Abstract:Reconfigurable intelligent surface-assisted integrated sensing and communication (RIS-ISAC) presents a promising system architecture to leverage the wide bandwidth available at millimeter-wave (mmWave) frequencies, while mitigating severe signal propagation losses and reducing infrastructure costs. To enhance ISAC functionalities in the future air-ground integrated network applications, RIS deployment must be carefully designed and evaluated, which forms the core motivation of this paper. To ensure practical relevance, a multi-RIS-ISAC system is established, with its signal model at mmWave frequencies demonstrated using ray-launching calibrated to real-world environments. On this basis, an energy-efficiency-driven optimization problem is formulated to minimize the multi-RIS size-to-coverage sum ratio, comprehensively considering real-world RIS deployment constraints, positions, orientations, as well as ISAC beamforming strategies at both the base station and the RISs. To solve the resulting non-convex mixed-integer problem, a simplified reformulation based on equivalent gain scaling method is introduced. A two-step iterative algorithm is then proposed, in which the deployment parameters are determined under fixed RIS positions in the first step, and the RIS position set is updated in the second step to progressively approach the optimum solution. Simulation results based on realistic parameter benchmarks present that the optimized RISs deployment significantly enhances communication coverage and sensing accuracy with the minimum RIS sizes, outperforming existing approaches.
Abstract:Multistatic integrated sensing and communications (ISAC) systems, which use distributed transmitters and receivers, offer enhanced spatial coverage and sensing accuracy compared to stand-alone ISAC configurations. However, these systems face challenges due to interference between co-existing ISAC nodes, especially during simultaneous operation. In this paper, we analyze the impact of this mutual interference arising from the co-existence in a multistatic ISAC scenario, where a mono- and a bistatic ISAC system share the same spectral resources. We first classify differenct types of interference in the power domain. Then, we discuss how the interference can affect both sensing and communications in terms of bit error rate (BER), error vector magnitude (EVM), and radar image under varied transmit power and RCS configurations through simulations. Along with interfernce analysis, we propose a low-complexity successive interference cancellation method that adaptively cancels either the monostatic reflection or the bistatic line-of-sight signal based on a monostatic radar image signal-to-interference-plus-noise ratio (SINR). The proposed framework is evaluated with both simulations and proof-of-concept measurements using an ISAC testbed with a radar echo generator for object emulation. The results have shown that the proposed method reduces BER and improves EVM as well as radar image SINR across a wide range of SINR conditions. These results demonstrate that accurate component-wise cancellation can be achieved with low computational overhead, making the method suitable for practical applications.
Abstract:In future sixth-generation (6G) mobile networks, radar sensing is expected to be offered as an additional service to its original purpose of communication. Merging these two functions results in integrated sensing and communication (ISAC) systems. In this context, bistatic ISAC appears as a possibility to exploit the distributed nature of cellular networks while avoiding highly demanding hardware requirements such as full-duplex operation. Recent studies have introduced strategies to perform required synchronization and data exchange between nodes for bistatic ISAC operation, based on orthogonal frequency-division multiplexing (OFDM), however, only for single-input single-output architectures. In this article, a system concept for a bistatic multiple-input multiple-output (MIMO)-OFDM-based ISAC system with beamforming at both transmitter and receiver is proposed, and a distribution synchronization concept to ensure coherence among the different receive channels for direction-of-arrival estimation is presented. After a discussion on the ISAC processing chain, including relevant aspects for practical deployments such as transmitter digital pre-distortion and receiver calibration, a 4x8 MIMO measurement setup at 27.5 GHz and results are presented to validate the proposed system and distribution synchronization concepts.
Abstract:Conventional base station (BS) deployments typically prioritize coverage, quality of service (QoS), or cost reduction, often overlooking electromagnetic field (EMF) exposure. Whereas EMF exposure triggers significant public concern due to its potential health implications, making it crucial to address when deploying BS in densely populated areas. To this end, this paper addresses minimizing average EMF exposure while maintaining coverage in a 3D urban scenario by jointly optimizing BS deployment and power. To address this, firstly, accurate EMF prediction is essential, as traditional empirical models lack the required accuracy, necessitating a deterministic channel model. A novel least-time shoot-and-bounce ray (SBR) ray-launching (RL) algorithm is therefore developed to overcome several limitations of current simulators and is validated with real-world measurements. Secondly, to further reduce computational complexity, unlike using a fixed grid size to discretize the target area, the adaptive grid refinement (AGR) algorithm is designed with a flexible grid to predict the overall EMF exposure. Finally, based on the EMF exposure predictions, the Nelder-Mead (NM) method is used in the joint optimization, and urban user equipment (UE) distributions are incorporated to better reflect real-world conditions. When evaluating the benefits of the whole process, the results are compared against using empirical channel models, revealing notable differences and underestimation of EMF exposure that highlight the importance of considering real-world scenario.
Abstract:Integrated sensing and communication (ISAC) is a novel capability expected for sixth generation (6G) cellular networks. To that end, several challenges must be addressed to enable both mono- and bistatic sensing in existing deployments. A common impairment in both architectures is oscillator phase noise (PN), which not only degrades communication performance, but also severely impairs radar sensing. To enable a broader understanding of orthogonal-frequency division multiplexing (OFDM)-based sensing impaired by PN, this article presents an analysis of sensing peformance in OFDM-based ISAC for different waveform parameter choices and settings in both mono- and bistatic architectures. In this context, the distortion of the adopted digital constellation modulation is analyzed and the resulting PN-induced effects in range-Doppler radar images are investigated both without and with PN compensation. These effects include peak power loss of target reflections and higher sidelobe levels, especially in the Doppler shift direction. In the conducted analysis, these effects are measured by the peak power loss ratio, peak-to-sidelobe level ratio, and integrated sidelobe level ratio parameters, the two latter being evaluated in both range and Doppler shift directions. In addition, the signal-to-interference ratio is analyzed to allow not only quantifying the distortion of a target reflection, but also measuring the interference floor level in a radar image. The achieved results allow to quantify not only the PN-induced impairments to a single target, but also how the induced degradation may impair the sensing performance of OFDM-based ISAC systems in multi-target scenarios.
Abstract:Enabling bistatic radar sensing within the context of integrated sensing and communication (ISAC) for future sixth generation mobile networks demands strict synchronization accuracy, which is particularly challenging to be achieved with over-the-air synchronization. Existing algorithms handle time and frequency offsets adequately, but provide insufficiently accurate sampling frequency offset (SFO) estimates that result in degradation of obtained radar images in the form of signal-to-noise ratio loss and migration of range and Doppler shift. This article introduces an SFO estimation algorithm named tilt inference of time offset (TITO) for orthogonal frequency-division multiplexing (OFDM)-based ISAC. Using available pilot subcarriers, TITO obtains channel impulse response estimates and extracts information on the SFO-induced delay migration to a dominant reference path with constant range, Doppler shift, and angle between transmit and receive ISAC nodes. TITO then adaptively selects the delay estimates that are only negligibly impaired by SFO-induced intersymbol interference, ultimately employing them to estimate the SFO. Assuming a scenario without a direct line-of-sight (LoS) between the aforementioned transmitting and receiving ISAC nodes, a system concept with a relay reflective intelligent surface (RIS) is used to create the aforementioned reference path is proposed. Besides a mathematical derivation of accuracy bounds, simulation and measurements at 26.2 GHz are presented to demonstrate TITO's superiority over existing methods in terms of SFO estimation accuracy and robustness.
Abstract:Integrated sensing and communication (ISAC) has been defined as one goal for 6G mobile communication systems. In this context, this article introduces a bistatic ISAC system based on orthogonal frequency-division multiplexing (OFDM). While the bistatic architecture brings advantages such as not demanding full duplex operation with respect to the monostatic one, the need for synchronizing transmitter and receiver is imposed. In this context, this article introuces a bistatic ISAC signal processing framework where an incoming OFDM-based ISAC signal undergoes over-the-air synchronization based on preamble symbols and pilots. Afterwards, bistatic radar processing is performed using either only pilot subcarriers or the full OFDM frame. The latter approach requires estimation of the originally transmitted frame based on communication processing and therefore error-free communication, which can be achieved via appropriate channel coding. The performance and limitations of the introduced system based on both aforementioned approaches are assessed via an analysis of the impact of residual synchronization mismatches and data decoding failures on both communication and radar performances. Finally, the performed analyses are validated by proof-of-concept measurement results.
Abstract:This article introduces adaptations to the conventional frame structure in binary phase-modulated continuous wave (PMCW) radars with sequence generation via linear-feedbck shift registers and additional processing steps to enable joint radar-communication (RadCom) operation. In this context, a preamble structure based on pseudorandom binary sequences (PRBSs) that is compatible with existing synchronization algorithms is outlined, and the allocation of pilot PRBS blocks is discussed. Finally, results from proof-of-concept measurements are presented to illustrate the effects of the choice of system and signal parameters and validate the investigated PMCW-based RadCom system and synchronization strategy.
Abstract:This article introduces a bistatic joint radar-communication (RadCom) system based on orthogonal frequency-division multiplexing (OFDM). In this context, the adopted OFDM frame structure is described and system model encompassing time, frequency, and sampling synchronization mismatches between the transmitter and receiver of the bistatic system is outlined. Next, the signal processing approaches for synchronization and communication are discussed, and radar sensing processing approaches using either only pilots or a reconstructed OFDM frame based on the estimated receive communication data are presented. Finally, proof-of-concept measurement results are presented to validate the investigated system and a trade-off between frame size and the performance of the aforementioned processing steps is observed.
Abstract:In recent years, orthogonal chirp-division multiplexing (OCDM) has been increasingly considered as an alternative multicarrier scheme, e.g., to orthogonal frequency-division multiplexing, in digital communication applications. Among reasons for thar are its demonstrated superior performance resulting from its robustness to impairments such as frequency selectivity of channels and intersymbol interference. Furthermore, the so-called unbiased channel estimation in the discrete-Fresnel domain has also been investigated for both communication and sensing systems, however without considering the effects of frequency shifts. This article investigates the suitability of the aforementioned discrete-Fresnel domain channel estimation in OCDM-based radar systems as an alternative to the correlation-based processing previously adopted, e.g., in the radar-communication (RadCom) literature, which yields high sidelobe level depending on the symbols modulated onto the orthogonal subchirps. In this context, a mathematical formulation for the aforementioned channel estimation approach is introduced. Additionally, extensions to multi-user/multiple-input multiple-output and RadCom operations are proposed. Finally, the performance of the proposed schemes is analyzed, and the presented discussion is supported by simulation and measurement results. In summary, all proposed OCDM-based schemes yield comparable radar sensing performance to their orthogonal frequency-division multiplexing counterpart, while achieving improved peak-to-average power ratio and, in the RadCom case, communication performance.