In this paper, we propose an integrated sensing and backscatter communication system utilizing high scanning-rate slot array antennas (SAAs) in a frequency-diverse configuration, leveraging an inverse scattering approach. This system employs a frequency diversity scheme to facilitate rapid spatial data acquisition, significantly outperforming traditional mechanical and electronic scanning methods in terms of speed and cost-efficiency. The proposed integrated system achieves simultaneous localization, identification, and backscatter communication of tags within cluttered environments. Our approach analyzes backscatter process based on the structural and antenna modes of tags, as well as the presence of clutter scatterers. By modulating the tags between open-circuit and short-circuit states, we effectively extract the structural and antenna mode components. The structural mode component allows us to sense both the tags and the surrounding clutter scatterers, while the antenna mode component is used for precise tag identification by incorporating both inverse scattering and compressive sensing (CS) algorithms. During these processes, channel state information (CSI) is gathered through the antenna mode, enhancing the backscatter communication capability of the system. Additionally, the efficacy of backscatter communication is assessed using the bit error rate (BER) with the maximum ratio combining (MRC) technique. Simulations and experimental results demonstrate that our proposed system can accurately sense and identify tags amidst clutter scatterers while maintaining robust backscatter communication over a 40 MHz bandwidth within the 3.98-4.02 GHz range. These results highlight the significant advantages of employing the proposed frequency-diverse antennas and the inverse scattering approach in integrated backscatter communication and sensing applications.

This paper proposes an innovative framework that integrates electromagnetic inverse scattering with improved quadrature spatial modulation (IQSM) to simultaneously accomplish sensing, identification, and backscatter communication. Specifically tailored for energy- and spectrum-efficient wireless operations in highly cluttered environments, the proposed system employs distinct load impedance modulation at the tags to effectively separate structural and antenna mode signatures. Structural mode signals are processed using inverse scattering combined with compressive sensing techniques, enabling precise localization of both tags and surrounding clutter. Concurrently, antenna mode signals are utilized for accurate tag identification. In addition, the antenna mode enables the acquisition of the reliable channel state information (CSI), facilitating the integration of IQSM schemes into the backscatter communication module. Furthermore, we present a theoretical analysis by deriving the bit error probability (BEP) for the proposed system. The proposed system is validated through a proof-of-concept experimental setup consisting of transmit and receive arrays, each configured as a 3×3 uniform linear antenna array (ULA). Both simulation and experimental results confirm that the inverse scattering-based approach achieves high-precision sensing and accurate identification of tags individually or in combination. Additionally, the integration of IQSM significantly enhances spectral efficiency (SE) and data throughput, compared with the state-of-the-art systems that do not incorporate spatial modulation (SM) techniques. These findings highlight the effectiveness and practical viability of the proposed integrated sensing and communication system for challenging clutter-rich scenarios.

In this work, we propose a compact millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system utilizing electronically steerable parasitic array radiator (ESPAR). We analyze the system and channel models for the compact mmWave massive MIMO system using a beamspace formulation and demonstrate that we can optimize the spectral efficiency of the compact mmWave massive MIMO system by jointly adjusting the variable reactive loads in the ESPAR with a digital beamformer. We formulate the compact mmWave massive MIMO system optimization problem to maximize spectral efficiency and propose an unconstrained optimization based algorithm with an initialization method. The spectral and energy efficiencies of the compact mmWave massive MIMO system are evaluated in comparison to conventional mmWave massive MIMO systems of the same antenna size using full-digital, fully-connected hybrid, and partially-connected hybrid beamforming. The results show that the compact mmWave massive MIMO system provides higher spectral efficiency than partially-connected hybrid beamforming. On top of this, it can provide higher energy efficiencies of around 3.21, 2.88, and 1.22 times compared to full-digital, fully-connected hybrid, and partially-connected hybrid beamforming but with lower hardware complexity and lower cost. Therefore, compact mmWave massive MIMO systems are a promising and effective alternative to conventional massive MIMO systems in millimeter wave (mmWave) communications.