arXiv subjects

Tommaso Bacchielli

Publications and source records attributed to Tommaso Bacchielli.

4 recordsLinked to original sources

arXiv2026

Extremely Large Antenna Spacing Method for Enhanced Wideband Near-Field Sensing

This paper proposes a monostatic wideband system for integrated sensing and communication (ISAC) at millimeter-wave frequencies, based on multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM). The system operates in a hybrid near-/far-field regime. The transmitter (Tx) operates in the far field (FF) and uses low-complexity beam steering. The receiver (Rx), on the other hand, operates in a pervasive near field (NF), enabled by a very large effective array aperture. To enable a fully digital implementation, we introduce an extremely large antenna spacing (ELAS) design. This design attains the required aperture with only a few widely spaced antenna elements while avoiding grating lobes in the composite Tx-Rx response. We analytically characterize the NF range-angle response of this architecture and study the interplay between NF effects and waveform bandwidth. This leads to the definition of a super-resolution region, where NF propagation at the Rx dominates the achievable range resolution and surpasses the classical, bandwidth-limited resolution. As a case study, we consider an extended target modeled as a collection of scatterers and assess localization performance via maximum-likelihood estimation. Numerical results evaluated in terms of root mean square error (RMSE) and generalized optimal sub-pattern assignment (GOSPA) show that operating in NF conditions with the ELAS-based design yields significant gains compared to a conventional FF baseline at both the Tx and Rx.

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arXiv2024

Cooperative Maximum Likelihood Target Position Estimation for MIMO-ISAC Networks

This letter investigates target position estimation in integrated sensing and communication networks composed of multiple cooperating monostatic base stations (BSs). Each BS employs a MIMO-orthogonal time-frequency space (OTFS) scheme, enabling the coexistence of communication and sensing. A general cooperative maximum likelihood (ML) framework is derived, directly estimating the target position in a common reference system rather than relying on local range and angle estimates at each BS. Positioning accuracy is evaluated in single-target scenarios by varying the number of collaborating BSs, using root mean square error (RMSE), and comparing against the square root of the Cram\'er-Rao lower bound. Numerical results demonstrate that the ML framework significantly reduces the position RMSE as the number of cooperating BSs increases.

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arXiv2024

Bistatic Sensing at THz Frequencies via a Two-Stage Ultra-Wideband MIMO-OFDM System

Only the chairs can edit The availability of abundant bandwidth at terahertz (THz) frequencies holds promise for significantly enhancing the sensing performance of integrated sensing and communication (ISAC) systems in the next-generation wireless systems, enabling high accuracy and resolution for precise target localization. In orthogonal frequency-division multiplexing (OFDM) systems, wide bandwidth can be achieved by increasing the subcarrier spacing rather than the number of subcarriers, thereby keeping the complexity of the sensing system low. However, this approach may lead to an ambiguity problem in target range estimation. To address this issue, this work proposes a two-stage maximum likelihood method for estimating target position in an ultra-wideband bistatic multiple-antenna OFDM-based ISAC system operating at THz frequencies. Numerical results show that the proposed estimation approach effectively resolves the ambiguity problem while achieving high resolution and accuracy target position estimation at a very low signal-to-noise ratio regime.

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arXiv2023

Performance Analysis of a Low-Complexity OTFS Integrated Sensing and Communication System

This work proposes a low-complexity estimation approach for an orthogonal time frequency space (OTFS)-based integrated sensing and communication (ISAC) system. In particular, we first define four low-dimensional matrices used to compute the channel matrix through simple algebraic manipulations. Secondly, we establish an analytical criterion, independent of system parameters, to identify the most informative elements within these derived matrices, leveraging the properties of the Dirichlet kernel. This allows the distilling of such matrices, keeping only those entries that are essential for detection, resulting in an efficient, low-complexity implementation of the sensing receiver. Numerical results, which refer to a vehicular scenario, demonstrate that the proposed approximation technique effectively preserves the sensing performance, evaluated in terms of root mean square error (RMSE) of the range and velocity estimation, while concurrently reducing the computational effort enormously.

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