Due to the large number of antennas in the antenna array, channel estimation for millimeter-wave (mm-Wave) massive MIMO becomes complex. Leveraging the sparsity of mm-Wave channels is an effective approach to reduce complexity and improve accuracy. For channel estimation methods that utilize the prior probability distribution of the sparse channel vector, the accuracy of the probability distribution is critical to the performance of channel estimation. This paper proposes a higher-order Markov prior model combined with the Turbo-OAMP framework, which is suitable for mm-Wave channel estimation scenarios where channel sparsity changes rapidly. Numerical simulation results show that the proposed method achieves better estimation accuracy and robustness in time-varying sparse mm-Wave channels.

Orthogonal time frequency space (OTFS) modulation has shown exceptional performance in high-mobility scenarios. However, downlink channel estimation in massive multiple-input multiple-output (MIMO) OTFS systems remains challenging due to limited Doppler and angular resolutions, underutilization of domain-specific channel characteristics, and substantial computational complexity. In this paper, we propose a multi-domain decoupled channel estimation framework that separates the coupled channel into its individual domain components. The framework enhances the utilization of channel characteristics and provides more flexibility in algorithm design. Based on the proposed framework, we develop a multi-domain decoupled Bayesian learning (MDDC-BL) channel estimation algorithm, achieving super-resolution performance in both Doppler and angular domains. For angular-domain estimation, we devise a dictionary learning based pattern-coupled Bayesian learning (DL-PC-BL) channel estimation algorithm to effectively capture the channel characteristics and handle the off-grid components. Additionally, the MDDC-BL algorithm reduces the dimensionality of the estimation model, thereby significantly lowering computational complexity. Simulation results demonstrate the superior performance of the proposed framework and channel estimation algorithms over existing state-of-the-art schemes.

In this paper, the weighted fractional Fourier transform (WFRFT) signal domain is introduced to enhance the security performance of two-way trusted relay systems at the signal level. The proposed scheme, which requires only a single relay node, leverages the multi-component energy distribution characteristics of WFRFT signals to improve security with low complexity and high power efficiency. The inherent security mechanism of WFRFT analyzed in this paper can be simply summarized as follows: the superposition of components in WFRFT signals that do not satisfy specific constraints will result in the inability to perfectly reconstruct the message signal. Based on this, confidential information is encoded into WFRFT signals with private transform orders, allowing legitimate users to achieve perfect decoding. Since WFRFT signals exhibit energy concentration only in specific transformation domains, mismatched transform orders adopted by the eavesdropper cause energy loss in the information-bearing signal, leading to inter-component interference that further degrades the quality of the recovered signal. The advantages of the proposed scheme in limiting information leakage and improving the achievable secrecy sum rate (SSR) are analyzed. Numerical results validate the theoretical analysis and demonstrate the secrecy performance of the proposed scheme.

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.

In this paper, we investigate hybrid precoder design to enhance the physical layer security of the millimeter-wave (mmWave) system with multiple eavesdroppers. Differing from traditional spatial domain-based schemes, we introduce an extra signal domain dimension and propose a multi-component-based security mechanism for the hybrid precoding system model. The model integrates both signal and spatial domains for designing baseband and analog precoders, ensuring that the received signal at the legitimate user complies specific signal domain characteristics. Consequently, all received energy becomes available for signal reconstruction, whereas the distorted signal at eavesdroppers inevitably forms inter-component interference. By introducing general multi-fractional Fourier transform (GMFRFT) signal domain into the model, we propose a specific GMFRFT-based scheme for subarray architectures. The secrecy performance is analyzed, and power allocation methods between multiple components are designed. Additionally, to optimize the utilization of spatial domain resources, we propose a GMFRFT-based scheme with dynamic subarrays, along with a low-complexity subarray partitioning algorithm. Furthermore, a GMFRFT-based scheme for fully connected architectures is investigated. It is verified to be equivalent to a lower-complexity weighted fractional Fourier transform (WFRFT)-based analog beamforming scheme, the efficacy of which hinges on the adherent secrecy provided by WFRFT signals. Both theoretical analysis and numerical results demonstrate the effectiveness of the proposed schemes.

Accurately estimating channels with fractional Doppler and delay is a challenging task for orthogonal time-frequency space (OTFS) systems. This paper proposes using the bilinear vector approximate message passing (Bi-VAMP) algorithm to sparsely estimate integer delay and Doppler shifts and learn fractional delay and Doppler shifts separately. The scalar coefficients of uncertain matrices are extended to vector form, transforming the first-order approximation model of the effective delay-Doppler (DD) domain channel response into an uncertain matrix estimation model. Furthermore, considering the characteristics of OTFS channels, this paper provides some suggestions to enhance the convergence robustness of the Bi-VAMP algorithm. Simulation results validate that compared to other on-grid and off-grid methods, the proposed off-grid Bi-VAMP OTFS channel estimation scheme exhibits significant advantages in normalized mean square error (NMSE) performance metrics.

In this paper, a fast beam training method based on geometric beam patterns is proposed. It accumulates precise geometric patterns created by extremely large-scale MIMO with displacement from different training frames and covers all directions. By analyzing beam gains of different patterns which contributed by the channel angle and geometric shapes, the proposed method acquires more channel angle information and significantly reducing beam training frames. Both analytical and simulation results demonstrate the proposed method has a faster error convergence speed compared with traditional methods. It becomes possible to achieve fast beam alignment in a few training frames for millimeter-wave extremely large-scale MIMO in high-mobility scenarios such as vehicular networks.

The Cyclic prefix (CP) in traditional OFDM systems is used to combat inter-symbol Interference (ISI) and inter-carrier Interference (ICI), which simplifies the design of the equalizer by converting the linear convolution (LS) between symbols and the channel into cyclic convolution (CC). However, the overhead of CP reduces the system’s spectral efficiency and energy efficiency. This paper proposes a CP-free OFDM system called TSE-OFDM by exploiting a truncated symbol extrapolation (TSE) module. The TSE module categorizes the received OFDM symbols into reliable and unreliable parts based on their susceptibility to ISI. By iteratively extrapolating the reliable portion unaffected by ISI, the TSE module restores the CC characteristic of the received symbols. We conduct noise analysis and simulations to evaluate the performance of the extrapolation algorithm, demonstrating its robustness against out-of-band noise. Furthermore, we simulate the TSE-OFDM system to assess its bit error rate (BER) and spectral efficiency (SE). The simulation results show that TSE-OFDM significantly improves SE while maintaining satisfactory BER performance. Compared to other CP-free OFDM schemes, TSE-OFDM exhibits ample tolerance to symbol timing offset (STO) and channel estimation errors.

As a lightweight, flexible, and high-performance operating system virtualization, containers are used to speed up the big data platform. However, due to the imperfection of the resource isolation mechanism and the property of shared kernel, the meltdown and spectre attacks can lead to information leakage of kernel space and coresident containers. In this article, a noise-resilient and real-time detection system, named ContainerGuard, is proposed to detect meltdown and spectre attacks in the container-based big data platform. ContainerGuard uses a nonintrusive manner to collect lifecycle multivariate time-series performance event data of processes in containers and then uses ensemble of variational autoencoders as generative neural networks to learn the robust representations of normal patterns. Therefore, ContainerGuard meets the urgent need for information protection in the container-based big data platform. Our evaluations using real-world datasets show that ContainerGuard achieves excellent detection performance and only introduces about 4.5% of running performance overhead to the platform.

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.

The weighted-type fractional Fourier transform (WFRFT)-based hybrid carrier (HC) system has been proposed to bridge the gap between orthogonal frequency division multiplexing (OFDM) system and single-carrier system with frequency domain equalization (SC-FDE). In this paper, we propose a novel HC system based on efficient fast-convolution (FC) without a cyclic prefix to meet the requirements of complex scenarios towards future communications. The proposed system can achieve flexible optimization of system performance, such as minimizing out-of-band emission (OOBE), peak to average power ratio (PAPR) and bit error rate (BER). This efficient FC based hybrid carrier (FCHC) system is among the most competitive waveforms. The closed-form BER expressions are derived and analyzed over additive white Gaussian noise (AWGN) and frequency-selective fading channels. A modified equalizer over frequency-selective channels is also provided to resist the inter-block interference (IBI). Moreover, the banded minimum mean-square error (MMSE) equalization based on FC can be embedded in the proposed system over doubly-selective channels, and then the interference caused by fading channels can be further suppressed through the combination of FC and HC. The simulation results demonstrate the superiority of the proposed system over the conventional HC system in terms of OOBE, PAPR and BER. The significant flexibility and combined performance advantages make the proposed system a potential scheme for future communications.

In this paper, we propose a security scheme based on extended weighted fractional Fourier transform to guarantee the physical layer security of wireless communication. The proposed scheme extends the existing fractional Fourier transform and reduces the equivalent signal-to-noise ratio and recognition probability of the eavesdropper by utilizing the anti-interception characteristics of the extended hybrid carrier signal, which guaranteed the robust nonzero security capability and anti-recognition performance. Moreover, due to the extension of parameter dimension, the diversity and design flexibility of EWFRFT also have adverse impacts on wiretapping. In addition, the self-interference property of the EHC signal is proposed and analyzed in detail to further enhance the security performance. Theoretical analysis and numerical simulation results show the superiority of the EWFRFT method. Compared with the existing HC system, the proposed scheme reduces the possibility of interception by eavesdroppers without extra computational complexity, which effectively guarantees the security of the system.

In this paper, a two-dimensional weighted fractional Fourier transform (2DWFRFT) based secure spatial modulation (SM) scheme is proposed to enhance the physical layer security (PLS) of the wireless communication system. In the proposed scheme, 2DWFRFT is implemented as the security kernel for PLS provision. The invertibility and uniqueness of the 2DWFRFT effectively protect the confidential messages from being intercepted by the eavesdroppers while imposing no performance degradation on the legitimate receiver. Both the signal generation strategy and the ergodic secrecy rate analysis under discrete-input continuous-output memoryless (DCMC) channel have been elaborated to depict the security mechanism of the proposed scheme. The maximum likelihood (ML) detector and the separate detection (SD) algorithm are formulated to correctly recover the received signal of our system. Simulation results demonstrate that the proposed scheme can achieve a much higher secrecy capacity than artificial noise schemes without requiring additional jamming power consumption.

In this paper, we propose an adaptive multi-attributes based physical layer authentication framework for enhanced authenticity provisioning. Instead of optimizing the "threshold" for a preset PHY-layer signature, this paper resort to exploiting and selecting multiple historical better performed PHY-layer attributes for authentication enhancement. In particular, the authenticator of the proposed scheme is designed to be capable of recording the historically performance of each potential attribute. Based on which, the most effective PHY-layer attributes (MEA) would be chosen to improve the reliability of the PHY-layer authentication. This paper experimentally proves that the dimension extension on PHY-layer signature attributes effectively enhances authenticator's capability in signal discrimination. However, with more attribute to observe, it also complicates the predicting and authenticating procedure. Therefore, a learning-based search algorithm is then formulated to facilitate the MEA selection procedure. Both theoretical analysis and experiment results are given to demonstrate the efficiency and superiority of the proposed scheme.

Cyclic prefix (CP) insertion is the most common way for inter-symbol interference (ISI) suppression, however, detrimental to the high-speed data transmission demand for its waste of spectrum resources. To solve this problem, a CP-free hybrid-carrier(HC) scheme is proposed in this paper. In the proposed scheme, the inherently relational process between circular convolution and Fourier transformation is utilized through zero-padding and interval extraction to maintain the cyclic characteristic of the received data block instead of the conventional CP insertion. Both analytical and simulation results are provided to demonstrate the practicability and the superiority of the proposed scheme, in term of bit error rate(BER) performance. Moreover, the proposed CP-free HC-FDE is also proved to be more spectral effective compared to the conventional FDE schemes.

Wireless communication in substation scenarios can be seriously degraded by impulsive noise. In this paper, we aim to investigate and mitigate the impact of impulsive noise for substation communications. Specifically, symmetric alpha-stable (SaS) distribution is used to model the impulsive noise and channel in substation scenario is modeled as a frequency selective fading channel with additive impulsive noise. Based on weighted fractional Fourier transform (WFRFT), a hybrid carrier (HC) scheme that is compatible with both conventional single carrier (SC) and multi-carrier (MC) schemes is introduced. Further, the WFRFT-based HC system combined with Alamouti scheme, referred as to HC-Alamouti, is proposed to mitigate the adverse effects of impulsive noise and frequency selective fading in substation scenarios. The impulsive noise mitigation mechanism of the proposed HC-Alamouti scheme is analyzed. Moreover, simulation results are given to show the superiority of the proposed HC-Alamouti system in terms of bit error rate (BER).

With the high mobility, flexibility and manoeuvrability, unmanned aerial vehicles (UAVs)‐enabled mobile edge computing (MEC) plays an important role in many applications that lack of available terrestrial infrastructures, such as disaster response, emergency relief and military scenarios. However, the high mobility of UAVs may severely degrade the implementation of UAV‐enabled MEC in computation‐intensive or delay‐sensitive scenarios from a physical layer signalling perspective, e.g. frequency selective fading effect caused by the low altitude and low elevation angle routes of UAVs. In this study, a generalised weighted‐type fractional Fourier transform (GWFRFT) based signal energy‐spreading transmission (EST) scheme is proposed for signalling and quality of service (QoS) provisioning for UAV‐enabled MEC. In the proposed scheme, the communication signal energy is redistributed evenly at the time‐frequency plane to enhance the robustness of UAV communications against the severe fading channels. The signalling provisioning mechanism of the GWFRFT‐EST scheme is analysed and simulated under poor air‐to‐ground channels with low Rician K ‐factor. Simulation results show that the proposed method greatly improves the bit error rate performance with a negligible computational complexity increase.

Internet of Things (IoT) is regarded as the fundamental platform for many emerging services, such as smart city, smart home, and intelligent transportation systems. With ever-increasing penetration of IoT, it becomes of great importance to ensure the IoT security, as the security threats are extended from the cyber world to the physical world. In this article, we investigate physical-layer authentication to help verify the identity of IoT entities for preventing unauthorized access to information or service. Specifically, we propose a Gaussian-tag-embedded physical-layer authentication (GTEA) scheme by using a weighted fractional Fourier transform (WFRFT). Through the superimposition of a low-power Gaussian WFRFT tag onto the message signal, the legitimate receiver can verify the authenticity of the received signal at the physical layer, without being detected by adversaries. Moreover, security analysis shows that with the deliberately designed Gaussian tag, the GTEA scheme is robust against spoofing and replaying attacks. In addition, tradeoff analysis and simulation results are provided to demonstrate the capability of the GTEA scheme in achieving reliability of the message delivery, stealth of the embedded tag signal, and balancing the tradeoff among the robustness of user authentication. Moreover, a prototype is further developed using FPGA and experiments are conducted to demonstrate the effectiveness and performance improvement of the proposed GTEA scheme.

In this paper, we study physical layer message authentication with perfect security for wireless networks, regardless of the computational power of adversaries. Specifically, we propose an efficient and feasible authentication scheme based on low-density parity-check (LDPC) codes and ϵ-AU2hash functions over binary-input wiretap channel. First, a multimessage authentication scheme for noiseless main channel case is presented by leveraging a novel ϵ-AU2hash function family and the dual of large-girth LDPC codes. Concretely, the sender Alice first generates a message tag T with message M and key K by using a lightweight ϵ-AU2hash functions; then Alice encodes T to a codeword Xnwith the dual of large-girth LDPC codes; finally, Alice sends (M, Xn) to the receiver Bob noiselessly. An adversary Eve has infinite computational capacity, and he can obtain M and the output Znof the BEC with input Xn. Then, an authentication scheme over binary erasure channel and binary-input wiretapper's channel is further developed, which can reduce the noisy main channel case to noiseless main channel case by leveraging public discussion. We theoretically prove that, the proposed schemes are perfect secure if the number of attacks from Eve is upper bounded by a polynomial times in terms of n. Furthermore, the simulation results are provided to demonstrate that the proposed schemes can achieve high authentication rate with low time latency.

This paper proposes a Weighted fractional Fourier transform (WFRFT) based cooperation scheme to improve PHY layer security against eavesdropping in wireless communications. Rather than dissipating valuable transmission power to jam the eavesdropper, by leveraging the features of WFRFT, the information bearing signal can create “Artificial Noise” effect at the eavesdropper while imposing no effect on the legitimate receiver. Specifically, the proposed WFRFT based cooperation is performed in a two-phase manner, whereby the source first broadcasts its message to the intermediate nodes which then perform WFRFT operation to relay the message to the destination, with the objective of boosting the secrecy rate of the source-destination pair. Simulation results are provided, which demonstrate that the WFRFT-based user cooperation scheme can acehieve a significant performance gain, in terms of secrecy ergodic capacity, compared with conventional security-oriented user cooperation schemes.

In spectrum sharing networks with relay cooperation, primary users can benefit from the assistance of secondary users while secondary users accessing the primary bandwidth to transmit their signals. Reasonable relay selection strategy can improve the performances of both primary and secondary users in terms of higher transmission data rate and lower outage probability, and at the same time, frequent relay switching can be avoided. In this paper, we propose a relay selection strategy considering both relay mobility and the required transmission data rate of primary user. The metrics of relay selection combine the relay activation duration and the transmission data rate of the secondary users through the mobility prediction of relay nodes. Simulation results show that the proposed strategy can select the best relay with lower primary outage probability and longer relay activation duration compared with existing schemes, and the transmission data rate of secondary user can also be improved so that the total number of transmit information bits can be increased.

Vehicular communication networks expect to accommodate the ever-increasing on-road wireless traffic by deploying roadside units (RSUs) and meanwhile exploiting existing wireless infrastructures. To achieve flexible deployment, energy-saving operation and low-latency services, a new type of RSUs, namely cache-enabled green RSUs are introduced, which can store popular contents locally and harvest renewable energy as power source. In this paper, we investigate cost-effective planning of heterogeneous vehicular networks consisting of conventional macro base stations and cache-enabled green RSUs. Specifically, the RSU density, cache size, and energy harvesting rate are jointly optimized to minimize network deployment cost, under the constraints of quality of service (QoS) requirements and limited backhaul capacities. For QoS guarantee, the lower bound of average data rate is derived in closed form by applying the theory of stochastic geometry, based on which the cost-effective network deployment scheme is proposed. Analytical results reveal the tradeoff between cache size and backhaul capacity, indicate renewable energy harvesting rate should be sufficient to support rush-hour demands, and also provide the optimal RSU density for the given vehicular traffic demands. Extensive simulations are conducted for validation. In addition, numerical results of optimal network planning are provided in details to offer insights into practical system design.

In this paper, we propose a novel user cooperation scheme based on weighted fractional Fourier transform (WFRFT), to enhance the physical (PHY) layer security of wireless transmissions against eavesdropping. Specifically, instead of dissipating additional transmission power for friendly jamming, by leveraging the features of WFRFT, the information bearing signal of cooperators can create an identical artificial noise effect at the eavesdropper while causing no performance degradation on the legitimate receiver. Furthermore, to form the cooperation set in an autonomous and distributed manner, we model WFRFT-based PHY-layer security cooperation problem as a coalitional game with non-transferable utility. A distributed merge-and-split algorithm is devised to facilitate the autonomous coalition formation to maximize the security capacity while accounting for the cooperation cost in terms of power consumption. We analyze the stability of the proposed algorithm and also investigate how the network topology efficiently adapts to the mobility of intermediate nodes. Simulation results demonstrate that the WFRFT-based user cooperation scheme leads to a significant performance advantage, in terms of secrecy ergodic capacity, compared with the conventional security-oriented user cooperation schemes, such as relay-jamming and cluster-beamforming.

In this paper, weighted fractional Fourier transform (WFRFT) is employed to safeguard the physical layer (PHY) security of wireless communications. By leveraging the features of WFRFT, we propose a PHY security modulation scheme, which significantly degrades the equivalent signal-to-noise ratio (SNR) of the unauthorized receiver while imposing no impact on the legitimate receiver. With the proposed scheme, a robust nonzero secrecy capacity can be guaranteed. Moreover, the proposed scheme can conceal the actual modulation paradigms to prevent malicious signal detection, due to the variation in signal characteristics. A higher order statistics (HOS) based classifier is used to investigate the anti- recognition performance. Meanwhile, the secrecy performance of the proposed scheme is evaluated in terms of both secrecy capacity and average bit error rate (BER) by numerical simulations. Finally, as a proof-of-concept, an all-digital field programmable gate array (FPGA) based prototype system is developed to validate the practicability of the proposed scheme.

Exploiting physical layer (PHY) characteristics has great potential to complement and secure upper-layer authentication protocols. Unlike existing PHY authentication mechanisms requiring special hardware designs, in this paper, we propose a practical PHY- aided authentication approach based on weighted fractional Fourier transform (WFRFT). Instead of exploiting the channel or hardware characteristics that are out of control, the proposed scheme can provide two-fold protection on upper-layer protocols by leveraging the intrinsic PHY features of the transmitted signal. Firstly, WFRFT can hide and forge the modulation paradigm to mislead attackers in signal demodulation. Secondly, WFRFT signal can be adjusted among different patterns automatically and dynamically to provide more security and freedom in PHY authentication, similar to frequency-hopping systems. Numerical simulations and analyses demonstrate that the proposed scheme can achieve more secure authentication with tolerate computational overhead.