arXiv subjects

Zhiqiang Xiao

Publications and source records attributed to Zhiqiang Xiao.

At least 19 recordsLinked to original sources

arXiv2026

Channel Knowledge Map Enabled Low-Complexity Dynamic Radio Environment Reconstruction

Accurate and timely radio environment reconstruction is important but challenging under particularly dynamic transmitter configurations. The conventional methods such as compressed sensing (CS), Kriging method or U-Net typically require environment measurements and reconstruction overhead for radio environment updating as the transmitter locations or radiation patterns change. In this paper, we propose a novel channel knowledge map (CKM)-enabled dynamic radio environment reconstruction method for efficient radio map updating. Specifically, the recently proposed CKM can store reusable path-level propagation knowledge that is decoupled from the transmitter-side radiation characteristics. We can leverage CKM for lightweight forward radio map generation as the transmitter locations and radiation patterns are known, without requiring new target-map measurements. Simulation results show that the proposed method outperforms CS, Kriging, and U-Net in reconstruction accuracy and exhibits strong robustness performance under dynamic transmitter configurations, which demonstrates the potential of the proposed method for flexible and efficient radio environment reconstruction in dynamic wireless networks.

eess.SP↗

arXiv2026

Low-Altitude ISAC With Spherical Directly-Connected Antenna Array: Performance Analysis and Beamforming Optimization

The safety development requirements of low-altitude economy (LAE) renders the robust low-altitude airspace monitoring critical important than ever before. Integrated sensing and communication (ISAC) as one of the key development trends of 6G provides potential solutions for the LAE. However, conventional antenna arrays suffer from limited three-dimensional (3D) sensing coverage and degraded angular resolution at high elevation angles. To address these challenges, this paper investigates low-altitude ISAC systems enabled by the recently proposed spherical directly-connected antenna array (DCAA). By carefully deploying multiple simple uniform planar arrays (sUPAs) over a spherical surface, without relying on any phase shifter, spherical DCAA enjoys advantages of full 3D coverage, superior and uniform angular resolution, enhanced energy-focusing and low hardware cost. In this paper, we first characterizes the sensing performance of the spherical DCAA, in terms of the sensing signal-to-noise ratio (SNR), area average probability of detection, and Cramér-Rao lower bounds (CRLBs) for both elevation and azimuth angle estimation. Then, a low-altitude ISAC optimization problem is formulated to maximize the worst-case sensing SNR over a prescribed aerial region while satisfying the communication quality-of-service requirements of ground users. To effective solve this mixed-integer non-convex problem, we develop a novel greed-based joint array selection and beamforming optimization framework. Simulation results demonstrate that spherical DCAA significantly outperforms conventional UPA in terms of sensing coverage, angle estimation accuracy, and communication-sensing SNR tradeoff, highlighting its potential for future low-altitude ISAC systems.

eess.SP↗

arXiv2026

Ray Antenna Array Enhanced Low-Altitude ISAC: Performance Analysis and Beamforming Design

The low-altitude economy (LAE) heavily relies on aerial vehicles, yet these platforms remain vulnerable to environmental and security risks, necessitating robust airspace monitoring. Integrated sensing and communication (ISAC) as one of the key technologies of 6G provides potential solutions for safe LAE. However, conventional antenna arrays face limitations in cost, scalability, and coverage, especially directly above the base station, due to hardware complexity and degraded angular resolution. By exploiting the recently proposed ray antenna array (RAA), this paper considers a RAA-enhanced low-altitude ISAC system. RAA architecture employs multiple ray-arranged arrays directly connected without phase shifters, significantly reducing hardware costs while supporting flexible beamforming via dynamic ray selection. Moreover, RAA can provide uniform angular resolution and eliminates coverage holes, making it particularly suitable for low-altitude ISAC. In this paper, we formulate an optimization problem for joint ray selection and beamforming to enhance sensing coverage under communication constraints. An efficient alternating optimization algorithm is proposed to solve this problem. Analytical and simulation results demonstrate that RAA achieves higher sensing signal-to-noise ratio compared to traditional arrays, offering a cost-effective and high-performance solution for achieving low-altitude ISAC.

cs.IT↗

arXiv2026

OpenACM: An Open-Source SRAM-Based Approximate CiM Compiler

The rise of data-intensive AI workloads has exacerbated the ``memory wall'' bottleneck. Digital Compute-in-Memory (DCiM) using SRAM offers a scalable solution, but its vast design space makes manual design impractical, creating a need for automated compilers. A key opportunity lies in approximate computing, which leverages the error tolerance of AI applications for significant energy savings. However, existing DCiM compilers focus on exact arithmetic, failing to exploit this optimization. This paper introduces OpenACM, the first open-source, accuracy-aware compiler for SRAM-based approximate DCiM architectures. OpenACM bridges the gap between application error tolerance and hardware automation. Its key contribution is an integrated library of accuracy-configurable multipliers (exact, tunable approximate, and logarithmic), enabling designers to make fine-grained accuracy-energy trade-offs. The compiler automates the generation of the DCiM architecture, integrating a transistor-level customizable SRAM macro with variation-aware characterization into a complete, open-source physical design flow based on OpenROAD and the FreePDK45 library. This ensures full reproducibility and accessibility, removing dependencies on proprietary tools. Experimental results on representative convolutional neural networks (CNNs) demonstrate that OpenACM achieves energy savings of up to 64\% with negligible loss in application accuracy. The framework is available on \href{https://github.com/ShenShan123/OpenACM}{OpenACM:URL}

cs.AR↗

arXiv2025

A Deep Transfer Learning-Based Low-overhead Beam Prediction in Vehicle Communications

Existing transfer learning-based beam prediction approaches primarily rely on simple fine-tuning. When there is a significant difference in data distribution between the target domain and the source domain, simple fine-tuning limits the model's performance in the target domain. To tackle this problem, we propose a transfer learning-based beam prediction method that combines fine-tuning with domain adaptation. We integrate a domain classifier into fine-tuning the pre-trained model. The model extracts domain-invariant features in adversarial training with domain classifier, which can enhance model performance in the target domain. Simulation results demonstrate that the proposed transfer learning-based beam prediction method achieves better achievable rate performance than the pure fine-tuning method in the target domain, and close to those when the training is done from scratch on the target domain.

cs.IT↗

arXiv2024

Achieving Full-Bandwidth Sensing Performance with Partial Bandwidth Allocation for ISAC

This letter studies an uplink integrated sensing and communication (ISAC) system using discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-s-OFDM) transmission. We try to answer the following fundamental question: With only a fractional bandwidth allocated to the user with sensing task, can the same delay resolution and unambiguous range be achieved as if all bandwidth were allocated to it? We affirmatively answer the question by proposing a novel two-stage delay estimation (TSDE) method that exploits the following facts: without increasing the allocated bandwidth, higher delay resolution can be achieved via distributed subcarrier allocation compared to its collocated counterpart, while there is a trade-off between delay resolution and unambiguous range by varying the decimation factor of subcarriers. Therefore, the key idea of the proposed TSDE method is to first perform coarse delay estimation with collocated subcarriers to achieve a large unambiguous range, and then use distributed subcarriers with optimized decimation factor to enhance delay resolution while avoiding delay ambiguity. Our analysis shows that the proposed TSDE method can achieve the full-bandwidth delay resolution and unambiguous range, by using only at most half of the full bandwidth, provided that the channel delay spread is less than half of the unambiguous range. Numerical results show the superiority of the proposed method over the conventional method with collocated subcarriers.

cs.IT↗

arXiv2024

Single-BS Simultaneous Environment Sensing and UE Localization without LoS Path by Exploiting Near-Field Scatterers

As the mobile communication network evolves over the past few decades, localizing user equipment (UE) has become an important network service. While localization in line-of-sight (LoS) scenarios has reached a level of maturity, it is known that in far-field scenarios without a LoS path nor any prior information about the scatterers, accurately localizing the UE is impossible. In this letter, we show that this becomes possible if there are scatterers in the near-field region of the base station (BS) antenna arrays. Specifically, by exploiting the additional distance sensing capability of extremely large-scale antenna arrays (XL-arrays) provided by near-field effects, we propose a novel method that simultaneously performs environment sensing and non-line-of-sight (NLoS) UE localization using one single BS. In the proposed method, the BS leverages the near-field characteristics of XL-arrays to directly estimate the locations of the near-field scatterers with array signal processing, which then serves as virtual anchors for UE localization. Then, the propagation delay for each path is estimated and the position of the UE is obtained based on the positions of scatterers and the path delays. Simulation results demonstrate that the proposed method achieves superior accuracy and robustness with similar complexity compared with benchmark methods.

eess.SP↗

arXiv2024

Movable Antenna for Wireless Communications:Prototyping and Experimental Results

Movable antenna (MA), which can flexibly change the position of antenna in three-dimensional (3D) continuous space, is an emerging technology for achieving full spatial performance gains. In this paper, a prototype of MA communication system with ultra-accurate movement control is presented to verify the performance gain of MA in practical environments. The prototype utilizes the feedback control to ensure that each power measurement is performed after the MA moves to a designated position. The system operates at 3.5 GHz or 27.5 GHz, where the MA moves along a one-dimensional horizontal line with a step size of 0.01λ and in a two-dimensional square region with a step size of 0.05λ, respectively, with λ denoting the signal wavelength. The scenario with mixed line-of-sight (LoS) and non-LoS (NLoS) links is considered. Extensive experimental results are obtained with the designed prototype and compared with the simulation results, which validate the great potential of MA technology in improving wireless communication performance. For example, the maximum variation of measured power reaches over 40 dB and 23 dB at 3.5 GHz and 27.5 GHz, respectively, thanks to the flexible antenna movement. In addition, experimental results indicate that the power gain of MA system relies on the estimated path state information (PSI), including the number of paths, their delays, elevation and azimuth angles of arrival (AoAs), as well as the power ratio of each path.

cs.IT↗

arXiv2024

Successors of topologies of connected locally compact groups

Let $G$ be a group and $σ, τ$ be topological group topologies on $G$. We say that $σ$ is a successor of $τ$ if $σ$ is strictly finer than $τ$ and there is not a group topology properly between them. In this note, we explore the existence of successor topologies in topological groups, particularly focusing on non-abelian connected locally compact groups. Our main contributions are twofold: for a connected locally compact group $(G, τ)$, we show that (1) if $(G, τ)$ is compact, then $τ$ has a precompact successor if and only if there exists a discontinuous homomorphism from $G$ into a simple connected compact group with dense image, and (2) if $G$ is solvable, then $τ$ has no successors. Our work relies on the previous characterization of locally compact group topologies on abelian groups processing successors.

math.GR↗

arXiv2024

Orthogonal Time Frequency Space with Delay-Doppler Alignment Modulation

Delay-Doppler alignment modulation (DDAM) is a novel technique to mitigate time-frequency doubly selective channels by leveraging the high spatial resolution offered by large antenna arrays and multi-path sparsity of millimeter wave (mmWave) and TeraHertz (THz) channels. By introducing per-path delay and Doppler compensations, followed by path-based beamforming, it is possible to reshape the channel features with significantly reduced channel delay and Doppler spreads. This offers new degrees-of-freedom for waveform designs such as orthogonal time frequency space (OTFS), since the reshaped channel can significantly relax the constraints on OTFS parameter selection and reduce the complexity of signal detection at the receiver. Therefore, in this paper, by combing DDAM with OTFS, we propose a novel technique termed DDAM-OTFS. Two implementation schemes are introduced for DDAM-OTFS, namely path-based alignment and bin-based alignment. Simulation results are provided to demonstrate the superior performance of the proposed DDAM-OTFS in terms of spectral efficiency (SE) and peak-to-average power ratio (PAPR) compared to the conventional OTFS.

eess.SP↗

arXiv2024

Rethinking Waveform for 6G: Harnessing Delay-Doppler Alignment Modulation

Waveform design has served as a cornerstone for each generation of mobile communication systems. The future sixth-generation (6G) mobile communication networks are expected to employ larger-scale antenna arrays and exploit higher-frequency bands for further boosting data transmission rate and providing ubiquitous wireless sensing. This brings new opportunities and challenges for 6G waveform design. In this article, by leveraging the super spatial resolution of large antenna arrays and the multi-path spatial sparsity of highfrequency wireless channels, we introduce a new approach for waveform design based on the recently proposed delay-Doppler alignment modulation (DDAM). In particular, DDAM makes a paradigm shift of waveform design from the conventional manner of tolerating channel delay and Doppler spreads to actively manipulating them. First, we review the fundamental constraints and performance limitations of orthogonal frequency division multiplexing (OFDM) and introduce new opportunities for 6G waveform design. Next, the motivations and basic principles of DDAM are presented, followed by its various extensions to different wireless system setups. Finally, the main design considerations for DDAM are discussed and the new opportunities for future research are highlighted.

eess.SP↗

arXiv2024

Fractional Delay Alignment Modulation for Spatially Sparse Wireless Communications

Delay alignment modulation (DAM) is a novel transmission technique for wireless systems with high spatial resolution by leveraging delay compensation and path-based beamforming, to mitigate the inter-symbol interference (ISI) without resorting to complex channel equalization or multi-carrier transmission. However, most existing studies on DAM consider a simplified scenario by assuming that the channel multi-path delays are integer multiples of the signal sampling interval. This paper investigates DAM for the more general and practical scenarios with fractional multi-path delays. We first analyze the impact of fractional multi-path delays on the existing DAM design, termed integer DAM (iDAM), which can only achieve delay compensations that are integer multiples of the sampling interval. It is revealed that the existence of fractional multi-path delays renders iDAM no longer possible to achieve perfect delay alignment. To address this issue, we propose a more generic DAM design called fractional DAM (fDAM), which achieves fractional delay pre-compensation via upsampling and fractional delay filtering. By leveraging the Farrow filter structure, the proposed approach can eliminate ISI without real-time computation of filter coefficients, as typically required in traditional channel equalization techniques. Simulation results demonstrate that the proposed fDAM outperforms the existing iDAM and orthogonal frequency division multiplexing (OFDM) in terms of symbol error rate (SER) and spectral efficiency, while maintaining a comparable peak-to-average power ratio (PAPR) as iDAM, which is considerably lower than OFDM.

eess.SP↗

arXiv2023

Integrated Sensing and Channel Estimation by Exploiting Dual Timescales for Delay-Doppler Alignment Modulation

For integrated sensing and communication (ISAC) systems, the channel information essential for communication and sensing tasks fluctuates across different timescales. Specifically, wireless sensing primarily focuses on acquiring path state information (PSI) (e.g., delay, angle, and Doppler) of individual multi-path components to sense the environment, which usually evolves much more slowly than the composite channel state information (CSI) required for communications. Typically, the CSI is approximately unchanged during the channel coherence time, which characterizes the statistical properties of wireless communication channels. However, this concept is less appropriate for describing that for wireless sensing. To this end, in this paper, we introduce a new timescale to study the variation of the PSI from a channel geometric perspective, termed path invariant time, during which the PSI largely remains constant. Our analysis indicates that the path invariant time considerably exceeds the channel coherence time. Thus, capitalizing on these dual timescales of the wireless channel, in this paper, we propose a novel ISAC framework exploiting the recently proposed delay-Doppler alignment modulation (DDAM) technique. Different from most existing studies on DDAM that assume the availability of perfect PSI, in this work, we propose a novel algorithm, termed as adaptive simultaneously orthogonal matching pursuit with support refinement (ASOMP-SR), for joint environment sensing and PSI estimation. We also analyze the performance of DDAM with imperfectly sensed PSI.Simulation results unveil that the proposed DDAM-based ISAC can achieve superior spectral efficiency and a reduced peak-to-average power ratio (PAPR) compared to standard orthogonal frequency division multiplexing (OFDM).

cs.IT↗

arXiv2023

Cramér-Rao Bounds for Near-Field Sensing with Extremely Large-Scale MIMO

Mobile communication networks were designed to mainly support ubiquitous wireless communications, yet they are also expected to achieve radio sensing capabilities in the near future. However, most prior studies on radio sensing usually rely on far-field assumption with uniform plane wave (UPW) models. With the ever-increasing antenna size, together with the growing demands to sense nearby targets, the conventional far-field UPW assumption may become invalid. Therefore, this paper studies near-field radio sensing with extremely large-scale (XL) antenna arrays, where the more general uniform spheric wave (USW) sensing model is considered. Closed-form expressions of the Cramér-Rao Bounds (CRBs) for both angle and range estimations are derived for near-field XL-MIMO radar mode and XL-phased array radar mode, respectively. Our results reveal that different from the conventional UPW model where the CRB for angle decreases unboundedly as the number of antennas increases, for XL-MIMO radar-based near-field sensing, the CRB decreases with diminishing return and approaches to a certain limit as the number of antennas increases. Besides, different from the far-field model where the CRB for range is infinity since it has no range estimation capability, that for the near-field case is finite. Furthermore, it is revealed that the commonly used spherical wave model based on second-order Taylor approximation is insufficient for near-field CRB analysis. Extensive simulation results are provided to validate our derived CRBs.

cs.IT↗

arXiv2022

Integrated Sensing and Communication with Delay Alignment Modulation: Performance Analysis and Beamforming Optimization

Delay alignment modulation (DAM) has been recently proposed to enable manipulable channel delay spread for efficient single- or multi-carrier communications. In particular, with perfect delay alignment, inter-symbol interference (ISI) can be eliminated even with single-carrier (SC) transmission, without relying on sophisticated channel equalization. The key ideas of DAM are delay pre-compensation and path-based beamforming, so that all multi-path signal components may arrive at the receiver simultaneously and be superimposed constructively, rather than causing the detrimental ISI. Compared to the classic orthogonal frequency division multiplexing (OFDM) transmission, DAM-enabled SC communication has several appealing advantages, including low peak-to-average-power ratio (PAPR) and high tolerance for Doppler frequency shift, which renders DAM also appealing for radar sensing. Therefore, in this paper, DAM is investigated for integrated sensing and communication (ISAC) systems. We first study the output signal-to-noise ratios (SNRs) for ISI-free SC communication and radar sensing, and then derive the closed-form expressions for DAM-based sensing in terms of the ambiguity function (AF) and integrated sidelobe ratio (ISR). Furthermore, we study the beamforming design problem for DAM-based ISAC to maximize the communication SNR while guaranteeing the sensing performance in terms of the sensing SNR and ISR. Finally, we provide performance comparison between DAM and OFDM for ISAC, and it is revealed that DAM signal may achieve better communication and sensing performance, thanks to its low PAPR, reduced guard interval overhead, as well as higher tolerance for Doppler frequency shift. Simulation results are provided to show the great potential of DAM for ISAC.

eess.SP↗

arXiv2022

Integrated Sensing and Communication with Delay Alignment Modulation

Delay alignment modulation (DAM) has been recently proposed to enable inter-symbol interference (ISI)-free single-carrier (SC) communication without relying on sophisticated channel equalization. The key idea of DAM is to pre-introduce deliberate symbol delays at the transmitter side, so that all multi-path signal components may arrive at the receiver simultaneously and be superimposed constructively, rather than causing the detrimental ISI. Compared to the classic orthogonal frequency division multiplexing (OFDM) transmission, DAM has several appealing advantages, including low peak-to-average-power ratio (PAPR) and high tolerance for Doppler frequency shift, which makes DAM also appealing for radar sensing. Therefore, in this paper, DAM is investigated for the emerging integrated sensing and communication (ISAC) setup. We first derive the output signal-to-noise ratios (SNRs) for ISI-free communication and radar sensing, respectively, and then propose an efficient beamforming design for DAM-ISAC to maximize the communication SNR while guaranteeing the sensing performance. The comparison analysis of DAM versus OFDM for ISAC is developed, and it is revealed that DAM enables higher sensing SNR and larger Doppler frequency estimation. Simulation results are provided to show the great potential of DAM for ISAC

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arXiv2022

Beamforming Towards Seamless Sensing Coverage for Cellular Integrated Sensing and Communication

The sixth generation (6G) mobile communication networks are expected to offer a new paradigm of cellular integrated sensing and communication (ISAC). However, due to the intrinsic difference between sensing and communication in terms of coverage requirement, current cellular networks that are deliberately planned mainly for communication coverage are difficult to achieve seamless sensing coverage. To address this issue, this paper studies the beamforming optimization towards seamless sensing coverage for a basic bi-static ISAC system, while ensuring that the communication requirements of multiple users equipment (UEs) are satisfied. Towards this end, an optimization problem is formulated to maximize the worst-case sensing signal-to-noise ratio (SNR) in a prescribed coverage region, subject to the signal-to-interference-plus-noise ratio (SINR) requirement for each UE. To gain some insights, we first investigate the special case with one single UE and one single sensing point, for which a closed-from expression of the optimal beamforming is obtained. For the general case with multiple communication UEs and contiguous regional sensing coverage, an efficient algorithm based on successive convex approximation (SCA) is proposed to solve the non-convex beamforming optimization problem. Numerical results demonstrate that the proposed design is able to achieve seamless sensing coverage in the prescribed region, while guaranteeing the communication requirements of the UEs.

cs.IT↗

arXiv2021

Waveform Design and Performance Analysis for Full-Duplex Integrated Sensing and Communication

Integrated sensing and communication (ISAC) is a promising technology to fully utilize the precious spectrum and hardware in wireless systems, which has attracted significant attentions recently. This paper studies ISAC for the important and challenging monostatic setup, where one single ISAC node wishes to simultaneously sense a radar target while communicating with a communication receiver. Different from most existing schemes that rely on either radar-centric half-duplex (HD) pulsed transmission with information embedding that suffers from extremely low communication rate, or communication-centric waveform that suffers from degraded sensing performance, we propose a novel full-duplex (FD) ISAC scheme that utilizes the waiting time of conventional pulsed radars to transmit dedicated communication signals. Compared to radar-centric pulsed waveform with information embedding, the proposed design can drastically increase the communication rate, and also mitigate the sensing eclipsing and near-target blind range issues, as long as the self-interference (SI) is effectively suppressed. On the other hand, compared to communication-centric ISAC waveform, the proposed design has better auto-correlation property as it preserves the classic radar waveform for sensing. Performance analysis is developed by taking into account the residual SI, in terms of the probability of detection and ambiguity function for sensing, as well as the spectrum efficiency for communication. Numerical results are provided to show the significant performance gain of our proposed design over benchmark schemes.

eess.SP↗