Automotive Millimeter-wave (mmWave) radar is becoming an essential modality for autonomous vehicles to enable all-weather perception, especially when LiDAR and camera fail in foggy, rainy, or snowy conditions. It is expected that the mutual interference among multiple radars becomes a critical issue in dense traffic scenarios, which can severely degrade the radar performance and lead to accidents. Despite extensive interference mitigation techniques, none can meet the less valid signal distortion while high robustness requirements for automotive radar perception in dense traffic scenarios. To overcome this predicament, we propose mmMic, a novel multiple mutual interference mitigation system that can accurately separate interference and recover valid signals to maintain the reliability of the radar measurements. The key insight is to design an interference estimator that can accurately localize the interference signal according to its linear frequency modulation features in the time-frequency (TF) domain. In addition, mmMic also fully exploits undisturbed valid signal information within an extended time-frequency domain to reconstruct the damaged signal. Our experiments on a real testbed show that mmMic can improve SINR to interference-free levels from multiple radars, achieving an average SINR improvement of 17% compared to the best-performing baseline.

Joint transmit-receive (JTR) beamforming is a key technique for multi-input multi-output (MIMO) integrated sensing and communication (ISAC) systems. Existing JTR designs assume independent communication and sensing channels and optimize beamforming only at the base station (BS), leaving the angular-domain correlation and the spatial degrees-of-freedom of user equipment (UE) unexploited. This paper investigates a communication-centric JTR design for downlink MIMO-ISAC under correlated channels, involving both the BS and a multi-antenna UE. A unified optimization problem is developed for both multiplexing and diversity modes to maximize the communication sum-rate under the constraints of sensing signal-to-clutter-and-noise ratio and transmit power. To solve the non-convex problem, a full-dimensional JTR (Full-JTR) method is proposed based on an alternating optimization framework. To reduce the computational burden in massive MIMO scenarios, a low-complexity power-allocation-based JTR (PA-JTR) method is further developed. Simulation results demonstrate that the Full-JTR method outperforms baseline methods in both modes. Moreover, the PA-JTR method achieves performance close to the Full-JTR method in both multiplexing and diversity modes with significantly lower computational complexity.

In future vehicular networks, emerging applications such as collaborative perception are expected to support flexible integrated sensing and communication functionalities and ubiquitous computing services. However, limited wireless and computational resources require joint design of sensing, communication, and computation to enhance overall system efficiency. In this paper, we formulate a joint precoding and detection (JPD) problem under a multi-objective optimization framework to address the physical-layer co-design of sensing and communication. To further support collaborative perception tasks, we extend the formulation to a joint precoding, detection, and resource allocation (JPDRA) problem by further incorporating mobile edge computing. First, we propose a multi-task learning (MTL) scheme to solve the JPD problem, where a Transformer-based network is designed to generate precoding and detection matrices, and a gradient and uncertainty weighting (GUW) algorithm is developed for balancing different subtasks. Next, we propose a multi-agent deep reinforcement learning (MADRL) scheme by adopting a GUW-enhanced minimax multi-agent deep deterministic policy gradient algorithm and transfer learning to solve the JPDRA problem. Finally, simulation results demonstrate that the proposed MTL scheme strikes an effective balance between communication and sensing, while the proposed MADRL scheme yields an 8.6% increase in collaborative perception gain over the baselines with 5 vehicles and 16 antennas.

The integrated sensing and communication (ISAC) design in vehicle-to-everything (V2X) scenarios introduces specific challenges for automotive radar sensing. For instance, the cochannel interference (CCI) caused by communication tasks and the non-line-of-sight propagation from multipaths generate false targets and sensing ghosts that do not exist in reality, thereby compromising the accuracy of environmental detection by the ISAC system. In this paper, we focus on accurate detection for four-dimensional (4D) multiple-input multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) ISAC systems in V2X with CCI and sensing ghosts. First, we propose a peak vector crossover product accumulation (PVCPA) algorithm for target detection while simultaneously filtering out CCI false targets in the range-Doppler domain. Next, we introduce a partial rotational invariance-based multiple signal classification (PRI-MUSIC) algorithm for near-field direction of arrival (DoA) estimation. We also proposed a method that distinguishes real scatterers from ghosts by further exploiting the ranges obtained by range-Doppler estimation and DoA estimation. Experimental results demonstrate that the PVCPA algorithm is effective in CCI false target filtering, and the PRI-MUSIC algorithm achieves high estimation accuracy with low computational complexity, particularly for the range estimation, which in turn provides good ghost suppression performance for the proposed method.

In this paper, we propose symbol-length transceive filter optimization methods for sidelobe suppression in filter bank based orthogonal time frequency space (FB-OTFS) systems. Specifically, we firstly establish the FB-OTFS system model with fast implementation for transceive filters. Then, we analyze the impact of the transceive filters on the orthogonal transmission and derive the constraints for symbol-length transceive filters to achieve the orthogonal transmission. Moreover, the complexity analysis is provided. With the derived orthogonal conditions as constraints, we formulate a transceive filter optimization problem to minimize the stopband energy (a commonly used sidelobe suppression criterion), and derive the theoretically optimal solutions. To further achieve flexible suppression of the spectral sidelobes within specific frequency intervals, we formulate a transceive filter optimization to minimize the weighted stopband energy by designing adjustable frequency domain weights, and also obtain the optimal solutions. Numerical results demonstrate that: 1) The proposed transceive filters have the lowest spectral sidelobes compared with the commonly used rectangular pulse and the Gaussian filter; 2) The sidelobe suppression effects within specific frequency intervals are successfully controlled by designing the frequency domain weights; 3) All proposed transceive filters are verified to satisfy the orthogonal conditions.

The last few decades have witnessed the rapid development of passive backscatter technologies, which envision promising cost-efficient ambient Internet of Things (IoT) for various applications, such as distributed solar sensor networks. However, limited by the harmonic interference caused by the conventional frequency-shifting-based backscatter control methods, existing backscatter communication technologies cannot support the growing scale of the network. To tackle this issue, we propose a harmonic interference resilient frequency-shifting technique to compress the harmonics during backscatter communication. Different from conventional backscatter tags that shift the frequency with square waves with a constant pulse width, we dynamically modify the pulse width of the square wave to compress different parts of the harmonic waves. Furthermore, we propose a lightweight communication coding algorithm to enhance the compatibility of our system with backscatter applications. We implement the system with off-the-shelf components and conduct comprehensive experiments to evaluate the performance. The results demonstrate our harmonic interference resilient backscatter system can compress the harmonic interference and reduce the BER (bit error rate) by 70%.

Integrated sensing and communication (ISAC) system utilizes multi-antenna arrays to transmit integrated signals, enabling multi-target sensing and simultaneous communication with multiple communication users (CUs). This requires the transmit signal to have sufficient degrees of freedom (DoF) for sensing and a high communication rate for effective communication. However, the DoF of the transmit signal is limited by the quantity of uncorrelated communication symbol streams (CSSs) in the ISAC system. To address this limitation, we employ space-time coding (STC) to extend CSSs, which not only provides additional DoF for sensing but also offers diversity gain for communication. Moreover, we optimize the transmit beampattern while ensuring that the signal-to-interference-plus-noise ratio (SINR) for each CU remains above a specified threshold. Consequently, we formulate an optimization problem with rank constraints and derive a suboptimal solution. The simulation results demonstrate that the proposed method achieves a better beampattern and a higher communication rate compared to previous work.

Despite the promising prospects of reusing ambient carriers for ultra-low-power communication, backscatter tags also suffer severe interference from ambient carriers, which limits their performance. Existing backscatter approaches avoid interference by shifting scattered signals away from the carrier, leading to spectral wastage and making large-scale deployment impractical. To address this issue, this paper proposes the first Ambient Carrier Interference Cancellation (ACIC) system for backscatter communication, especially tailored for Distributed photovoltaic (PV) scenarios. ACIC has the following novel components: (i) a carrier-detecting scheme that detects and filters out the carrier from the received ambient signals; (ii) an adaptive interference-cancellation system that cancels the carrier with programmable phase shift and attenuator; (iii) an acceleration algorithm to enhance the speed of the cancellation. We then implement the ACIC system and conduct comprehensive experiments to evaluate its performance. Our results demonstrate that the ACIC system achieves greater than 40 dB interference cancellation, both with and without a backscatter tag. Unlike frequency-shifting schemes that sacrifice spectral efficiency, our ACIC achieves in-band carrier cancellation, reducing BER from 0.5 to 0.03 at 0.5 m distance. This improvement enables reliable and scalable battery-free sensing in distributed PV systems.

Backscatter technologies promise to enable large-scale, battery-free sensor networks by modulating and reflecting ambient radio frequency (RF) carriers rather than generating new signals. Translating this potential into practical deployments—such as distributed photovoltaic (PV) power systems—necessitates realistic modeling that accounts for deployment variabilities commonly neglected in idealized analyses, including uncertain hardware insertion loss, non-ideal antenna gain, spatially varying path loss exponents, and fluctuating noise floors. In this work, we develop a practical model for reliable backscatter communications that explicitly incorporates these impairing factors, and we complement the theoretical development with empirical characterization of each contributing term. To validate the model, we implement a frequency-shift keying (FSK)-based backscatter system employing a non-coherent demodulation scheme with adaptive bit-rate matching, and we conduct comprehensive experiments to evaluate communication range and sensitivity to system parameters. Experimental results demonstrate strong agreement with theoretical predictions: the prototype tag consumes 825 µW in measured operation, and an integrated circuit (IC) implementation reduces consumption to 97.8 µW, while measured communication performance corroborates the model’s accuracy under realistic deployment conditions.

In this paper, we investigate the frequency domain phase noise estimation in millimeter wave filter-bank multicarrier with offset quadrature amplitude (mmWave FBMC-OQAM) systems. In the frequency domain, the primary impairment introduced by phase noise is the common phase error (CPE), whose estimation performance is significantly affected by the inter-carrier interference (ICI) and inter-symbol interference (ISI) experienced by OQAM symbols. To address the above problem, we propose novel frequency domain phase noise estimation and pilot symbol design methods to mitigate the impact of ICI and ISI. Firstly, we quantify the interferences affecting each pilot symbol and design appropriate weights to mitigate the impact of ICI and ISI on the phase noise estimation. Then, through analysis, we observe that the ICI and ISI originate from the interaction between the imaginary intrinsic interferences and the phase noise terms. Accordingly, we propose a pilot symbol design method by eliminating the primary imaginary intrinsic interferences, thereby reducing the ICI and ISI. Furthermore, we analyze the mean squared error (MSE) lower bound and the computational complexity. Simulation results demonstrate that the proposed phase noise estimation method outperforms the traditional method and the proposed pilot structure further improves the accuracy of the phase noise estimation.

A new sidelobe suppression method is proposed for filter bank multi-carrier systems using offset quadrature amplitude modulation (FBMC-OQAM), where we jointly optimize the prototype filter and the symbol distribution to minimize the normalized stopband energy of FBMC-OQAM signals. Firstly, we investigate the relationship between both the signal sidelobe and the prototype filter as well as the symbol distribution by deriving the general power spectral density (PSD) expression of the FBMC-OQAM signals of each subcarrier. Then, we investigate the impact of the prototype filter and the symbol distribution on the symbol reconstruction by deriving the inter-symbol interference (ISI) and inter-carrier interference (ICI) expressions of FBMC-OQAM systems. Based on the PSD and ISI/ICI expressions derived, we formulate and solve the joint prototype filter and symbol distribution optimization problem. Our simulations demonstrated that the proposed joint prototype filter and symbol distribution optimization method achieves lower normalized stopband energy and better sidelobe suppression of the first sidelobe than the single-parameter based prototype filter optimization methods.

In this paper, we propose a series of low-complexity symbol reconstruction methods for filter-bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) systems, where the key is direct symbol decision. Specifically, by analyzing the distribution characteristics of the demodulated OQAM symbols at the receiver, we firstly propose an interference avoidance based direct symbol decision (IAD) method that employs dual pilot symbols, avoiding the interference term and eliminating the need for guard symbols. Then, we observe that the decision coefficients on each subcarrier can be obtained from a straight line, which is determined by the demodulated OQAM symbols of multiple identical pilot symbols. Based on this, we propose a line fitting based IAD (LF-IAD) method that improves the symbol reconstruction performance by utilizing multiple identical pilot symbols. To minimize the symbol distortion, we further propose a minimum symbol distortion based IAD (MIAD) method and a line fitting based MIAD (LF-MIAD) method. Through complexity analysis, we show that all proposed methods have lower complexities than the traditional interference approximation method (IAM). Simulation results also demonstrate that both the proposed LF-IAD and LF-MIAD methods achieve significant bit error ratio (BER) perfor-mance improvement.

The Internet of Things (IoT) is envisioned to connect everything, spanning from terrestrial to nonterrestrial terminals, where reliable communication is expected to be allowed in both time-invariant and time-variant wireless channels. Since classic orthogonal frequency-division multiplexing (OFDM) modulation, which has been widely used in both the fourth-generation (4G) and the fifth-generation (5G) cellular systems, is sensitive to high Doppler effect, it is challenging to satisfy the ever-growing demands of future IoT. To circumvent this issue, the orthogonal time–frequency space (OTFS) scheme is proposed, which modulates the information bits in both the delay and the Doppler domains, and exhibits beneficial advantages in both static and high-mobility wireless channel scenarios. In this article, we present a comprehensive overview of OTFS for IoT, including the current transceiver design, the potential benefits, the challenge issues, as well as future design guidelines.

雷达通信一体化系统(Integrated Radar and Communication System,IRCS)可提升设备的可用性、可靠性和电磁兼容性,已成为雷达和通信交叉领域的研究热点.正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)具有高信息传输性能,且其模糊函数具有低旁瓣特性,在IRCS中得到广泛关注.在OFDM-IRCS中,组网时同频干扰严重影响雷达探测性能.针对这一问题,从信干比(Signal to Interference Ratio,SIR)分析了 IRCS同频干扰特性,推导了回波信号SIR的表达式.然后,结合OFDM中交织多址(Interleave Division Multiple Access,IDMA)和干扰重构的思想,提出了基于OFDM-IDMA的IRCS同频干扰抑制算法.所提算法通过不同的交织方式区分不同IRCS节点的信号,同时利用基于干扰重构的干扰消除算法实现干扰抑制.仿真结果表明,所提算法有效地抑制了IRCS同频干扰,实现了同频干扰环境下雷达目标探测性能提升.

In this paper, a novel scheme which utilizes cyclic delay combined with peak shrinking and interpolating (PSI), named as CD-PSI, is proposed to reduce the PAPR of multi-intermediate- frequency-over-fiber (Multi-IFoF) signals in mobile fronthaul. The key idea of the proposed scheme is to generate multi-IF OFDM signals through once combination of cyclic delay search so as to reduce the probability of the peak values. Then the PAPR is further reduced by peak shrinking and interpolating. The combination strategy can greatly reduce the sideband information overhead compared to PSI by reducing the recorded peak information. The simulation results demonstrate that the proposed scheme outperforms the previously proposed schemes in terms of both PAPR reduction performance and computational complexity.

In this paper, we propose a symbol encryption method based on the complex-valued symbol multiplication and design the encryption symbol placement for offset quadrature amplitude modulation based filter bank multicarrier (OQAM/FBMC) systems. Specifically, we firstly analyze the encryption and decryption effects of complex-valued symbol multiplication on the original OQAM symbols. Then, by utilizing the intrinsic interference characteristics of prototype filters, a symbol encryption method and the placement design are proposed to simultaneously achieve the encryption of all OQAM symbols and low complexity decryption. Finally, the symbol error rate (SER), average signal transmit power, computational overhead and power spectral density (PSD) are analyzed. Simulation results are consistent with the theoretical analysis and demonstrate that the proposed method outperforms the traditional method based on imaginary-valued encryption symbol insertion in terms of the SERs of both legitimate and illegitimate receivers.

A high speed directly modulated and tunable distributed Bragg reflector laser is proposed based on an equivalent phase shift Bragg grating. By inserting a uniform waveguide in the middle of Bragg grating section, a notch is formed on reflectivity spectrum of the grating, and the photon-photon resonance (PPR) effect could then be introduced to extend modulation bandwidth. An independent electrode is also added for controlling the equivalent phase shift, which plays a key role in the design to introduce the PPR effects, and ensure compatibility with wavelength tuning. Stability, tunability and small signal response of the laser are numerically investigated, 40 GHz direct modulation bandwidth and 7 nm tuning range are obtained, indicating that the laser designed could achieve a large modulation bandwidth within a certain wavelength tuning range.

In this paper, we investigate the two-hop active relaying for dynamic magnetic induction based underwater wireless sensor networks (MI-UWSNs). Specifically, we firstly propose the two-hop active relaying schemes with unidirectional (UD) and tri-directional (TD) active relays, respectively, by considering the angular misalignment in practical underwater MI environments. Then, the statistical properties of the received signal-to-noise ratio (SNR) for the proposed two-hop UD and TD active relaying schemes are rigorously analyzed and the corresponding closed-form expressions of the probability density functions are derived according to the distribution of the angular misalignment. Based on the statistical SNRs, we develop the analytical expressions of the ergodic achievable rate and the average bit-to-error rate for the two-hop UD and TD active relaying schemes employing the amplify-and-forward and decode-and-forward strategies. Extensive simulation results validate the effectiveness of our theoretical analyses and demonstrate that the proposed two-hop TD active relaying scheme performs the best among all comparative schemes.

We apply a Peak Shrinking and Interpolating (PSI) scheme to improve the Peak-to-Average Power Ratio (PAPR) performance in Multiple Intermediate-Frequency-over-Fiber (M-IFoF) based mobile fronthaul. The key idea is to detect the high peaks of the signal and shrink them, and then the shrunk peak values are interpolated into the original signal to reduce the PAPR. We also compare the PSI technique with the previous Tone-Reservation (TR) technique and Phase Pre-Distortion (PPD) technique in terms of PAPR reduction effect and computational complexity. The simulation results indicate that the PSI scheme can reduce the PAPR by more than 4.3 dB at 0.1% CCDF, which outperforms the two previous schemes with lower computational complexity. Furthermore, we find that altering M-IFoF system parameters has little effect on the performance of the PSI technique.

A theoretical model based on the mode expansion of the traveling wave equations is developed to investigate the mode interaction processes behind the photon-photon resonance (PPR) effect in distributed Bragg reflector (DBR) lasers. With dual-mode rate equations, strength of mode interactions is characterized by the cross power and the coupling factors, which arise from the non-orthogonality of the main mode and the PPR mode. Small signal analysis and large-signal dynamics are performed, and results indicate that the cross power is a key contributor to the PPR effect.