Zero-Knowledge Proofs (ZKPs), especially zk-SNARKs, rely heavily on Multi-Scalar Multiplication (MSM), a compute-intensive elliptic curve operation. While prior work targets curves with optimized operations like BLS12-377, MSM on general-purpose curves such as BLS12-381 remains challenging due to imbalanced resource usage, performance gaps between curve operations, and low utilization of point addition. This paper proposes FlexMSM to support scalable MSM cores on a single FPGA for BLS12-381 curve, delivering significant gains over existing works for input sizes from 218 to 226 .

Driven by the demand for high transmission efficiency in 6G networks, semantic communication has attracted significant interest recently. While most existing works focus on optimizing semantic communication system design to enhance end-to-end transmission performance, they often overlook the integration of quality of service (QoS) requirements. To address this gap, we employ the Alpha-Beta-Gamma (ABG) formula to empirically approximate the relationship between end-to-end transmission quality and signal-to-noise ratio (SNR). Based on this model, we first design an optimal beamforming scheme that minimizes transmission power while ensuring real-time QoS guarantees. Furthermore, to account for inevitable channel state information (CSI) estimation errors in practical scenarios, we propose robust beamforming design schemes under QoS constraints for both bounded and unbounded CSI estimation errors. These optimization problems are efficiently solved using semidefinite relaxation (SDR),S-lemma, and Bernstein-type inequalities. Finally, experimental results demonstrate that our proposed optimal beamforming design scheme outperforms conventional beamforming methods, while the robust beamforming schemes achieve superior performance in handling CSI estimation errors compared to existing computational approaches.

Global Navigation Satellite System (GNSS) functionality is highly vulnerable to jamming, which disrupts signals. Existing datasets and models for jamming classification are inefficient for low-power GNSS jamming. Additionally, current machine and deep learning models struggle to balance accuracy with efficiency. To address this, we develop the Multi-Featured GNSS Jamming Dataset (MFGJD), which includes 16 distinct jamming types along with a clean GNSS signal. Building on MFGJD, we propose the Multi-Scale Convolutional Attention Model (MSCAM), designed to operate in the precorrelation phase using spectrograms as input. MSCAM integrates channel, spatial, and temporal features, enabling accurate and robust jamming classification. Experimental results show that MSCAM outperforms current models, achieving 96.95% accuracy with 0.09 million parameters and 0.30 milliseconds inference time per sample, offering high efficiency and robustness.

Modular Inversion (MI) is one of the fundamental arithmetic operations in the finite field, which plays an essential role in various cryptographic applications and requires high performance and security. Unfortunately, the simple MI algorithm is vulnerable to side-channel attacks, such as the timing attack, which can compromise the cryptographic system by analyzing the time taken to execute cryptographic algorithms. Attackers may recover the initial data since the time can differ based on the input. Besides, the low complexity and low resource consumption of hardware implementations in MI are also challenging. In this article, we propose two novel modular inversion algorithms, named Constant-Time Integer Modular Inversion (CT-IMI) and Constant-Time Complementary Montgomery Modular Inversion (CT-CMMI). They both consist of constant iteration rounds to resist the timing attack. CT-IMI processes the data in the integer field, which is designed for common scenarios. CT-CMMI is suitable for the cross-domain case, which can directly use data in the Montgomery domain and avoid the conversion steps for some specific applications, e.g., scalar multiplication in Elliptic Curve Cryptography (ECC). In software simulations, we measure the average clock cycles for a single inversion and illustrate the relationship between various bit lengths and the latency. The significant differences between constant and non-constant algorithms demonstrate the vulnerability of modular inversion to timing attacks. In addition, we design two efficient hardware architectures on FPGA. Experimental results show that our CT-IMI can finish a single inversion in 2.56 \(\mu\) s with 4.2k LUTs, 1.8k FFs, and our CT-CMMI requires 2.45 \(\mu\) s with 2.7k LUTs, 1.6k FFs. The product of area and latency of our CT-IMI and CT-CMMI can reach 10.50 and 6.62, respectively, which shows optimal performance compared with all the results in the existing literature.

Authenticated Encryption with Associated-Data (AEAD) can ensure both confidentiality and integrity of information in encrypted communication. Distinctive variants are customized from AEAD to satisfy various requirements. In this paper, we take a 128-bit lightweight AEAD stream cipher Fountain as an example. We provide a general cryptographic solution with three Fountain variants. These three variants are for encryption, message authentication code (MAC) generation, and authenticated encryption with associated data, respectively. Besides, we propose area-saved and throughput-improved strategies for the FPGA implementation of Fountain. The conventional paralleled hardware implementation leads to much resource-consuming with higher parallel width. We propose a hybrid architecture with parallel and serial update modes simultaneously. We also analyze the trade-off between area occupation and authentication latency for those two architectures. According to our discussion, hybrid architectures can perform efficiently with higher throughput than most ciphers, including Grain-128 x32. Our Fountain keystream generator occupies 46 slices on Spartan-3 FPGAs, smaller than most ciphers with the same security level, and even smaller than the 80-bit security level cipher Trivium. In summary, the customized Fountain with optimized implementations on FPGA is suitable for various applications in the field of IoT.

Abstract The challenge of ensuring reliability for high‐efficiency technology, multiple‐input‐multiple‐output orthogonal‐frequency‐division‐multiplexing (MIMO‐OFDM), in wireless frequency‐selective fading environments persists. In this article, the concept of spreading a symbol's energy is proposed as a viable solution to enhance transmission reliability for MIMO‐OFDM systems. And an energy‐spreading‐transform (EST)‐based MIMO‐OFDM transceiver is developed. Following the Inverse Fast Fourier Transform (IFFT) performed by the conventional MIMO‐OFDM transmitter, an orthogonal transformation called the EST is introduced. This transform spreads the energy of a symbol across the entire frequency domain and all time slots. The EST is coupled with the improved iterative detection algorithm named EST‐partial decision (PD)‐iterative‐interference‐cancellation (EST‐PD‐IIC) to maximize and leverage the potential diversity gain. Numerical simulation results demonstrate that the proposed scheme approaches the performance bound when signal‐to‐noise ratio (SNR) is about 21dB for 16‐ary quadrature amplitude modulation (16‐QAM). Complexity analysis illustrates that the computational complexity of the evolved EST‐PD‐IIC algorithm is lower than that of the famous vertically Bell laboratory layered space‐time detector (V‐BLAST) when the antenna array size is greater than . In summary, the proposed scheme is practical for providing high‐quality communication in multi‐path fading environments and can even enable a reliable communication without channel encoding when Eb/N0 exceeds a threshold in 5G‐Advanced.

Fibonacci and Galois are two different kinds of configurations in stream ciphers. Although many transformations between two configurations have been proposed, there is no sufficient analysis of their FPGA performance. Espresso stream cipher provides an ideal sample to explore such a problem. The 128-bit secret key Espresso is designed in Galois configuration, and there is a Fibonacci-configured Espresso variant proved with the equivalent security level. To fully leverage the efficiency of two configurations, we explore the hardware optimization approaches toward area and throughput, respectively. In short, the FPGA-implemented Fibonacci cipher is more suitable for extremely resource-constrained or high-throughput applications, while the Galois cipher compromises both area and speed. To the best of our knowledge, this is the first work to systematically compare the FPGA performance of cipher configurations under relatively fair cryptographic security. We hope this work can serve as a reference for the cryptography hardware architecture research community.

Fruit-80, which emerged as an ultra-lightweight stream cipher with 80-bit secret key, is oriented toward resource-constrained devices in the Internet of Things. In this article, we propose area and speed optimization architectures of Fruit-80 on FPGAs. Our implementations include both serial and parallel structure and optimize area, power, speed, and throughput, respectively. The area optimization architecture aims to achieve the most suitable ratio of look-up-tables and flip-flops to fully utilize the reconfigurable unit. It also reuses NFSR and LFSR feedback functions to save resources for high throughput. The speed optimization architecture adopts a hybrid approach for parallelization and reduces the latency of long data paths by pre-generating primary feedback and inserting flip-flops. Besides, we recommend using the round key function to optimize serial or parallel implementations for Fruit-80 and using indexing and shifting methods for different throughput. In conclusion, our results show that the area optimization architecture occupies up to 35 slices on Xilinx Spartan-3 FPGA and 18 slices on Xilinx 7 series FPGA, smaller than that of Grain and other common stream ciphers. The optimal throughput/area ratio of the speed optimization architecture is 7.74 Mbps/slice, better than that of Grain v1, which is 5.98 Mbps/slice. The serial implementation of Fruit-80 with round key function occupies only 75 slices on Spartan-3 FPGA. To the best of our knowledge, the result sets a new record of the minimum area in lightweight cipher implementation on FPGA.

Fruit-80, an ultra-lightweight stream cipher with 80-bit secret key, is oriented toward resource constrained devices in the Internet of Things. In this paper, we propose area and speed optimization architectures of Fruit-80 on FPGAs. The area optimization architecture reuses NFSR&LFSR feedback functions and achieves the most suitable ratio of look-up-tables and flip-flops. The speed optimization architecture adopts a hybrid approach for parallelization and reduces the latency of long data paths by pre-generating primary feedback and inserting flip-flops. In conclusion, the optimal throughput-to-area ratio of the speed optimization architecture is better than that of Grain v1. The area optimization architecture occupies only 35 slices on Xilinx Spartan-3 FPGA, smaller than that of Grain and other common stream ciphers. To the best of our knowledge, this result sets a new record of the minimum area in lightweight cipher implementations on FPGA.

Abstract Multi‐source cooperative positioning systems relying on federated filtering have become attractive development directions of navigation strategy in real‐time localization and tracking under challenging urban environment. However, local Kalman filters of traditional federated filtering may result in divergence when the system model or the measurements is inaccurate, and the fixed information distribution coefficient in federated filter cannot adaptively reflect the performance of each local filter. To improve the precision and robustness of the integrated navigation system, a novel adaptive federated strong tracking Kalman filter with dynamic fading factor mechanism for multi‐sensor information fusion is proposed. Through iterative computation of the fading factor and updating the adaptive weight coefficients, strong tracking filter becomes robust to the uncertainty of system model. Meanwhile, an effective adaptive information distribution estimation algorithm based on the predicted residuals is constructed to balance the contributions of the kinematic model information and measurements on the state estimates. To ensure the stability of filtering, a simplified fusion strategy is established to solve the singular problem of the global covariance matrix of estimation error. Theoretical analysis and simulation results demonstrate the validity of the proposed approach in improving the accuracy and robustness of the integrated navigation and positioning systems. The proposed integrated multi‐modal cooperative navigation and positioning algorithm will be of great significance to the implementation of real‐time mobile target localization and tracking in harsh environment or dead zone.

Abstract This paper focuses on high efficiency secret key generation mechanism of physical‐layer communication over fading channels in ubiquitous wireless networks. The secret key rate via traditional physical‐layer approach could be limited when the wireless propagation channels connecting two sensors change slowly. To generate a high‐rate secret key and improve the communication efficiency over quasi‐static block fading channels, a novel multi‐randomness device‐to‐device secret key generation strategy and a cooperative communication mechanism aided by relay nodes are proposed. In the proposed schemes, the legitimate members to send random signals rotationally in every coherent time are set; thus, two legitimate ubiquitous wireless network members, Alice and Bob, can obtain the potential correlated information by exploiting the randomness and the reciprocity of the wireless propagation channels. Considering the reciprocity of wireless channels is variable while the forward channel gain and backward channel gain are correlated in coherent time, a modified secret key generation scheme is proposed via layered coding with theoretical secret key rates derived. The simulation results show that the proposed scheme outperforms traditional approaches with favourable application prospects in ubiquitous wireless communications networks and internet of things.

The integration of the massive multiple-input multiple-output (MIMO) and millimeter-wave (mmWave) communication can increase the throughput of 5G networks. As an attractive technique in the MIMO systems, hybrid beamforming (HBF) can improve the 5G capacity by employing spatial domain resources. However, with the increase of the number of antennas, the traditional beamforming algorithms fail to efficiently keep a balance between the hardware complexity and beamforming gains. In this paper, with the aid of bidirectional location information, a bidirectional positioning assisted HBF (BPA-HBF) scheme is proposed. Specifically, we first propose a new scheme to decouple the optimal problem of traditional HBF as two phases. In the analog beamforming (ABF) phase, the dominated path among the multi-path components is determined by the transmitter and receiver. In addition, the codebook-based beamforming weight vectors are bidirectionally and synchronously determined according to the angle parameters of the dominated path. In the second phase, based on the ABF matrices, the digital beamformers are designed to maximize the energy efficiency. Simulation results indicate that the proposed BPA-HBF scheme can lead to a lower convergence time and complexity than the conventional schemes. In addition, the results show that the algorithm convergence time can be significantly reduced by increasing the positioning precision.

Target position estimation of radar system has attracted much attention. Researchers have proposed a variety of joint direction‐of‐departure (DOD) and direction‐of‐arrival (DOA) estimation algorithms over the last few decades for this well‐known problem. However, traditional estimation algorithms require a pairing process between the DOD and DOA estimation. In this study, the authors propose an improved unitary estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm for joint DOD and DOA estimation without a pairing operation. The waveforms are transmitted by an array with M sensors and received by two detached sub‐arrays with and sensors, respectively. Specifically, the proposed algorithm eliminates a pairing process via sharing the eigenvectors of DOD and DOA. Theoretical derivation demonstrates that the proposed algorithm requires less computational complexity than two‐dimensional multiple signal classification (MUSIC), reduced‐dimension MUSIC, and ESPRIT. Simulation results show that the proposed algorithm can effectively enhance the accuracy of identifying and locating targets for the bistatic multiple‐input multiple‐output radar system.

With the development of the new generation satellite navigation and positioning systems utilise binary offset carrier (BOC) modulation to improve inter‐operability. The main shortcoming of BOC modulation is its ambiguity of searching for a multi‐peaked auto‐correlation function (ACF). In this study, an improved unambiguous synchronisation algorithm based on compensated correlation reconstructed technique (CCRT) is proposed for the arbitrary‐order BOC, which is a new modulation technique for navigation modernisation. The key technique used in this study is to generate local reference signals with different shape vectors. By recombining the piecewise correlation functions of the step‐shape coded symbol, a reconstructed correlation function which has only one peak is obtained, and the energy loss is compensated by the ACF. In the proposed algorithm, different shape vectors are employed in different BOC modulation signals. The simulation results demonstrate that the ambiguity problem is completely eliminated. Compared with traditional synchronisation methods, the proposed algorithm shows outstanding detection and multipath mitigation performance. Moreover, the CCRT can be utilised for arbitrary stage BOC modulation signals.

A new joint eigenvalue distribution (JED) based on dual extreme eigenvalues of finite random matrix is proposed in this study. Different from conventional JED based on K ( K ≥ 2) variables, only two variables are included in the proposed formulation. The upper and lower bounds of the new JED are determined. The new JED provides a simple and efficient way to deduce the distributions of key characteristics of finite random matrix, such as the extreme (largest and smallest) eigenvalues, standard condition number, and scaled largest eigenvalue. Moreover, a novel cooperative spectrum sensing (CSS) scheme based on the new JED is proposed for cognitive radio networks. The simulation results verify the proposed JED and the proposed CSS scheme can improve sensing performance.

Ultra-wideband (UWB) technology can provide a ranging accuracy of tens of centimeters with fine time resolution. UWB radio occupies a large bandwidth, e.g. at least 500 MHz, which translates to high multipath resolution. Thus, UWB is a suitable technology for accurate positioning through estimating time of flight (TOF) of the transmitted signal. In this paper, we present a highly accurate positioning scheme by estimating the round trip time (RTT) of frequency-converted transponded signal. The proposed scheme avoids complicated beam-forming techniques and clock synchronization between the unknown terminal and the referenced stations. To avoid employing high rate sampling analog-to-digital converters, we propose a novel time estimation method based on sliding correlation and a fractional delay polyphase filter. We use low-rate sampling data with polyphase filter to estimate the RTT, and obtain an equivalent sampling rate as high as tens of gigahertz. The theoretical analysis and numerical experiments demonstrate that the proposed scheme can realize high accuracy positioning.

Narrow band interference (NBI) suppression is one of major issues for ultra wideband (UWB) wireless communication system operating over huge spectrum occupied by narrow band wireless systems. In this paper, we propose an interference mitigation scheme based on complex-valued adaptive notch filter, which smartly exploits the substantial correlation difference of signals and removes the NBIs in UWB signal with noise by estimating the corresponding central frequencies. To obtain high speed convergence and maintain small signal distortion, a low complexity gradient algorithm for one-order basic adaptive notch filter cell is deduced. Considering that the data rate prior to despreading is extremely high, a novel time-division multiplexing (TDM) parallel approach for eliminating a single NBI is presented, which effectively simplify the hardware design especially in high speed digital signal processing. Based on the one-order basic adaptive notch filter cell, three different implementations including direct forms, linear cascade forms and TDM parallel cascade forms to eliminate multiple NBIs are developed and discussed. Theoretical analysis and simulation results indicate that the proposed scheme possesses the advantages of high convergence speed, small distortion and high stability. Furthermore, the propose scheme utilized as a preprocessing unit prior to despreading can considerably improve the interference tolerance margin of UWB systems, leading to it's suitable for the low complexity direct sequence (DS)-UWB receiver.