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Mobile edge computing (MEC) and millimeter wave (mmWave) communications are capable of significantly reducing the network's delay and enhancing its capacity. In this paper we investigate a mmWave and device-to-device (D2D) assisted MEC system, in which user A carries out some computational tasks and shares the results with user B with the aid of a base station (BS). We assume partial offloading model and the task can be partitioned into two portions: the first part is computed locally at user A, while the second part is transmitted to the BS and computed by the MEC server. The computational results are then sent to user B through a D2D link and via the link from the BS to user B, respectively. To support computation offloading, both the users and the BS are equipped with multiple antennas and employ analog and digital (A/D) hybrid beamforming. Moreover, we propose a novel two-timescale joint hybrid beamforming and task allocation algorithm to reduce the system latency whilst cut down the required signaling overhead. Specifically, the high-dimensional analog beamforming matrices are updated in a frame-based manner based on the channel state information (CSI) samples, where each frame consists of a number of time slots, while the low-dimensional digital beamforming matrices and the offloading ratio are optimized more frequently relied on the low-dimensional effective channel matrices in each time slot. A stochastic successive convex approximation (SSCA) based algorithm is developed to design the long-term analog beamforming matrices. As for the short-term variables, the digital beamforming matrices are optimized relying on the innovative penalty-concave convex procedure (penalty-CCCP) for handling the mmWave non-linear transmit power constraint, and the offloading ratio can be obtained via the derived closed-form solution. Simulation results verify the effectiveness of the proposed algorithm by comparing the benchmarks. [ABSTRACT FROM AUTHOR]

Channel estimation is a challenging issue for millimeter wave (mmWave) and massive multiple-input multiple-output (MIMO) in the future sixth generation (6G) wireless systems, where the conventional estimation schemes may fail to track the fast varying channels, especially in high-speed mobile scenarios. In this paper, a novel tensor-based uplink channel estimation scheme is proposed for multi-user MIMO (MU-MIMO) systems over time-varying channels. In the proposed scheme, a low-overhead pilot transmission scheme is designed to track the varying channel. The received uplink signal at the base station (BS) is formulated as a third-order tensor which admits a CANDECOMP/PARAFAC (CP) model. The CP decomposition issue is then solved using blind matrix decomposition, in which the special structures of signals in the time dimension and the matrix subspace are utilized. By exploiting low-rank structure of the signal tensor, the channel parameters (angles of arrival/departure, path gains, and Doppler shifts) are estimated from the factor matrices. Moreover, the proposed scheme is theoretically analyzed and it is guaranteed with low pilot overhead. Simulation results verify that the proposed scheme can outperform the compressed sensing (CS) based scheme and the iteration-based scheme in terms of accuracy and stability. The uniqueness of the proposed scheme is also verified in our simulation. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a downlink non-orthogonal multiple access (NOMA) transmission scheme for hybrid millimeter-wave (mmWave) system and study its user grouping and power allocation. In order to maximize the weighted sum-rate (WSR) of the system, we first propose a user grouping algorithm based on min-sum message passing (MSMP) strategy under the limited number of radio frequency (RF) chains. Then, with the zero-forcing (ZF) digital precoding, we propose a power allocation scheme for multiple-RF-chain NOMA (MRFC-NOMA) structure based on a non-convex transformation method, and design a low-complexity algorithm. The simulation results show that the proposed joint user grouping and power allocation method with lower complexity can achieve better WSR performance than the traditional schemes. [ABSTRACT FROM AUTHOR]

As millimeter wave (mmWave) technology becomes more integrated into today's communication infrastructure, its application to mobile scenarios has attracted considerable interests. In particular, mmWave technology is one of the leading candidates in Vehicle-to-Everything (V2X) community to address the ever-rising data exchange demand from vehicles. However, the inherent directionality of the technology poses challenges to peer discovery and transmission scheduling in typical V2X scenarios, causing significant loss of network capacity. To mitigate this issue, we propose a novel sub-6 GHz V2X-assisted synchronous mmWave communication scheduler in this paper. The sub-6 GHz channel serves as control channel for mmWave scheduling. The scheduler carefully considers data importance and freshness in determining communication schedule, such that network utility across mmWave links is maximized. We formulate the scheduling problem into an integer linear programming (ILP) problem. However, ILP problem is NP-hard and has exponential computational complexity for the worst cases. We then develop a scheduling algorithm, maximum weight matching based iterative algorithm (MWMIA), that operates in polynomial time with performance guarantees for the NP-hard ILP, by leveraging structural properties of link conflicts. Comparative simulation studies verify the effectiveness of our scheduler against other solutions. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) frequency spectrum offers orders of magnitude greater spectrum to mitigate the severe spectrum shortage in conventional cellular bands. To overcome the high propagation loss in the mmWave band, massive multiple-input and multiple-output (MIMO) can be adopted at both transmitter and receiver to provide large beamforming gains. At the same time, hybrid architecture is applied to reduce the huge power consumption caused by devices operating at radio frequency (RF). However, because of the hybrid architecture and large number of antennas, it is hard to obtain the channel state information (CSI) which is crucial for obtaining desirable beamforming gains. Off-grid error and sparsity pattern (SP) estimation error are two main limiting factors of the performance of most existing compressive sensing (CS) based channel estimation (CE) algorithms. Off-grid error presents when the true angle does not lie on the discretized angle grid of mmWave channel in the spatial domain. In this paper, we first propose a fast Bayesian matching pursuit method with ‘virtual sparsity’ to improve the accuracy of SP estimation and name it as the improved Bayesian matching pursuit (IBMP). Then an enhanced algorithm, named off-grid IBMP (OG-IBMP), is developed to mitigate the off-grid problem, followed by a theoretical analysis of OG-IBMP. This method iteratively updates the selected grid points and updates the corresponding parameters based on the maximum a posteriori (MAP) criterion. Numerical simulations are performed to validate our theoretical analysis and evaluate the performance of the proposed method. Compared to other existing methods, the results show that our proposed OG-IBMP algorithm greatly reduces the off-grid error and significantly enhances the accuracy of the SP estimation with low computational complexity. [ABSTRACT FROM AUTHOR]

Millimeter-wave rotary-wing (RW) unmanned aerial vehicle (UAV) air-to-ground (A2G) links face unpredictable Doppler effect arising from the inevitable wobbling of RW UAV. Moreover, the time-varying channel characteristics during transmission lead to inaccurate channel estimation, which in turn results in the deteriorated bit error probability performance of the UAV A2G link. This paper studies the impact of mechanical wobbling on the Doppler effect of the millimeter-wave wireless channel between a hovering RW UAV and a ground node. Our contributions of this paper lie in: i) modeling the wobbling process of a hovering RW UAV; ii) developing an analytical model to derive the temporal autocorrelation function (ACF) for the millimeter-wave RW UAV A2G link in a closed-form expression; and iii) investigating how RW UAV wobbling impacts the Doppler effect on the millimeter-wave RW UAV A2G link. Numerical results show that different RW UAV wobbling patterns impact the amplitude and the frequency of ACF oscillation in the millimeter-wave RW UAV A2G link. For UAV wobbling, the temporal ACF decreases quickly and the impact of the Doppler effect is significant on the millimeter-wave A2G link. [ABSTRACT FROM AUTHOR]

Most of the existing works in millimeter wave (mmWave) and non-orthogonal multiple access (NOMA) communications (mmWave NOMA) employs phased array (PA) antennas which yield only angle beamspace without range dependent, range-interference suppression and “dot-shaped” array resolution. In this paper, we propose a collocated transmitter (Tx) - receiver (Rx) mmWave NOMA system where frequency diverse array (FDA) antennas are utilized. FDA employs small frequency increments across the element indices which yields angle-range dependent beamspace. Herein, an equivalent radiate beamspace is designed to serve the users. Further, to ensure user equity, we formulate objective function to max-min achievable sum rate subject to power allocation and BS equivalent FDA transmit beamspace along the users. Since the problem is not convex, a boundary-compressed Bat meta-heuristic optimization algorithm is devised to provide a sub-optimal solution by optimizing the frequency increments to synthesis the BS beamspace along the users. The achievable secrecy rate, cost efficiency (CE), economic efficiency (ECE), and secrecy energy efficiency (SEE) are derived for the users. Both theoretical analysis and simulation results indicate that the proposed scheme would constitute an excellent nominee for 5G mmWave NOMA communication applications. [ABSTRACT FROM AUTHOR]

To exploit richer spectrum resources for even better service quality, millimeter wave (mmWave) communication has been considered for high-speed railway (HSR) communication systems. In this paper, we focus on scheduling as many flows as possible while satisfying their QoS requirements. Due to interference, eavesdropping, or other problems, some flows may not be directly transmitted from the track-side BS. In this paper, we propose an UAV-assisted scheduling scheme which utilizes a UAV to serve as relay for such flows. The proposed scheme also utilize two mmWave bands, one for the BS links and the other for the UAV links. The proposed algorithm aims to maximize the number of flows with their QoS requirements satisfied. Simulations demonstrate that the proposed scheme achieves a superior performance on the number of completed flows and the system throughput over two baseline schemes. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmW) is being deployed in hotspot scenarios for providing high bandwidths. However, the coverage of mmW cell is limited due to the rapid attenuation during the propagation and sensitivity to blockage by obstacles. In this paper, we propose a novel dynamic programming approach for automated dimensioning and appropriate placement of mmW small cells (SCs) in dense urban under the constraints of coverage and budget. Being cognizant of the blockage by city buildings, a fast search algorithm based on vector is introduced to enable most line-of-sight (LOS) communication links between base stations (BSs) and mobile stations (MSs). The analysis of time complexity is also derived in closed forms. The evaluation of our approach was carried out in both hypothetic and realistic scenarios. Results show that the studied model is effective for a real large-scaled network and 4 or 5 times faster than the conventional ones based on grid-map. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future wireless communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary ray-based channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including inter-path and intra-path are developed and illustrated in detail. The inter-path parameters are calculated in a deterministic way based on the given geometric information. The parameters of intra-path rays are generated in a stochastic way based on the statistical properties, which can be obtained in advance by applying a Gaussian mixture model (GMM) on the massive ray tracing (RT) data of different typical scenarios. Meanwhile, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. To speed up the RT algorithm, the 3D propagation scenario is reconstructed based on the user-defined digital map. Moreover, the theoretical statistical properties of the proposed channel model, i.e., power delay profile (PDP), autocorrelation function (ACF), Doppler power spectrum density (DPSD), cumulative distribution function (CDF), and level crossing rate (LCR) are derived. Finally, a typical U2V channel under urban scenario at 28 GHz is generated and validated. Simulation results demonstrate that the PDP and DPSD of the proposed channel model are accorded well with the theoretical ones, and the ACF, CDF, and LCR are consistent with the measured ones as well. [ABSTRACT FROM AUTHOR]

Cognitive radio networks (CRNs) and millimeter wave (mmWave) communications are two major technologies to enhance the spectrum efficiency (SE). Considering that the SE improvement in the CRNs is limited due to the interference temperature imposed on the primary user (PU), and the severe path loss and high directivity in mmWave communications make it vulnerable to blockage events, we introduce an intelligent reflecting surface (IRS) into mmWave CRNs. Due to the estimation mismatch and the passivity of Eavesdroppers (Eves), perfect channel state information (CSI) of wiretap links is challenging to obtain, which promotes our research on robust secure beamforming (BF) design in the IRS-assisted mmWave CRNs. This paper considers the collaborate scenario of Eves, which allows us to investigate the BF design in the harsh eavesdropping environment. Specifically, by using a uniform linear array (ULA) at the cognitive base station (CBS) and a uniform planar array (UPA) at the IRS, and supposing that imperfect CSIs of angle-of-departures for wiretap links are known, we formulate a constrained problem to maximize the worst-case achievable secrecy rate (ASR) of the secondary user (SU) by jointly designing the transmit BF at the CBS and reflect BF at the IRS. To solve the non-convex problem with coupled variables, an efficient alternating optimization algorithm is proposed. As for the transmit BF at the CBS, we propose a heuristic robust transmit BF algorithm to attain the BF vectors analytically. As for the reflect BF at the IRS, by means of an auxiliary variable, we transform the non-convex problem into a semi-definite programming problem with rank-1 constraint, which is handled with the help of an iterative penalty function, and then obtain the optimal reflect BF through CVX. Finally, simulation results indicate that the ASR performance of our proposed algorithm has a small gap with that of the optimal solution with perfect CSI compared with the other benchmarks. [ABSTRACT FROM AUTHOR]

In this article, we study the problem of user association, i.e., determining which base station (BS) a user should associate with, in a dense millimeter wave (mmWave) network. In our system model, in each time slot, a user arrives with some probability in a region with a relatively small geographical area served by a dense mmWave network. Our goal is to devise an association policy under which, in each time slot in which a user arrives, it is assigned to exactly one BS so as to minimize the weighted average amount of time that users spend in the system. The above problem is a restless multi-armed bandit problem and is provably hard to solve. We prove that the problem is Whittle indexable, and based on this result, propose an association policy under which an arriving user is associated with the BS having the smallest Whittle index. Using simulations, we show that our proposed policy outperforms several user association policies proposed in prior work. [ABSTRACT FROM AUTHOR]

The terahertz (THz) waves with enormous bandwidth can be used along with the existing sub-6GHz and millimeter wave (mmWave) bands to achieve the ever evolving ecosystem of applications that need to be supported by the modern wireless networks. This paper investigates a user-centric dynamic base station (BS) clustering design for a hybrid network where THz, mmWave, and sub-6GHz BSs coexist. Invoking the proposed clustering model, the BS cooperation within each band is made possible by considering long term channel variations and all the surrounding BSs within a cluster with tunable size. A typical user is associated with the best BS cluster, from either a sub-6GHz, mmWave or THz tier based on the maximum signal-to-interference-plus-noise-ratio (SINR) criterion or the maximum rate criterion. Using tools from stochastic geometry, we assess the performance of the proposed user-centric hybrid system in terms of SINR and rate coverage performances, while accounting for: band specific propagation models, directional beamfroming, and BSs random locations. The accuracy of the analytical results is validated with Monte-Carlo simulations. The obtained results recognize a clear coverage/rate trade-off where a high fraction of THz BSs improves the rate significantly but may degrade the coverage performance. Thus, with carefully planned networks, enabling user-centric BS cooperation for hybrid wireless systems can achieve ultra-high rates while maintaining sufficient coverage in sixth-generation (6G) networks. [ABSTRACT FROM AUTHOR]

We consider a reflection pattern (RP) designfor reconfigurable intelligent surface (RIS)-assisted vehicle-to-vehicle (V2V) communication systems. Fast-moving-vehicle environments necessitate developing more intuitive RP alignment technique that aligns a predefined codeword to the dominant channel directions. To support a fast RP alignment in RIS-assisted V2V systems, we provide a design guideline of the RP codebook by considering passive reflecting elements at the RIS. We analyze distributions of the incident and reflection channels by taking the street geometry in V2V networks into consideration. By using the statistical information on the difference in spatial frequencies between the incident and reflection channels, we define a set of ideal RPs that are likely to maximize a reflection beamforming gain. The RP codebook is constructed by designing a set of reflecting codewords that can generate actual RPs close to predefined ideal RPs. Numerical results verify that the proposed RP codebook provides a higher link gain than previously reported codebooks. [ABSTRACT FROM AUTHOR]

In this article, to improve the achievable sum-rate of the multi-user millimeter wave (mmWave) communication in densely blocked areas, we design a multi-route multi-hop (MRMH) cascaded intelligent reflecting surface (IRS)-aided system. In our designed system, we aim to maximize the achievable sum-rate for the multiple users by jointly optimizing the phase shifts (PSs) at the multiple IRSs and the active beamforming vector (ABV) at the base station (BS). To achieve this target, we formulate an optimization problem. However, it is non-convex and difficult to be solved. By considering the sparse scattering and near-orthogonality characteristics of the mmWave channels, we divide the optimization problem into multiple tractable sub-problems and obtain a near-optimal solution. The simulation results prove that the proposed scheme has better performance than the existing schemes. Furthermore, we prove the effectiveness of the multi-hop IRS-aided system by comparing the single-hop IRS-aided system. [ABSTRACT FROM AUTHOR]

This paper considers the hybrid precoder design in millimeter wave (mmWave) multi-input multi-output (MIMO) systems with low-resolution analog phase shifters. Aiming at reducing the complexities of the near-optimal algorithms, we propose a low-complexity multi-user hybrid precoding scheme based on tree-coding-aided adaptive-cross-entroy (TC-ACE) algorithm. By defining some discrete variables for the analog precoders and combiners, the problem of hybrid precoding is transformed into a cross-entroy (CE) optimization problem, which can be solved by iteratively updating the probability distributions of the predefined discrete variables. In order to derive the closed-form expression of the probability distributions, tree-coding is used to encode each entry of the analog precoders and combiners with a binary number. Through iterations, optimal analog precoders and combiners will be obtained when its probabilities are sufficiently high. Simulation results show that when the number of users exceeds a certain value, the proposed scheme outperforms the alternating minimization algorithm and coordinate descent method in terms of both the sum-rate and complexity. [ABSTRACT FROM AUTHOR]

In this paper, we study non-orthogonal multiple access (NOMA) user scheduling and resource allocation problem for a generic downlink single-cell multiple input and single output (MISO) millimeter wave (mmWave) system. The larger number of packed antennas and the highly directional property of mmWave communications enable directional beamforming to achieve spatial diversity. Toward this end, we consider two different hybrid precoding schemes which are based on orthogonal matching pursuit (OMP). Users are assigned into different clusters and the base station (BS) transmits superposed signals that share the same precoding vector. Moreover, both fixed number of users per cluster and dynamic number of users per cluster are investigated. We aim to jointly optimize the user clustering, service scheduling, and power allocation strategy, in maximizing the proportional fairness (PF) among the users and exploring the multiuser diversity and multiplexing gain. Since the formulated joint user clustering, scheduling and power allocation problem is a mixed integer non-convex optimization problem, we propose a two-fold methodology. First, we apply a hybrid precoding and user clustering scheme, where the hybrid precoder is constructed by singular vector division (SVD) or minimum mean square error (MMSE). Then, with the obtained result, we approximate the proportional fairness power allocation problem by a sequence of Geometric Programming (GP) problems which are solved iteratively. The proposed scheme strikes a balance between the spectral efficiency and service fairness. Results show that the proposed MISO-NOMA scheme which is based on MMSE hybrid precoder and the proposed user scheduling and power allocation strategy under proportional fairness metric can outperform various conventional MISO schemes. Furthermore, our proposed dynamic number of users per cluster scheme outperforms the fixed scheme and can be considered as an upper bound in several aspects, including spectral efficiency and fairness. [ABSTRACT FROM AUTHOR]

The millimeter waves (mmWave) bands, considered to support the forthcoming generation of mobile communications technologies, have a well-known vulnerability to blockages. Recent works in the literature analyze the blockage probability considering independence or correlation among the blocking elements of the different links. In this letter, we characterize the effect of blockages and their correlation on the ergodic capacity. We carry out the analysis for urban scenarios, where the considered blocking elements are buildings that are primarily parallel to the streets. We also present numerical simulations based on actual building features of the city of Chicago to validate the obtained expressions. [ABSTRACT FROM AUTHOR]

Recently, the reconfigurable intelligent surface (RIS) aided communication system has emerged as a promising candidate for future wireless communications. The existing channel estimation methods for RIS-aided millimeter-wave systems assume that the RIS is ideal without blockage. However, in practice, RIS may be blocked by the rain, snow, or dust, which will cause absorption and scattering of the incident/reflected signals and change the channel characteristics. In this paper, we formulate the system model of RIS-aided multi-user communications considering the blocked RIS. Then, we propose a variational Bayesian based channel estimation algorithm that is robust to RIS blockage, where we can simultaneously estimate the channel information and the RIS blockage. Simulation results demonstrate the superior performance of the proposed algorithm to existing ones. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surfaces (IRSs) can enhance the system performance of millimeter wave (mmWave) networks. In practice, phase shifts at the base station and the IRSs are digitally controlled and have discrete values. The channel state information (CSI) feedback also has a limited rate. This work analyzes the spectral efficiency performance of an IRS based mmWave network in which the beamsteering codebooks are used for the passive precoding and analog precoding, and the zero-forcing precoder is used for digital precoding. To capture the features of mmWave channels and reflect the impact of passive and analog precoding, a channel correlation based codebook is employed to quantize the effective channels. Upper-bounds are derived for the spectral efficiency losses due to finite-resolution beamsteering codebooks and limited CSI feedback. It is found that the spectral efficiency loss due to finite-resolution beamsteering codebooks does not depend on the transmit power in large signal-to-noise ratio regimes, while the spectral efficiency loss due to limited CSI feedback increases with the transmit power. Then, the asymptotic performance is analyzed when the numbers of transmit antenna elements and reflecting elements go to infinity. Simulations verify the derivations and findings. [ABSTRACT FROM AUTHOR]

In this paper, we investigate an intelligent reflecting surface (IRS) aided millimeter wave (mmWave) communication system using hybrid precoding of subarray-connected structure at the base station. To maximize the received signal power of the user, we jointly optimize the active beamforming at the BS and passive beamforming at the IRS, respectively. Exploiting the rank-one property of mmWave channels, we transform the original problem into an approximate optimization problem and give the closed-form solution of the approximated problem. Simulation results show that our proposed scheme can effectively improve the received signal quality of the user with a high energy efficiency. [ABSTRACT FROM AUTHOR]

As more and more people choose high-speed rail (HSR) as a means of transportation for short trips, there is ever growing demand of high quality of multimedia services. With its rich spectrum resources, millimeter wave (mm-wave) communications can satisfy the high network capacity requirements for HSR. Also, it is possible for receivers (RXs) to be equipped with antenna arrays in mm-wave communication systems due to its short wavelength. However, as HSRs run with high speed, the received signal power (RSP) varies rapidly over a cell and it is the lowest at the edge of the cell compared to other locations. Consequently, it is necessary to conduct research on RX beamforming for HSR in mm-wave band to improve the quality of the received signal. In this paper, we focus on RX beamforming for a mm-wave train-ground communication system. To improve the RSP, we propose an effective RX beamforming scheme based on deep reinforcement learning (DRL), and develop a deep Q-network (DQN) algorithm to train and determine the optimal RX beam direction with the purpose of maximizing average RSP. Through extensive simulations, we demonstrate that the proposed scheme has better performance than the four baseline schemes in terms of average RSP at most positions on the railway. [ABSTRACT FROM AUTHOR]

Hybrid Free-Space Optical (FSO) and millimeter Wave (mmWave) systems have emerged as a promising candidate for high data rate wireless transmissions due to the unique complementary properties against the different channel and environment conditions. Consequently, in this study, we investigate the hybrid FSO-mmWave systems from a physical-layer security point of view in the presence of different types of eavesdroppers, where the communication between two legitimate peers takes place over both FSO and RF links simultaneously. In particular, exponential atmospheric turbulence and Weibull fading channels are considered for FSO and mmWave links, respectively. We examine practical scenarios to eavesdrop the legitimate communication, and discuss the effects of random radio power of mmWave link and optical irradiance of FSO link on the probability of achieving a secure transmission. The impact of the fundamental physical layer parameters on the secrecy performance of the hybrid system is analyzed by obtaining analytical derivations of the probability of strictly positive secrecy capacity (SPSC) for different types of eavesdroppers, namely RF-, FSO- and Hybrid-Eve. In the light of results, we show that the analytical expressions are in exact agreement with the Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

An emerging technology namely the intelligent reflecting surface (IRS) can be deployed in millimeter wave (mmWave) communication to overcome the large propagation loss and huge power consumption issues. However, the large number of passive IRS elements without signal processing abilities induces high pilot overhead for channel estimation (CE). In this paper, the angular spread feature (or cluster feature) is exploited to formulate the CE problem as a structured sparse signal recovery problem. Then, a structured orthogonal matching pursuit (S-OMP) algorithm is proposed to efficiently solve the problem by utilizing the structure of the channel matrix in row and column without a priori knowledge of the angular spread. Simulation results demonstrate that S-OMP reduces about 40% to 50% pilot overhead at low signal-to-noise ratio (SNR) (SNR= 0 dB) while maintaining the same accuracy of CE compared with the existing methods. [ABSTRACT FROM AUTHOR]

Applying non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) networks has the potential to significantly enhance the spectral efficiency. In this paper, we propose an opportunistic beam-splitting NOMA scheme to fully exploit the antenna array gain in downlink mmWave networks, where single- and double-beam NOMA transmissions are dynamically enabled according to the spatial angle difference between the paired NOMA users, thereby enhancing the flexibility of applying NOMA in mmWave networks. The base station with a single radio frequency chain implements the double-beam NOMA transmission by adopting the beam-splitting technique. We develop a unified theoretical performance analysis framework for the proposed scheme, while taking into account the spatially random users, link blockage model, and general distance-based user pairing strategy. By using tools from stochastic geometry, we derive the exact expressions of the coverage probability and the sum rate of the proposed scheme under both the LoS exponential and ball models. We further derive the corresponding upper bound to simplify the analytical expressions. Simulations validate the theoretical analysis and demonstrate the performance gains of the proposed scheme in terms of the coverage probability and sum rate over the conventional single-beam NOMA and orthogonal multiple access (OMA) schemes. [ABSTRACT FROM AUTHOR]

Efficient millimeter wave (mmWave) beam selection in vehicle-to-infrastructure (V2I) communication is a crucial yet challenging task due to the narrow mmWave beamwidth and high user mobility. To reduce the search overhead of iterative beam discovery procedures, contextual information from light detection and ranging (LIDAR) sensors mounted on vehicles has been leveraged by data-driven methods to produce useful side information. In this paper, we propose a lightweight neural network (NN) architecture along with the corresponding LIDAR preprocessing, which significantly outperforms previous works. Our solution comprises multiple novelties that improve both the convergence speed and the final accuracy of the model. In particular, we define a novel loss function inspired by the knowledge distillation idea, introduce a curriculum training approach exploiting line-of-sight (LOS)/non-line-of-sight (NLOS) information, and we propose a non-local attention module to improve the performance for the more challenging NLOS cases. Simulation results on benchmark datasets show that, utilizing solely LIDAR data and the receiver position, our NN-based beam selection scheme can achieve 79.9% throughput of an exhaustive beam sweeping approach without any beam search overhead and 95% by searching among as few as 6 beams. In a typical mmWave V2I scenario, our proposed method considerably reduces the beam search time required to achieve a desired throughput, in comparison with the inverse fingerprinting and hierarchical beam selection schemes. [ABSTRACT FROM AUTHOR]

With the explosive growth of vehicle applications, vehicular networks based on millimeter wave (mmWave) bands have attracted interests from both academia and industry. mmWave communications are able to utilize the huge available bandwidth to provide multiple Gbps transmission rates among vehicles. In this paper, we address the content distribution scheduling problem in mmWave vehicular networks. It has been challenging for all vehicles in the same network to complete content downloading due to the limited communication resources of roadside units (RSUs) and the high mobility of vehicles. We propose a joint vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) scheduling scheme to minimize the total number of content distribution time slots from a global optimization perspective. In the V2I phase, the RSU serially transmits integrity content to vehicles, which are selected according to the vehicular network topology and transmission scheduling scheme. In the V2V phase, full-duplex communications and concurrent transmissions are exploited to achieve content sharing between vehicles and improve transmission efficiency. Performance evaluations demonstrate that our proposed scheme reduces the number of time slots and significantly improves system throughput when compared with other schemes, especially under large-size file transfers and a large number of vehicles. [ABSTRACT FROM AUTHOR]

To reduce strong mutual interference between unmanned aerial vehicles (UAVs) and ground base stations (GBSs) and to balance the quality of service (QoS) of cell-center and cell-edge users, in UAV-assisted millimeter wave (mmWave) cellular networks we let the UAVs serving as aerial base stations (ABSs) keep a certain distance from the GBSs. It is assumed that GBSs are distributed by a Poisson point process (PPP) on the ground, and the location of UAVs is modeled as a Poisson hole process (PHP) at a certain altitude. Based on the preserving neighbor hole approximation method, the nearest distance distribution functions are derived. With the strongest average received power association policy, we provide the distribution functions of serving distances and the user association probabilities. Then, the coverage probability of the considered network is derived. The coverage performance of two special cases, the mmWave terrestrial cellular network and the UAV-assisted mmWave cellular network with PPP model, are also derived. In addition, the analysis framework is extended into the scenario where UAVs have different altitudes. Through simulations, optimal key ABS parameters maximizing the coverage probability are demonstrated. It also unveils that the proposed UAV-assisted mmWave cellular network can enhance the coverage probability via carefully designing of system parameters. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) communication is one of the critical technologies of the fifth generation mobile communication. It can meet the increasing demand for high-speed railway (HSR) communications services. However, configuring mmWave links, which can be more complicated than that at lower frequency band, is a large source of overhead due to a large number of antennas and high path loss. In this paper, we assume a hybrid frequency system model with both low-frequency band and high-frequency band in the HSR communication scene to meet high data-rate and reliability requirements. Then, we make use of low-band channel information and historical data as the prior information to aid non-uniform mmWave beam selections, which is called Low-Band-and-Historical-Data-Aided-Non-Uniform-Beams-Selection (LBHDANUBS) algorithm. Moreover, we take into account the frequency dependence and time dependence of the same channel to more accurately simulate the characteristics of HSR channels. LBHDANUBS algorithm can not only help to improve the accuracy of beam selections, but also reduce the beam overhead in the training phase and improve the stability of the system. Our simulation results further verify that the proposed scheme based on the low-band information and historical data is superior to the traditional method like exhaustive search and Orthogonal Matching Pursuit (OMP) algorithm. [ABSTRACT FROM AUTHOR]

A three-dimensional (3D) printed Luneburg lens with nearly isotropic properties is presented. The cubical-lattice-type and the rod-type gradient-index materials are employed together to construct the novel printable spherical lens geometry, whose nearly isotropic properties improve the antenna radiation characteristics significantly. The dual-polarized radiation beam generated by the lens antenna can steer in a wide angular range with stable performance throughout a wide operating band. A prototype with an equivalent radius of 16.8 mm is printed and measured in the Ka-band. An impedance bandwidth of more than 40% for |S11| of less than −17.5 dB, a gain of up to 21.3 dBi, and promising radiation patterns with the dual polarization scanning in an angular range of ±60° are obtained experimentally. With the advantages of satisfying operating performance and ease of realization, the lens investigated in this paper would be an attractive candidate for the wireless applications in millimeter-wave vehicular networks. [ABSTRACT FROM AUTHOR]

The combination of unmanned aerial vehicles (UAVs) and millimeter wave (mmWave) multiple-input multiple-out (MIMO) system is regarded as a key enabling technology for beyond 5G networks, as it provides high data rate aerial links. However, establishing UAV-enabled mmWave MIMO communication is quite challenging due to the high hardware cost in terms of radio frequency (RF) chains. As a cost-effective alternative, a beamspace precoding with discrete lens arrays (DLA) architecture has received considerable attention. However, the underlying optimal design in beamspace precoding has not been fully exploited in UAV-enabled communication scenario. In this paper, the joint design of the UAV’s altitude and hybrid beamspace precoding is proposed for the UAV-enabled multiuser MIMO system, in which the DLA is exploited to reduce the number of the RF chain. In the proposed scheme, the optimization problem is formulated as a minimum weighted mean squared error (MWMSE) method. Then an efficient algorithm with the penalty dual decomposition (PDD) is proposed that aims to jointly optimize the altitude of UAV, beam selection and digital precoding matrices. Simulation results confirm the comparable performance of the proposed scheme and perform close to full-digital beamforming in terms of achievable spectral efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we consider the orthogonal frequency division modulation (OFDM) based integrated radar-communication (Rad-Com) for automobile systems operating in millimeter wave band with imperfect time-frequency synchronization for communications. Since different pilot power allocation and placement strategies can result in different performance, we investigate the power allocation and placement design for the Rad-Com system. We analyze the effect of power allocation and pilot placement on the system performance. Based on the analysis, we provide, along with a channel estimation scheme, the pilot power allocation and placement designs that can optimize the radar and communication performance, respectively. Moreover, the tradeoff between radar and communication performance is discussed and a tradeoff design is presented. We conduct simulations to validate our analysis and evaluate the proposed designs. Results show that our analysis is valid and insightful and the proposed designs are effective. [ABSTRACT FROM AUTHOR]

In this paper, we study a beam tracking problem for millimeter wave (mmWave) channels in massive multiple-input and multiple-output communication systems. We formulate the beam tracking problem as a stochastic filtering problem by modeling the dynamic state equation and the observation equation. Then, given prior information of the channel, we propose an efficient grid-based Bayesian beam tracking algorithm by leveraging the sparsity of the mmWave channel. Our proposed algorithm examines neighboring transmit and receive beam pairs and exploits multiple observations on the angular domain representation in the sense of the Bayesian statistics. Numerical results show that the proposed Bayesian method with multiple observations outperforms conventional schemes in terms of both the beam tracking accuracy and computational complexity. [ABSTRACT FROM AUTHOR]

In this paper, we propose three new compressive sensing-based algorithms for channel estimation in millimeter wave hybrid MIMO systems over doubly (time and frequency) selective channels. Utilizing the basis expansion model (BEM) for effectively representing doubly selective channels, we first propose a BEM-based block orthogonal matching pursuit (BBOMP) algorithm, which can work with any training sequence structure. Next, we present the second algorithm to reduce the complexity of the BBOMP method by employing a special training sequence which results in a computationally efficient block sparse sensing matrix. Finally, in order to further decrease the computational complexity, we propose the third algorithm, where the channel estimation is split into two separate steps of tap detection and gain estimation. The proposed algorithms exploit the entire available training sequence to estimate all channel parameters, and can capture channel variations across the entire training frames without requiring a feedback channel. The Cramer-Rao lower bound and the computational complexity of the proposed algorithms are also addressed. Intensive computer simulations are conducted to evaluate the accuracy of the proposed approaches, showing that they can significantly improve the mean squared error performance compared with the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communication is now being considered as one of possible technologies for the sixth generation (6G) wireless communication systems. In this paper, a novel three-dimensional (3D) space-time-frequency non-stationary theoretical channel model is first proposed for 6G THz wireless communication systems employing ultra-massive multiple-input multiple-output (MIMO) technologies with long traveling paths. Considering frequency-dependent diffuse scattering, which is a special property of THz channels different from millimeter wave (mmWave) channels, the relative angles and delays of rays within one cluster will evolve in the frequency domain. Then, a corresponding simulation model is proposed with discrete angles calculated using the method of equal area (MEA). The statistical properties of the proposed theoretical and simulation models are derived and compared, showing good agreements. The accuracy and flexibility of the proposed simulation model are demonstrated by comparing the simulation results of the relative angle spread and root mean square (RMS) delay spread with corresponding measurements. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) band, i.e., 30 to 300 GHz, is characterized by short range transmissions and vulnerability to path blockage necessitating the use of relaying. Probing more relays finds out the best relay having the highest spectral efficiency but at the expense of increasing the probing overhead due to excessive beamforming training (BT) causing a decrease in the overall throughput. In this paper, mmWave two-hop relaying will be formulated as a single player multi-armed bandit (MAB) problem enabling one relay probing while maximizing the achievable spectral efficiency. Moreover, the relays could not establish the mmWave link due to blockage for instance will be identified as sleeping relays and eliminated from the rest of the MAB game. Thus, sleeping non contextual MAB (S-MAB) algorithm, namely sleeping Thompson sampling (S-TS) will be proposed to handle the problem. Furthermore, by utilizing the multiband capability of standardized WiGig devices containing both 2.4/5 GHz WiFi and 60 GHz mmWave bands, WiFi information will be used as contexts of the MAB game. Therefore, sleeping contextual MAB (S-CMAB) algorithm, namely S-CTS, will be proposed as well. Numerical and regret analysis ensure the superior performance of the S-CMAB algorithm over the S-MAB counterpart and the existing mmWave relay probing solutions accompanied with high convergence rates. [ABSTRACT FROM AUTHOR]

The emerging 5G New Radio (NR) cellular systems that may operate in millimeter-wave (mmWave) frequency bands are expected to offer larger bandwidths. They are to be deployed in densely crowded environments, where the traffic load has a high degree of variability, which may introduce capacity bottlenecks. One of the options to alleviate the latter is to concurrently utilize the radio resources available in unlicensed mmWave bands, e.g., at 60 GHz. In this work, we address the coexistence of mmWave-based NR Unlicensed (NR-U) and WiGig technologies and account for the mmWave-specific directionality, propagation, and blockage effects. By further incorporating the features of duty cycling and random access operation, we construct a mathematical framework, which is capable of characterizing the achievable data rates of the NR-U users that operate over both licensed and unlicensed mmWave spectrum simultaneously. Our numerical results demonstrate that the rate attained by such devices is primarily regulated by the initial contention window size that, in its turn, heavily depends on the system and environmental parameters. We report the optimal contention window values for a wide range of blocker and user densities as well as antenna array configurations. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) communication enables ultra-high rate data transmission in wireless environments, but its performance depends on blockages between the transmitter and receiver significantly. To overcome the blockage problem, we consider two approaches: multi-connectivity and network densification. The multi-connectivity opens up a new paradigm for user centric communication, where each user autonomously chooses multiple base stations (BSs) to attain high quality services. The network densification allows network operators to deploy many BSs in a limited area, thereby providing qualified communication services to users. In this paper, we study user equipment (UE) association control in user centric mmWave communication environments. When a UE arrives, the network provides the UE with information on the resource status of adjacent BSs, and the UE generates a set of candidate BSs. For access control, we formulate two optimization problems that aim to minimize peak load and sum load, respectively. They are non-convex and combinatorial, so their computational complexity grows exponentially with the problem size. As a solution, we develop an access pricing and peak load limit control scheme. Through numerical experiments, we investigate its impact on the performance of mmWave communication systems. The results show that our proposed scheme successfully provides high quality services to users and allocates the network load fairly over the network. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) communication systems using adaptive-resolution analog-to-digital converters (RADCs) have recently drawn considerable interests from the research community as benefit of their high energy efficiency and low implementation cost. In this paper, we focus on the mmWave uplink using RADCs and investigate the joint user scheduling and resource allocation problem. Specifically, we seek to maximize the system throughput of the scheduled users by jointly optimizing their transmit power level and hybrid combiners as well as the number of quantization bits, subject to practical constraints. By relying on fractional programming (FP) techniques, we first covert this problem into a form amenable to optimization and exploit the specific structures in its solutions with the aid of the so-called Ky Fan $n$ -norm.Then, the resultant optimization problem is solved using a penalty block successive concave approximation (P-BSCA) algorithm. Our numerical results reveal that the proposed algorithm substantially enhances the throughput of the scheduled users compared to the state-of-the-art benchmark schemes and provides more flexible and efficient resource allocation control. [ABSTRACT FROM AUTHOR]

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. [ABSTRACT FROM AUTHOR]

This paper investigates secure broadcast communications in intelligent reflecting surface (IRS)-aided millimeter wave (mmWave) symbiotic radio (SR) networks, where the IRS and the base station (BS) are cooperating. Specifically, the IRS assists secure broadcasting for the BS by smartly reconfiguring the phase shifts of the signals from the BS, while delivering its own information to an Internet-of-Things device (IoD). We aim at maximizing the minimum secrecy rate of multiple users by jointly designing the hybrid precoder at the BS and the passive beamformer at the IRS, subject to the rate constraints of both the multiple users and the IoD. The design is formulated as a non-convex optimization problem, which is intractable. To handle it, we develop a computationally efficient iterative algorithm based on the successive convex approximation, the efficiency and superiority of which have been validated by simulation results. [ABSTRACT FROM AUTHOR]

The sensitivity to blockages is a key challenge for millimeter wave and terahertz networks in 5G and beyond. Since these networks mainly rely on line-of-sight (LOS) links, sudden link blockages highly threaten the reliability of the networks. Further, when the LOS link is blocked, the network typically needs to hand off the user to another LOS basestation, which may incur critical time latency, especially if a search over a large codebook of narrow beams is needed. A promising way to tackle the reliability and latency challenges lies in enabling proaction in wireless networks. Proaction allows the network to anticipate future blockages, especially dynamic blockages, and initiate user hand-off beforehand. This article presents a complete machine learning framework for enabling proaction in wireless networks relying on visual data captured, for example, by red-green-blue (RGB) cameras deployed at the base stations. In particular, the article proposes a vision-aided wireless communication solution that utilizes bimodal machine learning to perform proactive blockage prediction and user hand-off. This is mainly achieved via a deep learning algorithm that learns from visual and wireless data how to predict incoming blockages. The predictions of this algorithm are used by the wireless network to proactively initiate hand-off decisions and avoid any unnecessary latency. The algorithm is developed on a vision-wireless dataset generated using the ViWi data-generation framework. Experimental results on two basestations with different cameras indicate that the algorithm is capable of accurately detecting incoming blockages more than ${\sim} 90\%$ of the time. Such blockage prediction ability is directly reflected in the accuracy of proactive hand-off, which also approaches 87%. This highlights a promising direction for enabling high reliability and low latency in future wireless networks. [ABSTRACT FROM AUTHOR]

Satellite communication is considered as an efficient way to achieve the reliable communication for worldwide users. To further enhance the achievable rate of the satellite system, we propose joint beamforming schemes of an integrated satellite-terrestrial self-backhauled (ISTS) system, in which the satellite backhaul and terrestrial access links are operating at the same millimeter wave band. Specifically, the earth station and the base station (BS) constitute a self-backhauled relay to forward the satellite signals to the terrestrial users. A sum rate maximization problem is formulated under the constraints of the maximum power requirements of the satellite and the BS, the minimum quality-of-service requirements of the terrestrial users, and the maximum satellite backhaul capacity. To obtain some insights, we first assume that the perfect channel state information (CSI) on the satellite and terrestrial links is known and transform the formulated optimization problem to a standard difference of convex problem. Then we solve it iteratively by adopting the convex-concave procedure approach. Furthermore, when only imperfect CSI on the satellite and terrestrial links is available, we employ a iterative penalty function algorithm associated with the sequential convex approximation method and the S-procedure approach to obtain suboptimal beamforming vectors. Finally, simulation results demonstrate that the proposed joint beamforming schemes have better performance compared with other benchmark schemes and the ISTS architecture is suitable for the satellite systems in various orbits. [ABSTRACT FROM AUTHOR]

In this article, we propose hybrid precoding/combining designs for full-duplex amplify-and-forward millimeter wave relay systems. The imperfect channel estimations induced by applicable estimation techniques are considered to develop robust fully digital transceivers. A zero-space self-interference (SI) cancellation method is proposed to attenuate the SI. An alternating method with closed-form solutions is utilized to solve the hybrid processors. Simulation results show that the proposed design is close to the fully digital solutions and prevails the existing designs. [ABSTRACT FROM AUTHOR]

In this paper, we investigate hybrid beamforming, user scheduling, and resource allocation optimization based on spectrum coexisting forward transmission in integrated terrestrial-satellite network (ITSN) with the purpose of improving system sum rate and energy efficiency. Considering the limitation of on-board beamforming, a hybrid analog-digital beamforming scheme is designed under the scenario of millimeter wave (mmWave) coexisting in the ITSN framework. Besides, in order to further mitigate intra-beam and inter-beam interference, we propose an adaptive user scheduling scheme, which first determines the cluster center based on adaptive threshold, and then selects users with less channel correlation into a scheduling cluster. Moreover, we model system sum rate maximization problem that incorporates maximum power constrains and minimum data rate requirements. Combined with the aforementioned hybrid beamforming and user scheduling strategy, we formulate the sum rate maximizing problem to a pure power allocation issue. In view of the non-convexity and high complexity, we propose a feasible optimization method based on the minimum mean square error (MMSE) criterion and logarithmic linearization to optimize the power allocation for each user terminal (UT). Simulation results show that our proposed joint beamforming and resource allocation optimization scheduling scheme can achieve an attractive gain in system sum rate and energy efficiency compared with conservative beamforming and allocations. [ABSTRACT FROM AUTHOR]

In this paper, a novel beam alignment algorithm based on the sparse graph coding theory is proposed for millimeter wave (mmWave) time-varying channels. Firstly, a pilot design method is introduced to transform the mmWave time-varying beam alignment into a sparse-graph design and detection problem. Inspired by Low-Density-Parity-Check (LDPC) codes and fountain codes, a multi-stage sparse coding method is proposed for the design of the measurement matrix and the theoretical bound of the probability of success is derived to guide the design of the sparse-graph. A beam alignment algorithm is subsequently proposed to detect the beam index and estimate the carrier frequency offset (CFO). Then, the Carmeŕ-Rao Lower Bound (CRLB) is derived. Simulation results demonstrate that the proposed beam alignment algorithm achieves significant performance improvements over the conventional counterparts in both the noiseless and noise cases. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of hybrid precoding and combining for wideband millimeter wave (mmWave) and sub-terahertz (THz) MIMO-OFDM systems with beam squint effects. In the presence of the beam squint effect, the conventional spatially sparse precoding-based hybrid precoding method which approximates the optimal precoder/combiner with a set of array response vectors suffers severe performance degradation. To address this difficulty, we propose a new set of basis vectors to approximate the optimal precoder/combiner. Each new basis vector is devised to form a radiation pattern with a wide beam to cover the squinted beam directions caused by different frequencies. Simulation results show that the proposed method can effectively alleviate the beam squint effect and achieve a substantial performance improvement over the existing state-of-the-art hybrid precoding method. [ABSTRACT FROM AUTHOR]

Hybrid precoding is used in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems instead of full digital precoding to reduce the cost and power consumption. Conventional hybrid precoding however requires complex channel estimation before beamforming. In this paper, we propose a low complexity low-cost channel estimation-free deep direct beamforming method composed of two basic steps-beam impulse and beamforming for time division duplex (TDD). This method is built upon randomized singular value decomposition (RSVD) and can directly complete the process of beamforming. Furthermore, a realistic dataset of mmWave channel-DeepMIMO is adopted to evaluate and determine the practicability of this method. The simulation results demonstrate that the proposed deep direct beamforming achieves high performance while its complexity and power consumption are very low. Compared with other methods without perfect channel status information (CSI), the proposed method costs less and requires lower computational resources while achieves higher spectral efficiency. Furthermore, the RSVD can be easily combined with conventional beamforming methods hence the proposed method is easily extendable to other applications. [ABSTRACT FROM AUTHOR]

Multi-sensor millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs) relying on both distributed (D-MIMO) and centralized (C-MIMO) configurations are conceived. Hybrid combining based low complexity fusion rules are constructed for the fusion center (FC) for both D-MIMO and C-MIMO systems employing a partially connected structure (PCS) and a fully connected structure (FCS), respectively. The decision rules are based on the transmission of local binary sensor decisions and also take into account the accuracy of local detection at the individual sensors. Closed-form analytical expressions are derived for the probabilities of false alarm and correct detection to analyze the system's performance. Furthermore, the asymptotic distributed detection (DD) performance corresponding to both antenna architectures is analyzed in the large-scale antenna regime along with the pertinent power scaling laws. Additionally, digital signaling matrices are designed for enhancing the system performance. Our simulation results quantify the performance gains of the proposed architectures, which closely match the analytical results. [ABSTRACT FROM AUTHOR]

A substrate integrated waveguide (SIW) H-plane horn antenna with miniaturized longitudinal dimension and increased gain is proposed by loading slow-wave (SW) structures in the form of metallized blind via-holes inside the flare region of the horn for vehicular millimeter wave communications. The slow-wave structure can reduce the phase velocity around the center line of the broad wall and compensate the large phase difference between the center and edge of the aperture caused by reduction of longitudinal length of the horn. Compared with optimum horn with the same aperture width, the gain of miniaturized SIW horn is successfully increased, while the longitudinal dimension is decreased. A SW-SIW horn antenna which covers the 28 GHz band (27.5–28.35 GHz) allocated by Federal Communications Commission for the 5G millimeter wave communications is designed to verify the feasibility of the miniaturized SIW horn antenna facilitated by the proposed slow-wave structure. The SW-SIW horn realizes 53.83% reduction of longitudinal length compared with the optimum horn. The gain of the SW-SIW horn is improved by 1.1 dB on average over 27.5–28.5 GHz compared with optimum horn. A prototype of the proposed SW-SIW H-plane horn antenna is manufactured and measured. The measured results agree well with the simulations. [ABSTRACT FROM AUTHOR]