Directional modulation (DM) is a physical layer security (PLS) technique implemented at the transmitter, leveraging antenna arrays to ensure secure communications. Through a process of spatial precoding between transceivers to transmit signals in specific directions, DM is capable of disrupting communications in unintended directions to prevent eavesdropping. In general, recent progress in the development of multiple-input multiple-output (MIMO) systems, including advanced radio frequency (RF), antenna technologies, along with innovative precoding algorithms, has enhanced the capabilities of DM techniques, leading to a multitude of robust DM variants. Hence, this survey aims to offer a comprehensive overview of DM, covering its fundamentals, promising variants, applications, hardware implementations, and future trends. Initially, the basic principle of DM is outlined in a general manner for subsequent comprehension. Subsequently, the large family of DM techniques is categorized into distinct variants based on the types of transmitting arrays. Next, we give a comprehensive survey of DM in common wireless scenarios, including multi-user (MU), relay, Internet of Things (IoT), and non-orthogonal access (NOMA) networks. Furthermore, we provide an illustration of DM system implementations, encompassing foundational architectures and cost-effective hardware realizations. Finally, concerning the unresolved challenges and current research focal points in DM, we present future research directions that merit further exploration and reference.

Deep learning techniques have been widely used for two-dimensional (2D) and three-dimensional (3D) computer vision problems, such as object detection, super-resolution (SR) and classification to name a few. Radar images suffer from poor resolution as compared to optical images, hence developing a high-accuracy model to solve computer vision problems, such as a classifier, is a challenge. This is because of the lack of high-frequency details in the input images which makes it difficult for the classifier model to generate accurate predictions. Ways of addressing this challenge include training the learning model with a large dataset or using a more complicated model, such as deeper layer architecture. However, employing such approaches might result in the overfitting of the model, where the model might not generalize well on previously unseen data. Also, generating a large dataset for training the model is a challenging task, especially in the case of radar images. An alternate solution for achieving high accuracy in radar classification problems is provided in this paper wherein a CNN-enabled super-resolution (SR) model is integrated with the classifier model. The SR model is trained to generate high-resolution (HR) millimeter-wave (mmW) images from any input low-resolution (LR) mmW images. These resolved images from the SR model will be used by the classifier model to classify the input images into appropriate classes, consisting of threat and non-threat objects. The training data for the dual CNN layers are generated using a numerical model of a near-field coded-aperture computational imaging (CI) system. This trained dual CNN model is tested with simulated data generated from the CI numerical model wherein a high classification accuracy of 95% and a fast inference time of 0.193 s are obtained, making it suitable for real-time automated threat classification applications. For fair comparison, the developed CNN model is also validated with experimentally generated reconstruction data, in which case, a classification accuracy of 94% is obtained.

Abstract Recent works have shown that by using time‐modulated arrays (TMAs), directional modulation (DM) physical‐layer secured transmitters for orthogonal frequency‐division multiplexing (OFDM) wireless data transfer can be constructed. In this paper, three‐state TMAs are introduced for OFDM DM systems which allow more flexible manipulation of the injected orthogonal artificial noise and hence improve security. In particular, this paper presents for the first time both static and dynamic three‐state time‐modulated OFDM DM systems. Simulated bit error rate (BER) spatial distributions are shown for various system configurations in order to illustrate representative examples of secrecy performance enhancement that can be achieved by the proposed transmitter arrangement.

This paper proposes a technique which allows quadband impedance matching and impedance level shifting Doherty power amplifier (DPA) design. By using novel coupler networks with reactance and choosing appropriate complex load impedances, the quadband DPA can reach a power back-off range (OBO) of over 9 dB. In addition, the peak PA branch and the carrier PA branch use different coupler network parameters in order to satisfy different impedance requirements. To illustrate the design procedure a quadband DPA with 9 dB OBO operating in 0.5-0.7 GHz, 1.5-1.7 GHz, 2.5-2.7 GHz, and 3.5-3.7 GHz frequency ranges is designed, fabricated and tested. Measurements demonstrate that the DPA can deliver saturated output power between 43.1 dBm and 43.8 dBm in all four bands, with a drain efficiency ranging from 63.3% to 66.5%. Also, drain efficiency of from 42.2% to 52.3 % can be obtained at an OBO of 9 dB level. The DPA implemented here shows state-of-the-art performance for OBO under quad-band operation.

The frequency diverse array (FDA)-based directional modulation (DM) technology plays an important role in the physical-layer security (PLS) transmission of 5G and beyond communications. In order to meet the tremendous increase in mobile data traffic, a new memory-efficient design for the FDA-DM-based PLS transmission is urgently demanded. In this article, an analytical symmetrical multi-carrier FDA model is proposed in three dimensions, namely, range, azimuth angle, and elevation angle, differing from the conventional analytical approach with only range and azimuth angle considered. Then, a single-point (SP) artificial noise (AN) aided FDA-DM scheme is proposed, which reduces the memory consumption significantly compared with the conventional zero-forcing (ZF) and singular value decomposition (SVD) approaches. Moreover, the PLS performance of the proposed FDA-DM scheme is analyzed in fluctuating two-ray (FTR) fading channels for the first time, including the average secrecy capacity (ASC) and the secrecy outage probability (SOP). More importantly, the closed-form expressions for the lower bound on ASC and the upper bound on SOP are derived, respectively. The effectiveness of the analytical expressions is verified by numerical simulations. This work opens a way to lower the memory requirements for DM-based PLS transmission of 5G and beyond communications.

Accurate channel state information (CSI) is essential at the base station (BS) in order to serve multiple users simultaneously on the same time-frequency resources. Explicit low-rate CSI feedback from each user terminal to the BS is indispensable in frequency-division duplexing (FDD) multipleinput multiple-output (MIMO) hybrid precoding systems. In the presence of correlated Rician fading channels with arbitrary rank, and in order to reduce the feedback overhead, a unified adaptive statistical codebook is designed by leveraging the long-term first and second order channel statistics. Moreover, as the feedback overhead scales linearly with the number of BS antennas, which introduces a bottleneck in FDD massive MIMO systems, an adaptive two-stage reduced dimensionality codebook design is developed. The main idea stems from the fact that the high dimensional analog beamforming stage could get away with coarse CSI, e.g., statistical CSI, while the low dimensional baseband precoding stage acquires finite-rate quantized CSI of the reduced dimensionality channel to eliminate multiuser interference. These steps reduce significantly the CSI training and feedback overhead to scale linearly with the number of radio-frequency chains instead. For comparison purposes, the two extremes of full and statistical CSI at the BS are also included. The performance gap between these two extremes justifies the importance of the proposed two-stage reduced dimensionality adaptive statistical codebook.

To fully reap the benefits of massive multiple-input multiple-output hybrid analog and digital precoding in frequency division duplexing single-cell systems, a two-stage precoder is developed utilizing the signal-to-leakage-plus-noise ratio metric. The main idea of this technique is to jointly design the analog precoder based only on the long-term channel statistics information at the transmitter, i.e., the channel mean and reconstructed reduced rank covariance statistics, while the digital precoder is designed based on the instantaneous channel state information of the reduced dimensionality effective reconstructed channel. Consequently, we can significantly reduce the downlink training and uplink feedback overhead analogously to the rank of the resultant effective channel. The two extremes of full channel state information at the transmitter (CSIT) and statistical CSIT are also investigated. The performance gap between the full and statistical CSIT corroborates the importance of the proposed two-stage CSIT approach. These precoders are then extended to multi-cell systems. It is shown that the digital baseband precoder design problem reduces to the generalized Rayleigh quotient problem, while the analog precoder design problem reduces to the quotient trace problem, also known as the ratio trace problem. These dimensionality reduction problems are solved via the generalized eigenvalue decomposition method. Finally, in the presence of multiuser diversity where only a subset of the users are scheduled, to considerably alleviate the channel estimation and feedback overhead burden, a low-complexity one-stage and two-stage CSIT joint user scheduler and precoder algorithms are developed.

In this treatise, we introduce a novel polarization modulation (PM) scheme, where we capitalize on the reconfigurable polarization antenna design for exploring the polarization domain degrees of freedom, thus boosting the system throughput. More specifically, we invoke the inherent properties of a dual polarized (DP) antenna for transmitting additional information carried by the axial ratio (AR) and tilt angle of elliptic polarization, in addition to the information streams transmitted over its vertical (V) and horizontal (H) components. Furthermore, we propose a special algorithm for generating an improved PM constellation tailored especially for wireless PM modulation. We also provide an analytical framework to compute the average bit error rate (ABER) of the PM system. Furthermore, we characterize both the discrete-input continuous-output memoryless channel (DCMC) capacity and the continuous-input continuous-output memoryless channel (CCMC) capacity as well as the upper and lower bounds of the CCMC capacity. The results show the superiority of our proposed PM system over conventional modulation schemes in terms of both higher throughput and lower BER. In particular, our simulation results indicate that the gain achieved by the proposed Q-dimensional PM scheme spans between 10dB and 20dB compared to the conventional modulation. It is also demonstrated that the PM system attains between 54% and 87.5% improvements in terms of ergodic capacity. Furthermore, we show that this technique can be applied to MIMO systems in a synergistic manner in order to achieve the target data rate target for 5G wireless systems with much less system resources (in terms of bandwidth and the number of antennas) compared to existing MIMO techniques.

A two-ray multipath model for frequency diverse array (FDA)-based directional modulation (DM) is proposed in multi-input single-output multi-eavesdropper (MISOME) wiretap channels for the first time. The excitation factors of the FDA and the weighting coefficients of the inserted artificial noise (AN) are jointly designed in a way which imposes no impact on the desired receiver while simultaneously distorting the received signals of eavesdroppers. Secrecy rate is analyzed for the proposed two-ray multipath FDA-based DM model. Numerical simulations verify the capability of physical layer secure (PLS) transmissions of the proposed FDA-DM model in two-ray multipath MISOME wiretap channels.

The artificial noise (AN) aided multi-beam directional modulation (DM) technology is capable of wireless physical layer secure (PLS) transmissions for multiple desired receivers in free space. The application of AN, however, makes it less power-efficient for such a DM system. To address this problem, the weighted fractional Fourier transform (WFRFT) technology is employed in this paper to achieve power-efficient multi-beam DM transmissions. Specifically, a power-efficient multi-beam WFRFT-DM scheme with cooperative receivers and a power-efficient multi-beam WFRFT-DM scheme with independent receivers are proposed based on frequency diverse array (FDA), respectively. The bit error rate (BER), secrecy rate, and robustness of the proposed multi-beam WFRFT-DM schemes are analyzed. Simulations demonstrate that 1) the proposed multi-beam WFRFT-DM schemes are more power-efficient than the conventional multi-beam AN-DM scheme; 2) the transmission security can also be guaranteed even if the eavesdroppers are located close to or the same as the desired receivers; and 3) the proposed multi-beam WFRFT-DM schemes are capable of independent transmissions for different desired receivers with different modulations.

In this paper, we take a fundamental look at the interference characteristics of a lens-based millimeter-wave (mmWave) multiuser multiple-input multiple-output system (MU-MIMO) system. We consider a hybrid architecture, implemented via a bank of radio-frequency (RF) switches which perform beam selection followed by low-complexity uplink maximum-ratio combining (MRC) at baseband. Considering a Rotman lens antenna array in line- of-sight (LoS) propagation, we derive tight analytical approximations to the average (expected) interference power of an arbitrary terminal, with and without the presence of RF switching. The analytical expressions show that without RF switching, the Rotman lens losses its benefits and collapses to a conventional uniform linear array. Our numerical results demonstrate that the expected interference power to a given terminal decreases significantly with RF switching, due to beam selection separating the uplink direction-of-arrivals (DoAs), in contrast to the case without RF switching, which relaxes the beam selection constraint and thus allows very similar DoAs. Overall, the results in this paper emphasize the necessity of RF switching in order to obtain superior performance with lens arrays, over conventional phased arrays.

In this paper, a new type of architecture for secure wireless key establishment is proposed. A retrodirective array (RDA) that is configured to receive and re-transmit at different frequencies is utilized as a relay node. The RDA is able to respond in “real time,” reducing the required number of time slots to two. More importantly, in this architecture, equivalent reciprocal wireless channels between legitimate keying nodes can be randomly updated within one channel coherence time period, leading to greatly increased key generation rates in slow fading environment. The secrecy performance of this RDA-assisted key generation system is evaluated under several eavesdropping strategies and it is shown that it outperforms previous relay key generation systems.

This paper presents a 3D graphics rendering algorithm for photorealistic ray tracing operating over a network of personal computers. The implementation incorporates partitioning methodologies for both memory and workload to achieve efficient execution on a distributed personal computer, PC, network. Experimental results that compare algorithm efficiency in dual processor machines and TCP/IP networks with respect to execution on a single processor are discussed.