This paper investigates the ambiguity function (AF) of the emerging affine frequency division multiplexing (AFDM) waveform for random integrated sensing and communication (ISAC) signaling under a pulse shaping regime. Specifically, we first derive the closed-form expression of the average squared discrete period AF (DPAF) for AFDM waveform without pulse shaping, revealing that the AF depends on the parameterc1and the kurtosis of random communication data, while being independent of the parameterc2. As a step further, we conduct a comprehensive analysis on the DPAFs of various waveforms, including AFDM, orthogonal frequency division multiplexing (OFDM) and orthogonal chirp-division multiplexing (OCDM). Our results indicate that all three waveforms exhibit the same number of regular depressions in the sidelobes of their DPAFs, which incurs performance loss for detecting and estimating weak targets. However, the AFDM waveform can flexibly control the positions of depressions by adjusting the parameterc1, which motivates a novel design approach of the AFDM parameters to mitigate the adverse impact of depressions of the strong target on the weak target. Furthermore, the closed-form expressions of the average squared DPAFs for pulse-shaped AFDM, OFDM and OCDM waveforms are derived, which demonstrates that the pulse shaping filter generates the shaped mainlobe along the delay axis and the rapid roll-off sidelobes along the Doppler axis. Numerical results verify the effectiveness of our theoretical analysis and proposed design methodology for the AFDM waveform.

Affine frequency division multiplexing (AFDM) has garnered significant attention due to its superior performance in high-mobility scenarios, as well as multiple waveform parameters that provide greater degrees of freedom for system design. This paper proposes a novel secure affine frequency division multiplexing (SE-AFDM) system, which enhances physical-layer security by dynamically varying an AFDM pre-chirp parameter across subcarriers and over AFDM symbols. In the SE-AFDM system, the pre-chirp parameter is dynamically generated from a codebook controlled by a long-period pseudo-noise (LPPN) sequence. Instead of applying spreading in the data domain, our parameter-domain spreading approach provides additional security while maintaining reliability and high spectral efficiency. We also propose a synchronization framework to solve the problem of reliably and rapidly synchronizing the dynamic parameter in fast time-varying channels. The theoretical derivations prove that unsynchronized eavesdroppers cannot eliminate the nonlinear impact of the time-varying parameter and further provide useful guidance for codebook design. Simulation results demonstrate the security advantages of the proposed SE-AFDM system in high-mobility scenarios, and the hardware prototype validates the effectiveness of the proposed SE-AFDM system and the proposed synchronization framework.

This paper proposes an anti-interference affine frequency division multiplexing (AFDM) system to ensure reliability and resource efficiency under malicious high-power interference originating from adversarial devices in high-mobility scenarios. Closed-form expressions of interferences in the discrete affine Fourier transform (DAFT) domain are derived by utilizing the stationary phase principle and the Affine Fourier transform convolution theorem, which indicates that interference impacts can be classified into stationary and non-stationary categories. On this basis, we reveal the analytical relationship between packet throughput and the parameters of spread spectrum and error correction coding in our proposed anti-interference system, which enables the design of a parameter optimization algorithm that maximizes packet throughput. For reception, by jointly utilizing the autocorrelation function of spreading sequence and the cyclic-shift property of AFDM input-output relation, we design a linear-complexity correlation-based DAFT domain detector (CDD) capable of achieving full diversity gain, which performs correlation-based equalization to avoid matrix inversion. Numerical results validate the accuracy of the derived closed-form expressions and verify that the proposed anti-interference AFDM system could achieve high packet throughput under interference in high-mobility scenarios.

This paper investigates the sensing potential of affine frequency division multiplexing (AFDM) in high-mobility integrated sensing and communication (ISAC) from the perspective of radar waveforms. We introduce an innovative parameter selection criterion that establishes a precise mathematical equivalence between AFDM subcarriers and Nyquist-sampled frequency-modulated continuous-wave (FMCW). This connection not only provides a clear physical insight into AFDM's sensing mechanism but also enables a direct mapping from the DAFT index to delay-Doppler (DD) parameters of wireless channels. Building on this, we develop a novel input-output model in a DD-parameterized DAFT (DD-DAFT) domain for AFDM, which explicitly reveals the inherent DD coupling effect arising from the chirp-channel interaction. Subsequently, we design two matched-filtering sensing algorithms. The first is performed in the time-frequency domain with low complexity, while the second is operated in the DD-DAFT domain to precisely resolve the DD coupling. Simulations show that our algorithms achieve effective pilot-free sensing and demonstrate a fundamental trade-off between sensing performance, communication overhead, and computational complexity. The proposed AFDM outperforms classical AFDM and other variants in most scenarios.

This paper introduces a secure affine frequency division multiplexing (SE-AFDM) for wireless communication systems to enhance communication security. Besides configuring the parameter$c_{1}$to obtain communication reliability under doubly selective channels, we also utilize the time-varying parameter$c_{2}$to improve the security of the communications system. The derived input-output relation shows that the legitimate receiver can eliminate the nonlinear impact introduced by the time-varying$c_{2}$without losing the bit error rate (BER) performance. Moreover, it is theoretically proved that the eavesdropper cannot separate the time-varying$c_{2}$and random information symbols, such that the BER performance of the eavesdropper is severely deteriorated. Meanwhile, the analysis of the effective signal-to-interference-plus-noise ratio (SINR) of the eavesdropper illustrates that the SINR decreases as the value range of$c_{2}$expands. Numerical results verify that the proposed SE-AFDM waveform has significant security while maintaining good BER performance in high-mobility scenarios.

This paper proposes an integrated sensing and communications (ISAC) system based on affine frequency division multiplexing (AFDM) waveform. To this end, a metric set is designed according to not only the maximum tolerable delay/Doppler, but also the weighted spectral efficiency as well as the outage/error probability of sensing and communications. This enables the analytical investigation of the performance trade-offs of AFDM-ISAC system using the derived analytical relation among metrics and AFDM waveform parameters. Moreover, by revealing that delay and the integral/fractional parts of normalized Doppler can be decoupled in the affine Fourier transform-Doppler domain, an efficient estimation method is proposed for our AFDM-ISAC system, whose unambiguous Doppler can break through the limitation of subcarrier spacing. Theoretical analyses and numerical results verify that our proposed AFDM-ISAC system may significantly enlarge unambiguous delay/Doppler while possessing good spectral efficiency and peak-to-sidelobe level ratio in high-mobility scenarios.

One-shot neural architecture search (NAS) has achieved impressive results in the field of synthetic aperture radar (SAR) ship detection. However, it is a challenge to balance resource consumption and search speed. To address this issue, we propose a zero-shot NAS method for searching the backbone of SAR ship detection model, named as ZeroSARNas, which is implemented via a multi-characterization proxy and an integer linear programming (ILP) search algorithm. Specifically, we first design the multi-characterization proxy for network capacity prediction, which takes advantage of information entropy and local intrinsic dimensionality (LID) of feature maps, named as ELID proxy, to obtain a more comprehensive understanding of each candidate module in the search space. We then formulate the NAS problem as a ‘0–1’ ILP problem which maximizes the ELID value under the different constraints such as parameters to quickly identify the optimal network. The experimental results show that the detection accuracy of the networks found by ZeroSARNas on the SSDD, HRSID, and LS-SSDD-v1.0 datasets can reach 98.59%, 91.30%, and 75.11% in mean average precision (mAP) with only 1.23 M, 1.75 M, and 1.29 M parameters, respectively. The proposed method reduces the search time from several GPU days or hours to 10.0 seconds, achieving competitive search efficiency.

This paper shows that the error probability of a querying policy for noisy 20 questions is upper bounded by the minimum Hamming distance of its querying matrix. Following this distance principle, sparse querying matrices with the row-column constraint are constructed for the scenarios, where only limited areas can be detected at each querying round. It demonstrates that the row-column constraint promises a large minimum distance to ensure low error probability of queries. Moreover, the proposed sparse matrices with random block coding provide unequal error-protection capability to further improve the querying accuracy under the scenarios of detecting half of the areas. Simulation results verify that the quantized mean squared errors of our proposed policies outperform those of the existing policies under the above scenarios.