In this paper, we propose a novel frequency-modulated continuous wave (FMCW)-enabled integrated sensing, identification, and backscatter communication (ISIBC) system design for 6G Internet of Things (IoT). In this system, during the sensing stage, the base station (BS) emits the FMCW signal, and from the echo signal, it estimates the angles of arrival (AoAs) and ranges of multiple targets to obtain their positions while simultaneously identifying these targets through detecting the symbols transmitted by the attached backscatter devices (BDs). In particular, we first formulate precise models for the echo signal and the discrete beat signal at the uniform linear array (ULA). To eliminate the inter-symbol interference (ISI), we propose a zero-padded BD symbol pattern. Subsequently, by leveraging the proposed BD symbol pattern and a truncation operation, we further reformulate the discrete beat signal model into an explicit third-order tensor model. Next, building on the reformulated tensor model, we propose a canonical polyadic decomposition (CPD)-based algorithm for joint parameter estimation and BD symbol detection. Finally, numerous simulation results are provided to validate the effectiveness and excellent performance of the proposed FMCW-enabled ISIBC system design.

This paper introduces a novel frequency-modulated continuous wave (FMCW)-enabled integrated sensing, identification, and backscatter communication (ISIBC) system to support the emerging low-altitude economy (LAE). In this system, during the sensing stage, the ground base station (GBS) utilizes the FMCW radar to estimate the range and radial velocity of the unmanned aerial vehicle (UAV), and concurrently to identify the UAV through detecting the symbols transmitted by the attached backscatter device (BD). In particular, we first formulate explicit signal models for the echo signal and the discrete beat signal. To mitigate the inter-symbol interference (ISI), we propose a zero-padded BD symbol pattern. Subsequently, the beat signal model is reformulated into a rank-1 matrix model through the proposed BD symbol pattern and the truncation operation. Next, based on the rank-1 matrix model, we propose a singular value decomposition (SVD)-based algorithm for joint parameter estimation and BD symbol detection. Finally, extensive simulation results are provided to demonstrate the effectiveness and superior performance of the proposed ISIBC system design for LAE.

The emerging integrated sensing and backscatter communication (ISABC), is expected to provide a new paradigm for Internet of Things (IoT) applications. In this paper, we propose a novel radar-enabled ISABC (R-ISABC) system design, where the signal processing center (SPC) can simultaneously perform localization for multiple targets and symbol detection for multiple backscatter devices (BDs) without requiring knowledge of the exact waveform of the radar signal. In particular, we first characterize the received signal models using the angle of arrivals (AOAs) of targets, symbol vectors transmitted by BDs, and the environment radar reverberation, and then an explicit third-order tensor model is elaborated by leveraging the periodicity of the radar reverberation and rearranging the sampled received signals. Then, we propose a novel CANDECOMP/PARAFAC decomposition (CPD)-assisted joint angle estimation and BD symbol detection algorithm based on the formulated third-order tensor model with the differential coding adopted at each BD. Numerous simulation results verify the feasibility and effectiveness of the R-ISABC system design.

Multiple-input multiple-output orthogonal time frequency space (MIMO-OTFS) systems have gained increasing attention due to their superior performance in double-selective channel scenarios. However, MIMO-OTFS systems typically suffer from high pilot overhead and complex channel estimation (CE) when the number of antennas is large. To tackle these issues, in this paper, we propose a novel transceiver design, consisting of a new transceiver architecture, a low-overhead pilot pattern, and the corresponding low-complexity CE algorithm. Specifically, firstly, we apply the Inverse Discrete Fourier Transformation (IDFT) module at the transmitter (TX) and the corresponding Discrete Fourier Transformation (DFT) module at the receiver (RX), by resorting to which the received signals can be separated effectively in the time-delay-angular (TDA) domain to greatly reduce the inter-path and inter-antenna interferences. Secondly, at the TX, we design a new pilot pattern that removes the guard region and the length of which does not increase with the number of transmit antennas (TAs), leading to significantly reduced pilot overhead and increased spectral efficiency. Thirdly, at the RX, we utilize the three-dimensional (3D) sparsity of the MIMO-OTFS channel in the delay-Doppler-angular (DDA) domain to correspondingly achieve a low-complexity CE algorithm. Extensive numerical results demonstrate the effectiveness of our proposed transceiver design.