This paper presents a monolithic interface application-specific integrated circuit (ASIC) for a MEMS disk resonator gyroscope (DRG) with low zero-rate output (ZRO) drift and low scale factor (SF) nonlinearity. The ASIC is implemented under a high-precision force-to-balanced (FTR) mode combined with an easily integrable self-excitation drive loop. The ASIC improves the performance in two ways: First, based on an analysis of electrical errors in MEMS DRG performance, a time-domain anti-coupling architecture is proposed to reduce electrical coupling effects on ZRO drift and SF nonlinearity. This architecture also eliminates the need for high-bandwidth signal processing compared to traditional frequency-domain architectures. Second, the first-order linear relationship between ZRO drift and drive amplitude voltage in the FTR mode is analyzed and validated, and a low hardware compensation circuit is designed to correct ZRO drift. The ASIC is fabricated using a $0.35\mu $ m BCD process with a chip area of 4.3 mm $\times 4.2$ mm. Combined with the MEMS structure, it achieves a bias instability (BI), angle random walk (ARW), and SF nonlinearity of 0.018°/h, 0.0055° h, and 108 ppm, respectively.

Affine Frequency Division Multiplexing (AFDM) is a chirp-transform modulation technique that has shown reliable performance in high-mobility scenarios, making it an attractive option for next generation communication systems. Recent literature suggests that under chirp parameter adjustment, AFDM can achieve optimal diversity performance in delay-doppler channels with maximum likelihood (ML) detection. However, the performance of AFDM with minimum mean square error equalization (MMSE-Eq) has not been extensively investigated in the existing literature. In this paper, we analyze the performance of AFDM with MMSE-Eq, derive a lower bound for the theoretical bit error rate (BER) of the AFDM system, and discuss the relationship between chirp parameters and performance degradation. To optimize BER performance, we propose two distinct chirp parameter selection strategies for frequency selective and doubly selective channels, respectively. These strategies offer the advantage of avoiding extensive computations. Additionally, we propose a low-complexity and high-performance iterative MMSE-Eq algorithm based on time-domain channel matrix operations. The algorithm resolves the issue encountered in existing low-complexity methods, where different chirp parameter selections significantly impact the complexity. Simulation results demonstrate the efficacy of our proposed parameter selection strategies and the outstanding BER performance achieved by the iterative MMSE-Eq algorithm.

Space-air-ground integrated network (SAGIN), as an integration of interconnected space, air, and ground network segments, is expected to see prevalent usage as part of intelligent transportation systems (ITS), providing an enhanced service provision in terms of coverage, flexibility and reliability. However, restricted by the limited and unbalanced network resources, the efficiency and security of the underlying connectivities of SAGIN are of utmost concern for ITS applications. In this paper, a weighted fractional Fourier transform (WFRFT) based parallel complex spreading (PCS) approach is proposed to improve the communication efficiency and security of SAGIN at the physical (PHY-) layer. The concept of WFRFT along with the direct sequence spread spectrum technology establish the security kernel of the proposed scheme. The practicability of the complex-valued WFRFT-spreading architecture is verified by studying the correlation properties of the WFRFT-spreading signals. Taking advantages of the signal uniqueness of WFRFT, the proposed scheme is capable of providing more flexibility in signal characteristic control. Moreover, the complex-valued WFRFT-spreading processing makes the proposed scheme inherently robust against the large Doppler shift distortions in SAGIN. Simulation results demonstrate the superiority of the proposed WFRFT-PCS scheme in terms of communication efficiency and PHY-layer security. Finally, as a proof of concept, an all-digital FPGA prototype system is designed to show the practicability and the performance enhancement of the proposed scheme.

In order to minimize the weight and volume of the radio frequency equipment while alleviating the shortage of spectrum resources, electronic system integration has become a topical area in both civil and military fields, and the radar-communications integrated technology based on the time-modulated array (TMA) has also been proposed due to its low complexity and easy reconfiguration property. The TMA has power losses caused by sideband signals radiation, which is inherent drawback. However, existing TMA power loss optimization methods are not suitable for radar-communication integration, because of the existence of multiple harmonic components. In this paper, a closed-form expression of TMA power losses for radar-communications integration is derived and the sideband radiation is optimized. Firstly, some preliminaries about TMA are shown. Then, the radar-communications integration strategy based on TMA is introduced. Moreover, a closed-form expression of TMA power losses caused by sideband signals radiation is derived, and the direct power losses optimization method is proposed based on the derived results. Finally, the theoretical results are validated by simulations.

Exploiting physical (PHY)-layer characteristics for authentication has great potential to provision underlying trust for low-ended Internet of things (IoT) devices with limited computation resources. In this paper, we propose an online learning aided adaptive PHY-layer authentication framework for enhanced authenticity provisioning. Instead of relying on some preset PHY-layer signatures with scenario-sensitive ?thresholds?, multiple PHY-layer attributes are jointly considered by the proposed scheme to improve the reliability and robustness of PHY-layer authentication. Such a dimension extension on PHY-layer signatures can effectively deteriorate the spoofing capability of malicious attackers. However, it also complicates the predicting and authenticating procedure of the legitimate receiver. Therefore, artificial intelligence aided search algorithms are formulated to facilitate adaptive selection of the Most Effective PHY-layer Attributes (MEA) through learning their historical authenticity performance. To be specific, the attributes which are predicted to be effective in maximizing the authentication capability, in terms of low false alarm rate and low miss detection rate, will be dynamically selected by the authenticator in an autonomous manner. Theoretical analysis shows that the proposed learning algorithm achieves asymptotically diminishing regret. Moreover, extensive experiments are conducted using Universal Software Radio Peripherals (USRPs) in a laboratory environment, which further validates the efficiency of the proposed scheme.

In this letter, we derive the basic conditions that should be met for the weighted signal suitable for the communication system and extend the weighted fractional Fourier transform (WFRFT) based classical hybrid carrier system to the generalized hybrid carrier system. Furthermore, a generalized hybrid carrier signal design is presented with equal component power. Compared with the classical hybrid carrier signal, the power distribution of the proposed system in the time-frequency plane is more uniform which makes it more suitable for doubly selective channels. Simulation results show that over doubly selective channels, the generalized hybrid carrier signal with equal component power achieves better bit error rate (BER) performance than the classical hybrid carrier signal does.