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Reconfigurable intelligent surface (RIS) assisted non-orthogonal multiple access (NOMA) transmission can effectively improve the energy/spectrum efficiency in wireless networks. This paper designs a low-complexity scheme to achieve the balanced tradeoff between the sum-rate and power consumption in a RIS-assisted NOMA system, which can be measured by energy efficiency. To solve the formulated problem effectively, the original non-convex problem is first decomposed into two subproblems, i.e., beamforming optimization and phase shift optimization. Alternating optimization is proposed to solve these two subproblems iteratively. In particular, successive convex approximation (SCA) is utilized to convert the non-convex constraints to convex ones. The provided simulation results demonstrate that the proposed scheme can achieve superior performance on energy efficiency compared to the random phase shifts and orthogonal multiple access (OMA) schemes. [ABSTRACT FROM AUTHOR]

A zero forcing (ZF) assisted single layer beamforming is developed for spatial modulation (SM) and space shift keying (SSK) modulation multiple input multiple output (MIMO) systems, termed as SZF-SM/SZF-SSK, to achieve both transmit beamforming and receive diversity gain in this paper. Specifically, the proposed SZF-SM/SZF-SSK maps part of the bits to spatial domain, simultaneously forming a ZF precoding assisted single layer data both in multiple input single output (MISO) and MIMO systems, that differs greatly from conventional ZF beamforming assisted MIMO systems. With MISO configuration, the ZF precoder of SZF-SM/SZF-SSK converges to the maximum ratio transmission (MRT), achieving only the transmit beamforming gain. With MIMO configuration, SZF-SM/SZF-SSK tranceiver could be further modified along with the MIMO channel to achieve single layer transmission and joint detection, attaining both the transmit beamforming and receive diversity gain in SM-MIMO system. The theoretical analysis and the simulation results of the proposed SZF-SM/SZF-SSK with MISO and MIMO configurations are presented in this paper respectively, which show an attractive performance gain over the conventional SM/SSK. Compared with the conventional ZF beamforming assisted MIMO systems and some other CSI assisted SM-MIMO schemes, the proposed scheme exhibits better performance, especially under highly correlated MIMO channels, rendering a new and practical way to achieve low rank MIMO transmission with good performance and high data rate. [ABSTRACT FROM AUTHOR]

In this paper, we investigate joint retrospective interference alignment (RIA) and caching schemes for multiple-input single-output (MISO) broadcast channels (BC) with delayed channel state information at the transmitter (CSIT). By exploiting the cached content, we propose one sophisticated cache-aided RIA scheme to cancel the interference. Importantly, our scheme takes the number of symbols in a packet into account, as different number of symbols in a packet result in different system configuration, which may have significant impact on the design of the transmission scheme and achievable degrees of freedom (DoF). Furthermore, we present two theorems to quantify the achievable sum DoF of the proposed cached-aided RIA scheme for different system configuration. Moreover, the system configuration of the existing cache-aided RIA scheme with mixed CSIT can be treated as a special case in our paper. And also our scheme can simultaneously support more users than the existing cache-aided RIA scheme with mixed CSIT to invoke zero forcing (ZF) precoding, which limits the number of users simultaneously supported. [ABSTRACT FROM AUTHOR]

Cache-enabled small base stations (SBS) are capable of relieving the heavy burden of the backhaul link and reducing the transmission latency. The hit probability depends on the coverage probability and caching placement probabilities. However, the interference in the small-cell networks may significantly degrade the coverage probability. In this paper, for MIMO small-cell networks consisting of SBS and users, where both of them are equipped with multiple antennas, a joint interference alignment (IA) and probabilistic caching (JIA-ProbC) scheme is proposed. Using tools from stochastic geometry, the $K$ -th order Voronoi cells are constructed to form clusters, where $K$ SBSs cooperatively serve users within each of the $K$ -th order Voronoi cells. Then, the IA scheme for MIMO interference channel (IC) is employed to cancel the intra-cluster interference within each $K$ -th order Voronoi cell. By exploiting the advantage of multiples antennas at users, the IA scheme can simultaneously support more users interference-free than both the zero forcing (ZF) based interference cancellation scheme for MISO systems and SISO systems without interference management, as more interference can be canceled. Furthermore, the coverage probability is analytically approximated by the a closed-form expression. Moreover, the optimal caching placement probability is analytically derived. Numerical Simulation results show that the proposed JIA-ProbC can significantly outperform the existing joint ZF and probabilistic caching (JZF-ProbC) scheme for MISO systems and SISO probabilistic caching (SISO-ProbC) scheme as well as the joint IA and most popular caching (JIA-MPC) caching scheme. [ABSTRACT FROM AUTHOR]

A tradeoff between sum rate and fairness for multiple-input single-output (MISO) broadcast communication employing dirty paper coding or zero-forcing dirty paper coding at physical layer is investigated in this paper. The tradeoff is based on a new design objective termed “tri-stage” approach as well as a new $\ell _1$ -based fairness measure that is much more robust than the well-known Jain's index for comparing fairness levels achieved by various design objectives at a much finer resolution in high SNR regime. The newly proposed tri-stage design also introduces a new concept of statistical power allocation that randomly allocates power to users based on an optimal probability distribution derived from the tradeoff between sum rate and fairness. Simulation results show that the proposed approach can simultaneously achieve a larger sum rate and better fairness than the reputable proportional fairness criterion. A performance upper bound is also given in the paper to show the excellent performance of the proposed approach at moderate and high SNR regimes as well as some potential for further improvement in low SNR regime. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is a passive antenna array composed of a large number of reflecting elements. In a RIS-assisted communication system, it is a challenging task to acquire accurate channel state information (CSI). In this paper, we propose a semi-blind channel estimation method for a RIS-assisted massive multiple-input single-output (MISO) system. Assuming a Gaussian priori on the data symbols, an iterative expectation maximization (EM)-based algorithm is developed to obtain the maximum likelihood (ML) estimate of the cascaded RIS channel. Different from existing pilot-based methods, the proposed semi-blind channel estimation method exploits the data symbols for channel estimation enhancement and only a fraction of full-pilot signaling overhead is required. Simulation results verify that the proposed method achieves significant improvement in the accuracy of the channel estimation while it noticeably reduces the training pilot overhead. [ABSTRACT FROM AUTHOR]

This paper studies a secure multiuser multiple-input single-output (MISO) communication system aided by an intelligent reflecting surface (IRS), where multiple colluding eavesdroppers (EVEs) coexist. We aim to maximize the sum secrecy rate (SSR) via jointly optimizing the beamforming vectors, the artificial noise (AN) and the phase shifts at the IRS subject to the maximum transmit power constraint and unit modulus constraints. To address the non-convex optimization problem, we first propose an alternating optimization (AO) algorithm based on semidefinite relaxation (SDR) and obtain a high-quality sub-optimal solution. In order to reduce the high computational complexity, a low-complexity alternating optimization (LC-AO) algorithm is developed, in which the beamforming vectors, AN and the IRS phase shifts are optimized alternately by the generalized power iteration (GPI) and the Riemannian manifold conjugate gradient (RMCG) algorithm, respectively. Simulation results show the advantages of deploying the IRS in improving the system secrecy performance. [ABSTRACT FROM AUTHOR]

In this paper, we propose a physical layer secure transmission technology based on multi-components for multiple-input single-output (MISO) systems. The scheme mainly realizes physical layer security (PLS) in General Multi-Fractional Fourier Transform (GMFRFT) signal domain, which is different from traditional schemes that rely on the spatial domain. Different GMFRFT components are transmitted by multiple antennas at the transmitter, then the legitimate receiver and the eavesdropper receive the superposition of multiple non-orthogonal components. The resulting mutual interference will reduce the signal-to-interference and noise (SINR) at the eavesdropper, but without affecting the legitimate receiver. Because the legitimate receiver receives the non-contaminated GMFRFT signal due to designing multi-components at the transmitter, while the eavesdropper receives the signal whose constraint relations in the GMFRFT signal domain are destroyed, which will cause the energy loss of the information bearing signal. Furthermore, in order to achieve the maximum secrecy capacity, the selection method of GMFRFT transform order is given to adjust the power allocation among GMFRFT components. Compared with the scheme based on artificial noise (AN), the advantages of our scheme are: 1) our scheme can further reduce the capacity of wiretap channel while not requiring the transmitter to use partial power to transmit meaningless artificial noise signals; 2) our scheme outperforms AN-based schemes when the available spatial degrees of freedom are limited. Simulation results are provided to demonstrate the secrecy performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

This work focuses on the beamforming design for downlink multiple-input single-output (MISO) nonorthogonal multiple access (NOMA) systems. The beamforming vectors are designed by solving a total transmission power minimization (TPM) problem with quality-of-service (QoS) constraints. In order to solve the proposed nonconvex optimization problem, we provide an efficient method using semidefinite relaxation. Moreover, for the first time, we characterize the optimal beamforming in a closed form with quasi-degradation condition, which is proven to achieve the same performance as dirty-paper coding (DPC). For the special case with two users, we further show that the original nonconvex TPM problem can be equivalently transferred into a convex optimization problem and easily solved via standard optimization tools. In addition, the optimal beamforming is also characterized in a closed form and we show that it achieves the same performance as the DPC. In the simulation, we show that our proposed optimal NOMA beamforming outperforms OMA schemes and can even achieve the same performance as DPC. Our solutions dramatically simplifies the problem of beamforming design in the downlink MISO NOMA systems and improve the system performance. [ABSTRACT FROM AUTHOR]

This paper investigates the capacity results of dimmable visible light communications (VLCs) channel under practical range-limited constraints. Upper and lower bounds for both single-input single-output (SISO) and multiple-input single-output (MISO) scenarios which are valid in all signal-to-noise (SNR) region are derived. We reveal that the SISO capacity is a symmetrical function of the dimming target, and is strictly increasing at its left half. Tight MISO upper bounds are obtained by solving non-convex problems, and alternating optimization method is employed with constraint transformations. [ABSTRACT FROM AUTHOR]

This paper reconsiders the design of blind interference alignment (BIA) for $K$-user MISO interference channel in which each receiver is equipped with a reconfigurable antenna of preset $M_k\geq 3$ modes. Beyond the degree of freedom (DoF)-oriented BIA (D-BIA) design proposed by Lu et al., we further take into account the frequency of mode switching within one supersymbol frame. Even though every receiving antenna is reconfigurable with preset multiple modes, from an engineering perspective, it is of practical importance for each receiving antenna to make less number of mode switching in order to gain the benefits such as less switching power consumption and less signal distortion. To this end, we propose in this paper switching-oriented BIA (S-BIA) scheme, which preserves the same degree of freedom (DoF) gain as D-BIA while offering reduced mode switching frequency. Theoretical analysis and simulation results demonstrate that, compared to D-BIA, S-BIA can gain $100/(M-1)$ percent of switching saving when $M_k = M$ is odd for all transmitters. Remarkably, S-BIA offers 50% switching saving for multiuser $3\times 1$ interference channels. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of downlink multiple-input-single-output (MISO) non-orthogonal multiple access (NOMA) aided vehicular communication systems. To prepare the background for MISO NOMA-based vehicular systems, we first derive the exact outage probability (OP), average bit error rate (ABER), and ergodic capacity (EC) expressions for the single-input-single-output (SISO) NOMA-based vehicular systems over independent but not necessarily identically distributed (i.ni.d.) double Nakagami-m fading channels. Furthermore, we propose two transmit antenna selection schemes at multiple-antenna source vehicle for both far user and near user. Based on these antenna selection strategies, we derive the exact expressions for the OP, ABER, and EC, of the MISO NOMA-based vehicular systems over i.ni.d. double Nakagami-m fading channels. The derived ABER expressions for both SISO and MISO NOMA-enabled vehicular systems can be applicable for various modulation schemes. Moreover, to reveal better insights into the diversity orders of SISO and MISO NOMA-enabled vehicular systems, we present the asymptotic OP analysis in the high signal-to-noise ratio (SNR) regime. The numerical and simulation results corroborate our theoretical and analytical findings, and demonstrate the effects of transmit power, power allocation factor, fading severity parameters, and number of antennas, on the system's performance. We further compare the performance of both systems, and show that the multiple antennas can improve the performance of vehicular systems, which can be further improved significantly with the simultaneous improvement in fading severity parameters. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the physical layer security (PLS) for a multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) visible light communication (VLC) system, whose information is intercepted by collusive eavesdroppers. For the case of known eavesdroppers’ locations, a precoding scheme is proposed to maximize the secrecy capacity of the system by suppressing the rate of collusive eavesdroppers. Then we extend the scheme to the case of unknown eavesdroppers’ locations. Specifically, the artificial noise is introduced in the precoding scheme to further suppress the average rate of eavesdroppers. To solve the non-convex optimization problem, we propose an iterative algorithm based on concave-convex procedure. Simulation results illustrate the outperformance of the proposed schemes in guaranteeing the PLS for the MISO NOMA VLC system under the interception of collusive eavesdroppers. [ABSTRACT FROM AUTHOR]

This paper proposes a stochastic-robust constructive interference (CI) precoding scheme for downlink multi-user MISO systems, assuming that channel state information (CSI) at the transmitter side (CSIT) is contaminated by Gaussian-distributed uncertainties. Our objective is to minimize the total transmit power under users’ quality-of-service constraints: formulating CI at each user with high probabilities for a given target signal-to-noise ratio (SINR). We first analyze the probability of CI under imperfect CSIT. A series of approximations are then developed, transforming the intractable stochastic CI constraints into determined convex constraints. The non-convex stochastic-robust CI power minimization (CIPM) problem is then converted into second-order cone programming. We show that we could create tightened or relaxed approximations by changing the parameters, enabling us to find upper-bounds and lower-bounds for the original stochastic CIPM problem. The best parameter values corresponding to the tightest upper and lower bounds are also discussed and obtained. Simulation results show that the proposed methods reasonably approximate the stochastic CIPM problem. Using the given parameter values, it can guarantee the required probability of CI for each user under acceptable channel uncertainties and outperform the existing robust CI precoding in terms of both transmit power and feasibility rate. The small gap between the upper and lower bounds also shows that the proposed method does not cause too much performance loss. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel physical layer strategy to improve the secrecy performance of multiuser multiple-input single-output networks. In this strategy, orthogonal space-time block code (OSTBC) is employed at an A\text{A}-antenna base station and artificial noise (AN) is employed at an A\text{J} -antenna cooperative relay to enhance the security level of the network. Moreover, two opportunistic scheduling schemes, namely selection combining (SC) and scan-and-wait combining (SWC), are leveraged to select one legitimate user for data transmission. To evaluate the secrecy performance of the proposed OSTBC-SC-AN and OSTBC-SWC-AN schemes, we derive new exact closed-form expressions for the secrecy outage probability and the effective secrecy throughput. Using numerical results, we show that the OSTBC-SWC-AN scheme outperforms the OSTBC-SC-AN scheme when the switching threshold is carefully chosen, while the OSTBC-SC-AN scheme is independent of the switching threshold. We also show that increasing A\text{A} at a low switching threshold or decreasing A\rm{A} at a high switching threshold achieves secrecy enhancement for the OSTBC-SWC-AN scheme, while increasing A\rm{A} brings better secrecy performance for the OSTBC-SC-AN scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the power allocation problem for secure secondary transmission in a multiple-input single-output cognitive wiretap system with artificial noise (AN). The secondary transmitter exchanges confidential information with the secondary destination in the presence of an unknown eavesdropper. Since the eavesdropper's channel state information (CSI) is unavailable, we propose an optimal adaptive power allocation scheme, and derive a closed-form expression of the optimal power allocation factor that minimizes the secrecy outage probability (SOP). A suboptimal fixed power allocation scheme is also proposed to reduce the system complexity. Moreover, exact closed-form expressions of SOP under both schemes are derived. Numerical results are provided to corroborate the accuracy of our analytical results and the superiority of the proposed schemes to the benchmarks. [ABSTRACT FROM AUTHOR]

This paper investigates the achievable rate region of the multiple-input single-output (MISO) interference channel aided by intelligent reflecting surfaces (IRSs). We exploit the additional design degree of freedom provided by the coordinated IRSs to enhance the desired signal and suppress interference so as to enlarge the achievable rate region of the interference channel. To this end, we jointly optimize the active transmit beamforming at the transmitters and passive reflective beamforming at the IRSs, subject to the constant modulus constraints of reflective beamforming vectors. To address the non-convex optimization problem, we propose an iterative algorithm to optimize the transmit beamforming via second-order cone program (SOCP) and the reflective beamforming via the semi-definite relaxation (SDR). Numerical results demonstrate that the performance of the IRS-aided interference channel with the proposed algorithm can significantly outperform the conventional interference channel without IRS. [ABSTRACT FROM AUTHOR]

Recently, the intelligent reflecting surface (IRS) has become a promising technology for energy-, and spectrum-efficient communications by reconfiguring the radio environment. In this paper, we consider multiple-input single-output (MISO) transmissions from a multi-antenna access point (AP) to a receiver, assisted by a practical IRS with a power budget constraint. The IRS can work in energy harvesting, and signal reflecting phases. It firstly harvests RF energy from the AP's signal beamforming, and then uses it to sustain its operations in the signal reflecting phase. We aim to characterize the maximum capacity by optimizing the AP's transmit beamforming, the IRS's time allocation in two operational phases, and the IRS's passive beamforming to enhance the information rate. To solve the non-convex maximization problem, we exploit its structural properties, and decompose it into two sub-problems in two phases. The IRS's phase shift optimization in the reflecting phase follows a conventional passive beamforming problem to maximize the received signal power. In the energy harvesting phase, the IRS's time allocation, and the AP's transmit beamforming are jointly optimized using monotonic optimization. Simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been deemed a promising technology to achieve high spectral efficiency. This paper investigates transmit power optimization for a multi-user multiple-input single-output (MISO) NOMA downlink system endowed with energy harvesting and physical layer security. More specifically, the system is designed to satisfy the data-link security requirements of its legitimate users while charging energy harvesting devices. To achieve that goal, we investigate a joint design on beamforming vectors and artificial noise (AN) covariance matrix. Then, an iterative difference-of-two-convex-function (D.C.) algorithm is proposed by applying the successive convex approximation (SCA) approach. To further reduce the computational complexity, a sub-optimal alternating D.C. (ADC) algorithm is devised by decoupling beamforming and mapping the AN to the null space of legitimate users. In the ADC algorithm, optimal null space and beamforming vectors are alternately solved by convex programming. Furthermore, the convergence of the proposed D.C. and ADC algorithms is derived. Extensive simulation results show that the two proposed AN-aided algorithms significantly reduce the transmit power cost over OMA and NOMA scheme without AN, especially when there are more eavesdroppers. [ABSTRACT FROM AUTHOR]

In this paper, we consider a cellular downlink multiple-input-single-output (MISO) nonorthogonal multiple access (NOMA) secure transmission system, where users are grouped as multiple clusters. Each cluster consists of a central user and a cell-edge user. The central user is an entrusted user, and the cell-edge user is a potential eavesdropper. We focus on the secure beamforming and power allocation design optimization problem which maximizes the sum achievable secrecy rate of central users subject to the transmit power constraint at the base station and transmission rate requirements at cell-edge users. The problem is nonconvex because of coupling optimization variables in the considered fractional quadratically constrained quadratic programming. We propose an alternating optimization-based solution and a constrained concave–convex procedure-based solution to the considered problem. Simulation results demonstrate that our proposed NOMA schemes outperform the conventional orthogonal multiple access scheme. [ABSTRACT FROM AUTHOR]

Zero-forcing precoding is a commonly-used multiple-user, multiple-input multiple-output beamforming technique. Applying such precoding, the signal-to-interference-plus-noise ratio (SINR) statistics with outdated channel state information, which involve various projections related to the multi-dimensional channel vectors and precoding vectors, have never been explicitly derived. In this paper, for the multiple-input single-output scenario with uniform power allocation, the distributions of these projections are derived, and then the SINR distribution and the conditional outage probability can be computed using those distributions. [ABSTRACT FROM AUTHOR]

In this work, we consider a secure precoding optimization problem for the artificial noise (AN) scheme in multiple-input single-output (MISO) wiretap channels. In previous researches (Lin et al., 2013), it was proved that the generalized AN scheme which allows some portion of AN signal to be injected to the legitimate receiver's channel is the optimal precoding scheme for MISO wiretap channels. However, the optimality is valid only under some ideal assumptions such as perfect channel estimation and spatially uncorrelated channels. To break through this limitation, in this paper, we propose a novel deep neural network (DNN)-based secure precoding scheme, called the deep AN scheme. To the best of the authors’ knowledge, the deep AN scheme is the first secure precoding scheme which exploits a DNN to jointly design and optimize the precoders for the information signal and the AN signal. From the numerical experiments, it is demonstrated that the proposed deep AN scheme outperforms the generalized AN scheme under various practical wireless environments. [ABSTRACT FROM AUTHOR]

In this paper, we study the secrecy performance of a $K$ -user multi-input single-output (MISO) broadcast channel with random beamforming (RB), where the transmitter is equipped with $N$ antennas, and the eavesdropper has $N_e$ antennas. We first propose a signal-splitting random beamforming (SSRB) scheme for a single-user MISO wiretap channel, and then improve the SSRB scheme with power-minimizing (PM), which is called a PM-SSRB scheme. To improve the spectral efficiency of a multiuser network, we combine PM with non-orthogonal multiple access (NOMA), and propose a hybrid NOMA (H-NOMA) scheme and a signal-splitting NOMA (SS-NOMA) scheme for the $K$ -user MISO wiretap channel, respectively. The sum ergodic secrecy rate of the $K$ -user scenario is analyzed comprehensively, and a closed-form expression for the lower bound on the ergodic secrecy rate is also derived for the single-user case. Simulation results show that, compared with the traditional hybrid artificial fast-fading scheme (AFF) and artificial noise (AN) scheme, the proposed SSRB scheme and PM-SSRB scheme perform much better in terms of the ergodic secrecy rate in all power regimes. More importantly, when the eavesdropper has more antennas than the transmitter, our schemes always outperform the AFF and AN schemes. The PM-SSRB scheme is also shown to be superior to the secret-key AFF scheme. For the multiuser case, the SS-NOMA scheme can achieve higher ergodic secrecy rate than the H-NOMA scheme. [ABSTRACT FROM AUTHOR]

We propose a semi-closed-form solution to the problem of computing the capacity and optimal signaling for a Gaussian MIMO channel under a joint sum power constraint (SPC) and per-antenna power constraint (PAPC). Existing efficient solutions to this fundamental problem are only applicable to some special cases: multiple-input single-output (MISO) systems, or full column rank MIMO channels with sufficiently high transmit power, or full-rank optimal signaling. For the general case, we present an efficient numerical method to solve the considered problem which does not make any assumptions on the rank of the channel matrix or the maximum transmit power. To achieve this, the considered problem is transformed into an equivalent minimax problem. We then exploit the special structure of the minimax problem to derive a closed-form solution based on a concave-convex procedure (CCP)-like algorithm. Extensive simulation results show that our proposed algorithm outperforms the existing solutions in terms of complexity and generality. [ABSTRACT FROM AUTHOR]

Recently, intelligent reflecting surface (IRS) has received considerable attention and is seen as a promising technology for 6 G communications. This correspondence studies the IRS-aided multiuser multi-input single-output (MISO) downlink multicast beamforming. Depart from the conventional (rank-one) beamforming, the Alamouti-aided rank-two beamforming is employed at the base station (BS), and a joint optimization of the rank-two beamforming and the IRS phase shift is formulated to minimize the transmit power with guaranteed signal-to-noise ratio at the users. This power minimization problem is nonconvex. To tackle it, we custom-derive a proximal distance algorithm (PDA) with generalized power method (GPM) to iteratively optimize the beamformer and the phase shift. Both PDA and GPM can be performed very efficiently than the semidefinite relaxation method. Simulation results demonstrate that the rank-two beamforming attains much lower porwer than the rank-one beamforming with reduced computation complexity. [ABSTRACT FROM AUTHOR]

Mobile Edge Computing (MEC) is a promising technology in the next generation network, which provides computing services for user equipments (UEs) to reduce the task delay and prolong the usage time of UEs. To address the deficiency of poor channel quality caused by multipath and blockages in traditional MEC networks, a multiple input single output (MISO) UAV-assisted MEC network is studied. A system energy consumption minimization problem is formulated by jointly optimizing the the UAV’s beamforming vectors, the UAV’s central processing unit (CPU) frequency, the UAV’s trajectory, the UEs’ transmission power and the UEs’ CPU frequency subject to the constraints on the task, the UAV’s trajectory, and the UEs’ computation tasks. A three-stage iterative algorithm is proposed to solve the challenging non-convex problem. The closed-form expressions for the optimal UAV CPU frequency and the transmission power of UEs are derived. Simulation results show that the proposed algorithm is superior to the benchmark schemes in terms of energy consumption, and the convergence performance is guaranteed. [ABSTRACT FROM AUTHOR]

This article studies the beamforming optimization for intelligent reflecting surface (IRS) assisted multiple-input single-output (MISO) wireless communication system. We establish a deep transfer learning (DTL)-based framework to learn how to optimize the phase shifts at the IRS side. Based on it, we also design a loss function to implement unsupervised training without a large number of labeled data samples. Finally, we extend the optimization problem to discrete phase shift constraint to solve the hardware limitation. The simulation verifies that the proposed DTL-based approach can achieve similar performance compared with upper bound while substantially reducing the computational complexity. [ABSTRACT FROM AUTHOR]

In practical multi-antenna systems, the design of precoding and power control is not straightforward even for multi-input single-output (MISO) systems because of the distortion caused by nonlinear power amplifiers. Through analysis of the signal-to-interference-plus-noise ratio (SINR), we found that the equal gain transmission scheme can achieve the maximum SINR of a nonlinear MISO system only at the point of local optimal transmit power. Then we derived an approximated optimal transmit power for the nonlinear MISO system. To maximize the SINR in all transmit power region, we propose a precoding and power control algorithm for a MISO system with nonlinear power amplifiers under power constraint. By simulation, we show that the proposed scheme can achieve the local optimum SINR, and outperform other baseline precoding techniques. [ABSTRACT FROM AUTHOR]

Although there have been extensive studies on transmit beamforming in multi-input single-output (MISO) multicell networks, achieving optimal sum-rate with limited channel state information (CSI) is still a challenge even with a single user per cell. A novel cooperative downlink multicell MISO beamforming scheme is proposed with highly limited information exchange among the base stations (BSs) to maximize the sum-rate. In the proposed scheme, each BS can design its beamforming vector with only local CSI based on limited information exchange on CSI. Unlike previous studies, the proposed beamforming design is non-iterative and does not require any vector or matrix feedback but requires only quantized scalar information. The proposed scheme closely achieves the optimal sum-rate bound in almost all signal-to-noise ratio regime based on non-iterative optimization with lower amount of information exchange than existing schemes, which is justified by numerical simulations. [ABSTRACT FROM AUTHOR]

We study the cooperative secure transmissions in (multiple-input signal-output) MISO vehicular relay networks where the infrastructure node with multiple antennas sends two confidential messages to two legitimate vehicles with only one antenna, respectively. By exploiting the signal superposition and cooperative jamming techniques, the legitimate vehicle near the infrastructure node directly decodes its own messages and is also responsible for relaying messages for the other legitimate vehicle who is distant from the infrastructure node. To combat eavesdropping threat from a malicious node for these two legitimate vehicles, we first provide comprehensive analysis of the secrecy performances and then design optimal secure transmission schemes for both vehicles. In particular, we first derive the closed-form expressions of the transmission outage probability (TOP) and secrecy outage probability (SOP), which offer mathematic tools for separate control with respect to security and system throughput. Following these results, we develop the optimized transmission schemes for two typical secure communication scenarios. One scenario is to maximally suppress the message leak while maintaining satisfied transmission rate. To achieve this goal, we derive the optimal power allocation strategy to minimize the SOP under the upper bounded TOP requirement. The other scenario is to improve the average secrecy rate with system throughput taken into consideration. Corresponding, we propose a prioritized and an explicitly parameterized power allocation schemes, which address the mutual impact across legitimate vehicles transmissions by different approaches. Numerical results are presented to validate the derived theory analytical results and show the performance superiority of the proposed schemes in terms of the average secrecy rate and the SOP performance. [ABSTRACT FROM AUTHOR]