Emanuele Grossi

This work investigates a radar-centric integrated sensing and communication (ISAC) transceiver that incorporates a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and a radar receiver equipped with a passive electronically scanned array (PESA) and a single digital channel. A periodic pulsed waveform, emitted by a feeder, illuminates the STAR-RIS, which applies space-time modulation to the redirected pulses. The spatial response of the STAR-RIS and the spatial beamformer of the radar receiver are jointly designed to illuminate desired directions on each side of the STAR-RIS, i.e., those monitored by the radar and those corresponding to communication users, while mitigating clutter returns. Time modulation enables both the embedding of communication data and the assignment of unique signatures to echoes from each side of the STAR-RIS. Two encoding schemes are proposed, enabling either simultaneous or sequential illumination of the two sides, while the corresponding radar and communication receivers are designed using a generalized information criterion. Several trade-offs between radar and communication functionalities can be achieved by adjusting the STAR-RIS and PESA array power patterns; in addition, the proposed data encoding schemes allow different data transmission and error rates, while having minimal impact on the radar performance.

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.

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.

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.

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.

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.

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.

In this paper, we consider a monostatic radar and study the joint detection and localization of a prospective target when the receiver is assisted by a reconfigurable intelligent surface (RIS). To mitigate the multiplicative path loss in the target-RIS-radar hops, we resort to an active RIS, which allows both redirecting and amplifying the incident signal. Upon choosing the array gain factor of the radar transmitter and the RIS to uniformly cover the inspected region, the joint target detection and localization is formulated as a composite hypothesis testing problem, which is solved via a generalized likelihood ratio test (GLRT). Numerical examples are provided to show the merits of the proposed architecture.

This paper deals with the problem of joint detection and localization of multiple targets in a distributed multiple-input multiple-output radar system where the emitted waveforms present imperfect auto- and cross-correlation functions. In this context, the sidelobe masking effects can considerably degrade the detection and localization performance of correlation-based detectors. To address this issue, we first derive a convenient discrete-time signal model, wherein the echoes generated by a target towards each receive antenna are regarded as a subspace signal. Then, we formulate the joint detection and localization problem as a composite multiple hypothesis test and derive the optimal solution according to a generalized information criterion, whose complexity scales exponentially with the number of prospective targets. To reduce the computational burden, we derive two iterative approximate solutions which detect and localize one target at a time from the noisy data, upon mitigating the sidelobe masking caused by the previously-detected ones. Finally, we provide an extensive numerical analysis to demonstrate the effectiveness of the proposed solutions, even in the challenging case where an unknown number of strong and weak targets is present in the covered area.

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.