the RIS elements is formulated as the maximization of the probability of detection in the location under inspection for a fixed probability of false alarm, and suitable optimization algorithms are proposed. The performance analysis shows the benefits granted by the presence of the RISs and shed light on the interplay among the key system parameters, such as the radar-RIS distance, the RIS size, and location of the prospective target. A major finding is that the RISs should be better deployed in the near-field of the radar arrays at both the transmit and the receive side. The paper is concluded by discussing some open problems and foreseen applications.

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Radar Target Detection aided by Reconfigurable Intelligent Surfaces

In this work, we consider the target detection problem in a sensing architecture where the radar is aided by a reconfigurable intelligent surface (RIS), that can be modeled as an array of sub-wavelength small reflective elements capable of imposing a tunable phase shift to the impinging waves and, ultimately, of providing the radar with an additional echo of the target. A theoretical analysis is carried out for closely- and widely-spaced (with respect to the target) radar and RIS and for different beampattern configurations, and some examples are provided to show that large gains can be achieved by the considered detection architecture.

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