Abstract: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.
Abstract: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.
Abstract:This paper develops a Doppler-aware sensing framework for cell-free massive MIMO (CF-mMIMO) networks operating under 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 the scalability, a user-target-centric AP association approach is utilized. The 3D tangential components of the target's velocity vector are estimated, and several search and optimization strategies, including coarse grid search, gradient-based refinement, and particle swarm optimization (PSO), are developed and evaluated. The Doppler-aware GLRT statistic and receive sensing signal-to-noise ratio (SNR) are derived. Simulation results demonstrate that the proposed PSO-aided detector achieves the most favorable accuracy-complexity trade-off, while Doppler mismatch can cause substantial sensing-SNR degradation in high-mobility scenarios. Additionally, leveraging more OFDM subcarriers enhances frequency-domain diversity and yields further sensing-SNR gains.
Abstract: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.
Abstract:This study investigates a communication-centric integrated sensing and communication (ISAC) system that utilizes orthogonal time frequency space (OTFS) modulated signals emitted by low Earth orbit (LEO) satellites to estimate the parameters of space targets experiencing range migration, henceforth referred to as high-speed targets. Leveraging the specific signal processing performed by OTFS transceivers, we derive a novel input-output model for the echo generated by a high-speed target in scenarios where ideal and rectangular shaping filters are employed. Our findings reveal that the target response exhibits a sparse structure in the delay-Doppler domain, dependent solely upon the initial range and range-rate; notably, range migration causes a spread in the target response, marking a significant departure from previous studies. Utilizing this signal structure, we propose an approximate implementation of the maximum likelihood estimator for the target's initial range, range-rate, and amplitude. The estimation process involves obtaining coarse information on the target response using a block orthogonal matching pursuit algorithm, followed by a refinement step using a bank of matched filters focused on a smaller range and range-rate region. Finally, numerical examples are provided to evaluate the estimation performance.
Abstract: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.
Abstract: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.
Abstract: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.
Abstract: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.
Abstract:In this work, we consider a transmit architecture where few active antennas (sources), each equipped with a dedicated radio frequency chain, illuminate a reconfigurable intelligent surface (RIS) that control the beam-steering capability of the whole system. In this framework, we tackle the beampattern design problem, where the waveform emitted by the sources and the phase shifts introduced by the RIS are designed so that the realized beampattern matches, in a least-square sense, the desired one. The design of this architecture can be useful in many areas, such as radar detection and tracking, millimeter wave, sub-THz, and THz communications, and integrated sensing and communications. We provide a sub-optimum solution to the beampattern design problem, and we report an example to show that this RIS-based transmit architecture can be competitive with respect to fully-digital MIMO systems, especially if constant-modulus waveforms are required.