This paper investigates uplink transmission rate enhancement in space-air-ground integrated networks (SAGIN) by jointly designing precoders for a multi-antenna ground user and an unmanned aerial vehicle (UAV). Assuming a stationary relative position between the UAV and the satellite, we propose two joint precoding designs to optimize the uplink transmission rate while considering the practical finite signaling. We introduce an alternating iteration optimization approach (AIOA) when accurate channel state information (CSI) of the Rician link from the ground user and UAV is available. Additionally, we account for the statistical CSI induced by multi-path effects in various terrestrial environments, and derive a new closed-form expression for the uplink transmission rate. Building on this, a convex optimization framework is formulated by vectoring the optimization matrix and introducing auxiliary variables to tackle the non-convexity of the problem. Then, the AIOA is further adopted to jointly optimize the ground user and UAV precoders, significantly reducing computational complexity. Simulation results confirm the efficiency of the proposed AIOAs improving uplink transmission rates in SAGIN.

In this work, we focus on developing near-field beamforming schemes for covert wireless communications to maximize the communication quality while ensuring communication covertness, where three different antenna architectures are considered. Specifically, we first analyze the monotonicities of the throughput and the minimum detection error probability with respect to the signal-to-noise ratio (SNR) at a legitimate receiver and a warden. Then, the formulated optimization problem is transformed into a semi-definite programming (SDP) problem via vectorizing the matrix. Lastly, a maximum signal-to-leakage ratio (MSLR) scheme with a low complexity is proposed. Our results indicate that the proposed near-field beamforming schemes facilitate covert communication in both the distance and angle dimensions. The two hybrid antenna architectures lead to a slight performance loss, but significantly reduce the circuit budget. Meanwhile, the low-complexity algorithm greatly reduces the algorithm complexity, although it exhibits a noticeable disadvantage in its covert transmission performance. Furthermore, our results indicate that the designed near-field beamforming strategies are more beneficial in meeting the covertness constraints, highlighting a feasibility of covert communications in the near-field region.

As an emerging technology for wireless communication, the intelligent reconfigurable surface (IRS) is made up of numerous low-cost passive elements with reconfigurable parameters, which can reflect signals with a certain phase shift and build a programmable communication environment. To reduce the high hardware cost and energy consumption in spatial modulation (SM), an IRS-aided hybrid secure SM (SSM) system with a hybrid precoder is proposed in this paper, where an optimization problem is formulated to maximize the secrecy rate (SR) by jointly optimizing the beamforming at IRS and the hybrid precoding at transmitter. For the IRS beamforming, an alternating direction method of multipliers (IRS-ADMM) scheme is first proposed. To achieve a higher SR, an IRS beamforming scheme via semidefinite relaxation (IRS-SDR) is put forward. To reduce the high complexity of IRS-SDR, we design a block coordinate ascend-based IRS beamforming scheme (IRS-BCA) with a closed-form solution. As for the hybrid precoding, two methods, called a successive convex approximation method based on the approximate secrecy rate (ASR-SCA) and a gradient ascend method based on cut-off rate (COR-GA), are presented. Simulation results show that the proposed IRS-ADMM and IRS-SDR harvest substantial SR performance gains over IRS-BCA. In comparison to the IRS-ADMM and IRS-SDR, the proposed IRS-BCA is of the lowest complexity at the cost of performance loss. Regarding hybrid precoding, the proposed ASR-SCA outperforms COR-GA in the high transmit power region. According to the complexity and SR performance of six combination methods including each IRS beamforming method and each hybrid precoding method, we selected three combinations: IRS-BCA plus ASR-SCA, IRS-ADMM plus ASR-SCA and IRS-SDR plus COR-GA. Moreover, it is showed that the SR performance achieved by the three combination methods is significantly higher than those of IRS with random beamforming and without IRS.

The use of a reconfigurable intelligent surface (RIS) in the enhancement of the rate performance is considered to involve the limitation of the RIS being a passive reflector. To address this issue, we propose a RIS-aided amplify-and-forward (AF) relay network in this paper. By jointly optimizing the beamforming matrix at AF relay and the phase-shift matrices at RIS, two schemes are put forward to address a maximizing signal-to-noise ratio (SNR) problem. First, aiming at achieving a high rate, a high-performance alternating optimization (AO) method based on Charnes–Cooper transformation and semidefinite programming (CCT-SDP) is proposed, where the optimization problem is decomposed into three subproblems solved using CCT-SDP, and rank-one solutions can be recovered using Gaussian randomization. However, the optimization variables in the CCT-SDP method are matrices, leading to extremely high complexity. To reduce the complexity, a low-complexity AO scheme based on Dinkelbachs transformation and successive convex approximation (DT-SCA) is proposed, where the variables are represented in vector form, and the three decoupling subproblems are solved using DT-SCA. Simulation results verify that compared to three benchmarks (i.e., a RIS-assisted AF relay network with random phase, an AF relay network without RIS, and a RIS-aided network without AF relay), the proposed CCT-SDP and DT-SCA schemes can harvest better rate performance. Furthermore, it is revealed that the rate of the low-complexity DT-SCA method is close to that of the CCT-SDP method.

This paper studies a convincingly secure transmission framework under an allowable outage probability for practical finite-alphabet inputs, where a full-duplex receiver (Bob) is taken into account to emit the artificial noise for deteriorating the eavesdropper’s decoding performance. We develop a secure-reliable mechanism to take the place of prior secrecy rate (SR) maximization strategy, where a closed form expression is invoked for substituting the non-closed SR expression upon exploiting the multi-exponential decay fitting approach. Hence, the intractable expectation operation over a large number of noise samples is circumvented. Moreover, a pair of critical probabilities of the reliable transmission and secure outage are first analyzed, and then a low-complexity optimization scheme is formulated. Apart from designing the transmission scheme for classically secure networks consisting of a transmitter, Bob and an eavesdropper, we further carry out an investigation on conceiving a secure-reliable strategy against multiple Eves for improving the system’s extensibility. To this end, analytical expressions of both the reliability outage and secrecy outage probabilities for multiple-Eve scenarios are also derived. Furthermore, a pragmatic iterative solution is conceived for addressing the corresponding max-min optimization problem. Finally, the simulation results validate the significance of our considered secure-reliable transmission in terms of the average SR performance attained.

Because of discrepant deteriorations of the intended receiver and the unintended receiver, artificial noise (AN) can be invoked in conjunction with the precoder to wireless transmissions for enhancing the secrecy rate (SR) performance as long as we elaborately frame them. This paper studies a secure transmission strategy by jointly designing the precoder and AN beamformer at the relay network, where a passive eavesdropper and finite-alphabet inputs are taken into account. We propose a pair of solutions for low-order modulation and high-order modulation, respectively. To solve the first optimization problem, we propose a low-complexity algorithm with the aid of the invoked cut-off rate. Interestingly, we find that the phase of an optimum precoder for maximizing the SR has a correlation to both the channels spanning from the transmitter to the relays and spanning from the relays to the legitimate receiver. Furthermore, we reveal that the AN beamformer vector has at most one non-zero component, which only locates at the position corresponding to the minimum element of the channel between the relays and the intended receiver. According to these findings, the SR maximization problem over the two vectors is simplified as one only related to a pair of scalars. As for the high-order modulation, a new solution is further proposed for circumventing the predicament that the computational complexity exponentially increases as the size of the adopted modulation increases, where we not only eliminate two-layer summation over the legitimate symbols but also conceive a concave maximization SR problem. Finally, simulation results demonstrate the efficiency of the proposed algorithms in terms of the SR performance.

Technically, the security performance of generalized spatial modulation (GenSM) networks can be enhanced by dynamically adjusting the precoder allocated to the legitimate signal as communication channel varies. For this purpose, our paper proposes a secure transmission strategy upon designing both digital and analog precoders for hybrid GenSM systems, where an eavesdropper is taken into account. The concept of the hybrid GenSM system has arose to improve the spatial multiplexing (SMX) gain for remedying the shortcoming of the limited number of radio frequency chains in traditional GenSM systems. However, this may lead to a great deal of security degradation since the SMX gain of the unintended receiver will be also improved. To this end, we develop a secrecy enhancement scheme by devising both analog and digital precoders for hybrid GenSM networks. Specifically, we derive an efficiently closed-form alternative to the original secrecy rate (SR) expression for reducing the excessive computational complexity of the joint optimization problem over the hybrid precoder. Then, by using this alternative as our cost function, an iterative algorithm is proposed. In particular, we elaborately conceive a pair of concave maximization problems in order to optimize the digital and analog precoders, respectively. Our proposed strategy not only utilizes semi-positive definite relaxing technique over the analog precoder but also invokes a lower bound of the alternative to further simplify the optimization over the vectored digital precoder. Subsequently, both the convergence and computational complexity of the proposed alternating iteration algorithm are analyzed. Compared to existing designs, our proposed strategy strikes a compelling role in balancing the SR performance and complexity. Finally, our simulation results confirm the efficiency of the proposed algorithm in terms of the SR performance achieved.

Spatial modulation (SM) is a particularly important form of multiple-input multiple-output (MIMO), which uses both modulation symbols and antenna indices to carry information. In this paper, to avoid the high cost and circuit complexity of SM, we consider the hybrid SM system with a hybrid precoding transmitter architecture, combining a digital precoder and an analog precoder. In such a system, we carried out secure hybrid precoding and transmit antenna subarray selection (TASS) methods. Two hybrid precoding methods, called maximizing approximate secrecy rate (SR) via gradient ascent (Max-ASR-GA) and maximizing approximate SR via alternating direction method of multipliers (Max-ASR-ADMM), are proposed to improve the SR performance. As for TASS, a high-performance method of maximizing the approximate SR (Max-ASR) is first presented. To reduce its high complexity, two low-complexity TASS methods, namely maximizing eigenvalue (Max-EV) and maximizing product of signal-to-interference-plus-noise ratio and artificial noise-to-signal-plus-noise ratio (Max-P-SINR-ANSNR), are proposed. Simulation results demonstrate that the proposed Max-ASR-GA and Max-ASR-ADMM hybrid precoders harvest substantial SR performance gains over existing method. For TASS, the proposed three methods Max-ASR, Max-EV, and Max-P-SINR-ANSNR perform better than existing leakage method. Particularly, the proposed Max-EV and Max-P-SINR-ANSNR are of low-complexity at the expense of a little performance loss compared with Max-ASR.

The security of spatial modulation (SM) aided networks can always be improved by reducing the desired link's power at the cost of degrading its bit error ratio performance and assuming the power consumed to artificial noise (AN) projection (ANP). We formulate the joint optimization problem of maximizing the secrecy rate (Max-SR) over the transmit antenna selection and ANP in the context of secure SM-aided networks. In order to solve this problem, we provide a pair of solutions, namely joint and separate solutions. Specifically, an accurate approximation of the SR is used for reducing the computational complexity, and the optimal AN covariance matrix (ANCM) is found by convex optimization for any given active antenna group (AAG). Then, given a large set of AAGs, simulated annealing mechanism is invoked for optimizing the choice of AAG, where the corresponding ANCM is recomputed by this optimization method as well when the AAG changes. To further reduce the complexity of the above-mentioned joint optimization, a low-complexity two-stage separate optimization method is also proposed. Moreover, when the number of transmit antennas tends to infinity, the Max-SR problem becomes equivalent to that of maximizing the ratio of the desired user's signal-to-interference-plus-noise ratio to the eavesdropper's. Thus, our original problem reduces to a fractional programming problem and a significant computational complexity reduction can be achieved. Finally, our simulation results verify the efficiency of the proposed methods in terms of the SR performance attained.