Search

Large-scale multiple testing is common in the statistical analysis of high-dimensional data. Conventional multiple testing procedures usually implicitly assumed that the tests are independent. However, this assumption is rarely established in many practical applications, particularly in "high-throughput" data analysis. Incorporating dependence structure information among tests can improve statistical power and interpretability of discoveries. In this paper, we propose a new large-scale dependent multiple testing procedure based on the hidden semi-Markov model (HSMM), which characterizes local correlations among tests using a semi-Markov process instead of a first-order Markov chain. Our novel approach allows for the number of consecutive null hypotheses to follow any reasonable distribution, enabling a more accurate description of complex local correlations. We show that the proposed procedure minimizes the marginal false non-discovery rate (mFNR) at the same marginal false discovery rate (mFDR) level. To reduce the computational complexity of the HSMM, we make use of the hidden Markov model (HMM) with an expanded state space to approximate it. We provide a forward-backward algorithm and an expectation-maximization (EM) algorithm for implementing the proposed procedure. Finally, we demonstrate the superior performance of the SMLIS procedure through extensive simulations and a real data analysis. [ABSTRACT FROM AUTHOR]

The stochastic block model is one of the most studied network models for community detection, and fitting its likelihood function on large-scale networks is known to be challenging. One prominent work that overcomes this computational challenge is the fast pseudo-likelihood approach proposed by Amini et al. for fitting stochastic block models to large sparse networks. However, this approach does not have convergence guarantee, and may not be well suited for small and medium scale networks. In this article, we propose a novel likelihood based approach that decouples row and column labels in the likelihood function, enabling a fast alternating maximization. This new method is computationally efficient, performs well for both small- and large-scale networks, and has provable convergence guarantee. We show that our method provides strongly consistent estimates of communities in a stochastic block model. We further consider extensions of our proposed method to handle networks with degree heterogeneity and bipartite properties. for this article are available online. [ABSTRACT FROM AUTHOR]

The stochastic block model (SBM) is widely employed as a canonical model for network community detection. Recovering community labels under SBM is not a trivial task, since its theoretical optimization problem is NP‐hard. To solve this problem, numerous statistical methods have been developed in the literature, most of which are, however, not applicable to large‐scale networks. To overcome this limitation, in this paper, we propose a split likelihood (SL) framework, under which we provide a fast converging algorithm, named the SL algorithm, with significant advantages in terms of both community detection accuracy and computational efficiency. Moreover, to deal with networks with hub nodes or those with substantial degrees of variation within communities, we develop a variant of the SL algorithm, named the conditional SL (CSL) algorithm. We present the computational and statistical properties of the proposed algorithm. Then, we demonstrate the superiority of the proposed methods through a large amount of numerical experiments as well as two empirical analyses on real‐world networks. [ABSTRACT FROM AUTHOR]

Multi‐layer networks are often used to represent multiple types of relationships between nodes in network studies. In this paper, we investigate the community detection problem in multi‐layer networks. Specifically, we consider the multi‐layer stochastic block model (MLSBM), which assumes that the community memberships are shared across all network layers, while other model parameters can be different between different layers. Variational methods have been developed to fit the MLSBM, but they do not scale well to very large networks. Inspired by the iterative pseudo‐likelihood maximization strategy for single networks, we develop a pseudo‐likelihood based algorithm to fit the MLSBM and estimate the community labels, and we also extend the proposed algorithm to the degree‐corrected case to deal with degree heterogeneity. The proposed algorithms are fast and can cope with multi‐layer networks with up to millions of nodes. The advantages of the proposed methods in both community detection and computational efficiency are demonstrated by numerical studies. [ABSTRACT FROM AUTHOR]

This paper investigates the uplink transmission in multicell multiuser multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. The system model considers imperfect channel estimation, pilot contamination (PC), and multicarrier and multipath channels. Analytical expressions are first presented on the mean square error (MSE) of two classical channel estimation algorithms [i.e., least squares (LS) and minimum mean square error (MMSE)] in the presence of PC. Then, a simple H-infinity (H-inf) channel estimation approach is proposed to have good suppression to PC. This approach exploits the space-alternating generalized expectation–maximization (SAGE) iterative process to decompose the multicell multiuser MIMO (MU-MIMO) problem into a series of single-cell single-user single-input single-output (SISO) problems, which reduces the complexity significantly. According to the analytic results given herein, increasing the number of pilot subcarriers cannot mitigate PC, and a clue for suppressing PC is obtained. It is shown from the results that the H-inf has better suppression capability to PC than classical estimation algorithms. Its performance is close to that of the optimal MMSE as the length of channel impulse response (CIR) is increased. By using the SAGE process, the performance of the H-inf does not degrade when the number of antennas is large at the base station (BS). [ABSTRACT FROM PUBLISHER]

Multicarrier direct-sequence code-division multiple-access (MC-CDMA) overlay has been proposed to be used for ultra-wide-band (UWB) communications. Interference reduction and interference suppression are the key issues for sharing the spectrum in harmony between the established narrow-band systems and e overlaid UWB system. In this paper, investigation is carried out on the use of compromising measures incorporated to the MC-CDMA overlay to meet these goals, as well as on their impacts to e involving parties. At the transmitter, interference reduction to e established narrow-band systems is done by using notch filters. multipath Nakagami fading channel is assumed. At the receiver, e interference suppression from those narrow-band systems is filled by minimum mean square error (MMSE) detection technique. Numerical results show that precombining MMSE with selective-maximal combining provides the UWB system with much better performance than the receiver made up of notch filter in cascade with code correlator. [ABSTRACT FROM AUTHOR]

In this letter, the performance of multicarrier code-division multiple-access (CDMA) systems is studied in the presence of narrowband interference for future ultra-wideband (UWB) communications. A Nakagami fading channel is assumed, and notch filters along with diversity techniques are used in the multicarrier CDMA receiver. A complete performance analysis of error probability is given. It is shown that when the number of subcarriers jammed by narrowband interference is small, the multicarrier receiver without notch filters can work well, due to the gain of frequency diversity from nonjammed subcarriers. On the other hand, when the number of subcarriers jammed by the narrowband interference is large, using notch filters can improve the multicarrier system performance significantly. [ABSTRACT FROM AUTHOR]

In this paper, the effect of imperfect channel estimation on the transmit diversity based on space-time block coding for the downlink of a direct-sequence code-division multiple-access system is studied. Two transmit antenna and one receiving antennas are employed. However, the results of this paper can be extended to the system with more receiving antennas. Each channel is modeled as frequency-selective Rayleigh fading and the pair of channels corresponding to two transmit antennas are mutually independent. Both spatial diversity gain and multipath diversity gain are obtained in the system. The system performance is evaluated in terms of bit-error rate under the perfect and imperfect channel estimation. A pilot-assisted channel-estimation scheme with one common spreading code sequence is exploited. It is shown that the inaccurate channel estimates suffering from multiple access and multipath interference significantly degrade the system performance and can be effectively improved by use of a simple low-pass filter. The investigation of the power ratio of pilot to data channels illustrates that the base station should dynamically adjust the transmit power of the pilot channel according to the varying system configurations in order to achieve the best performance. [ABSTRACT FROM AUTHOR]

Proposes a novel frequency hopping/M-ary frequency-shift-keyed (MFSK) receiver with additional partial correlators by means of side information for asynchronous frequency-hopping multiple-access systems in the presence of Rayleigh fading. Description on the system model; Analysis of bit error rate of the novel MFSK receiver with Rayleigh fading; Presentation of numerical results.

Investigates the performance of fast frequency-hopping (FFH) self-normalized orthogonal M-ary frequency-shift-keyed (MFSK) noncoherent receivers in the presence of multitone jamming. Description of the system models; Bit error probability for noncoherent self-normalized FFH/MFSK receivers; Presentation of numerical results.

Proposes a multicarrier direct-sequence/slow-frequency-hopping code-division multiple access systems. Description on the system models; Performance analysis; Discussion on the numerical results.

Presents information on an analytical study of the performance of fast frequency-hopped (FFH), M-ary orthogonal frequency-shift keyed (MFSK) noncoherent modulation with linear combining square-law envelops in the presence of multitone interference. Description of the system model; Calculation of bit-error probability for FFH/MFSK communication systems with multitone interference; Numerical results.

Presents a study which described the behavior of reflection coefficients of stochastic lattice filter applied to acode-division multi-access overlay system. Analytic expressions for coefficients for two-stage filter using Rayleigh fading channel; Details of filter coefficients; Conclusion.

Focuses on the use of a suppression filter for a direct-sequence code-division multiple-access (DS-CDMA) system operating over a Rayleigh fading and sharing common spectrum with a narrow-band waveform. DS-CDMA system and channel models given; Up-link bit error rate (BER) performance of CDMA system; Parameters that influence CDMA system BER performance.

This paper investigates the average bit error rate performance of a direct sequence code division multiple access system operating over a multipath Rician fading channel (which models indoor radio propagation in factories). We consider both phase shift-keying modulation with coherent demodulation and differential phaseshift-keying modulation with non-coherent demodulation. Predetection multipath diversity (maximal-ratio-combining for coherent reception and equal gain combining for non-coherent reception) is considered for improving the BER performance. [ABSTRACT FROM AUTHOR]

Communities are often associated with important structural characteristics of a complex network system, therefore detecting communities is considered to be a fundamental problem in network analysis. With the development of data collection technology and platform, more and more sources of network data are acquired, which makes the form of network as well as the related data more complex. To achieve integrative community detection of a multi-layer attributed network that involves multiple network layers together with their attribute data, effectively utilizing the information from the multiple networks and the attributes may greatly enhance the accuracy of community detection. To this end, in this article, we study the integrative community detection problem of a multi-layer attributed network from the perspective of matrix factorization, and propose a penalized alternative factorization (PAF) algorithm to resolve the corresponding optimization problem, followed by the convergence analysis of the PAF algorithm. Results of the numerical study, as well as an empirical analysis, demonstrate the advantages of the PAF algorithm in community discovery accuracy and compatibility with multiple types of network-related data. [ABSTRACT FROM AUTHOR]

The technical challenges, e.g. the mobility management and the offloading process, hinder the conventional cellular systems to meet the huge data traffic requirements of the next generation mobile communications. The traditional system (e.g dual-connectivity (DC)) has been proposed to improve the mobility management, however, it will inherit the big trade-off in the offloading process between the energy consumption for the small cell (SC) discovery (SCD) process and the efficiency of utilizing the system resources (e.g. frequency and signaling). In this paper, we present a framework to model the potential offloading opportunities as well as the offloading loss when a typical user equipment (UE) performs the inter-frequency (IRF) scan periodically. The proposed framework also studies the impact of the SCD on the energy efficiency. To improve the system performance and reduce the power consumption at the UEs, a new scheme, trio-connectivity (TC), is proposed in this paper to tackle the aforementioned challenges. The TC includes three planes: control-plane (C-plane), user-plane (U-plane) and indication-plane (I-plane). The I-plane works as an indicator to help the UE to identify and discover the SCs in the system prior to offloading. The role of the I-plane is to keep the SCD on one frequency channel regardless of the number of frequency channels in the system. In the proposed offloading mechanism, some of the energy consumption is transferred from the UE to the network. By using the proposed framework, UE energy efficiency and system energy efficiency as well as the total energy consumption are derived as performance metrics to compare between the TC and the DC. The results show that the TC can outperform the DC in dense cellular systems. [ABSTRACT FROM AUTHOR]

Multi-input multi-output and non-orthogonal multiple access (MIMO-NOMA) Internet-of-Things (IoT) systems can improve channel capacity and spectrum efficiency distinctly to support real-time applications. Age of information (AoI) plays a crucial role in real-time applications as it determines the timeliness of the extracted information. In MIMO-NOMA IoT systems, the base station (BS) determines the sample collection commands and allocates the transmit power for each IoT device. Each device determines whether to sample data according to the sample collection commands and adopts the allocated power to transmit the sampled data to the BS over the MIMO-NOMA channel. Afterwards, the BS employs the successive interference cancellation (SIC) technique to decode the signal of the data transmitted by each device. The sample collection commands and power allocation may affect the AoI and energy consumption of the system. Optimizing the sample collection commands and power allocation is essential for minimizing both AoI and energy consumption in MIMO-NOMA IoT systems. In this paper, we propose the optimal power allocation to achieve it based on deep reinforcement learning (DRL). Simulations have demonstrated that the optimal power allocation effectively achieves lower AoI and energy consumption compared to other algorithms. Overall, the reward is reduced by 6.44% and 11.78% compared the to GA algorithm and random algorithm, respectively. [ABSTRACT FROM AUTHOR]

In the fifth generation (5G) era, mobile networks will provide diversified services such as enhanced Mobile BroadBand (eMBB) and ultra-reliable low-latency communication (URLLC). Furthermore, the 5G architecture will be fog-like, enabling a functional split of network functionalities between cloud and edge nodes. In this article, we propose a non-orthogonal multiple access (NOMA)-enabled fog-cloud structure in a novel density-aware fog-based radio access networks (F-RAN) to tackle different aspects of high and low-density regions, in order to meet the heterogeneous requirements of eMBB and URLLC traffic. A framework of two different problem formulations is considered to cater the high throughput and low-latency requirements in a high and low-density mode respectively. In the first problem, we study the joint caching placement and association strategy aiming at minimizing the average delay. To deal with the first problem, we apply McCormick envelopes and Lagrange partial relaxation method to transform it into three convex sub-problems, which is then solved by proposing a distributed algorithm. The second problem is to jointly optimize transmission mode selection, subchannel assignment and power allocation to maximize the sum data rate of all fog user equipments (F-UEs) while satisfying fronthaul capacity and fog-computing access point (F-AP) power constraints. Moreover, for given transmission mode selection and subchannel assignment, the optimal power allocation is derived in a closed-form expression. Simulation results are provided to validate the effectiveness of the proposed NOMA-enabled F-RAN framework and reveal that the ultra-low latency and high throughput can be achieved by properly utilizing the available resources. [ABSTRACT FROM AUTHOR]

Content caching at mobile user devices (UDs) utilizing device-to-device (D2D) communications is a promising technology to enhance the performance of mobile networks in terms of latency, throughput, and energy consumption. In this paper, a novel method of content delivery using multiple devices to single device (MDSD) communications through D2D links is presented. In this method, the Zipf distribution with an exponent shape parameter is adopted to model the content caching popularity for the analysis of the achievable signal-to-interference-plus-noise ratio. In order to investigate the advantage of the proposed MDSD method, first, a closed-form expression of the outage probability is theoretically derived for a single D2D communication to evaluate the success of content delivery to a reference UD. Second, the expression of the outage probability for MDSD communication is derived, where the outage probability is modeled as a function of content caching popularity, the density of UDs, and the size of cooperative area. The research work is further extended to address the frequency reuse among different UDs in one cell, where a frequency band factor is introduced, and the optimal radius of the cooperative area is introduced and analyzed. The analytical results, validated by the simulation results, show that the outage probability decreases drastically when the popularity of the content increases or the radius of the cooperative area increases. Using the derived closed-form expression of the outage probability, the area spectral efficiency (ASE) of the system is presented. Furthermore, the results show that as the frequency band factor increases, the outage probability decreases, and also the ASE decreases. Finally, it is shown that the MDSD outperforms the single-D2D-based method. [ABSTRACT FROM AUTHOR]

Microbial infections endanger human health and life. Conventional antibiotics has saved countless human lives, however, is seriously challenged by the quick emergence of antibiotic-resistant pathogens. It is urgent to develop new types of antimicrobial agents to treat antibiotic-resistant microbial infections. Host defense peptides (HDPs) have broad-spectrum antimicrobial activity and low susceptibility to antimicrobial resistance, therefore, have been actively studied to develop promising antimicrobial agents. However, natural HDPs are structurally unstable due to their easy hydrolysis by proteases. Sequence-defined peptides have been explored as HDP mimics and have proven as promising candidates of antimicrobial drugs. Nevertheless, preparation of these HDP-mimicking peptides by solid-phase synthesis is time-consuming, expensive, and difficult for large scale synthesis. Assisted by the development of polymerization chemistry, polypeptides can be prepared in the form of amino acid polymers conveniently and at large scales using the polymerization strategy. Amino acid polymers, also known as poly(amino acid)s, have the same or similar backbone structure as natural peptides and have excellent biocompatibility. Several classes of such antimicrobial polymers have been explored as synthetic mimics of HDPs including α-amino acid polymers, β-amino acid polymers, peptoid polymers, amino acid hybrid polymers, and peptide mimicking polymers such as poly(2-oxazoline)s. To tune the biological activities and obtain the optimal antimicrobial polymers, key structure characteristics of HDPs are involved and investigated such as positive charges and the hydrophobic/hydrophilic amphiphilic structure. In this review, we provide an overview of research in the last decade about the design of HDP-mimicking antimicrobial amino acid polymers and beyond, including positive charge, amphiphilic structure, chain length, end group, hydrophilicity, stereochemistry, secondary structure, topology, self-assembly and backbone structure, as well as the major applications of antimicrobial amino acid polymers. Finally, we provide a perspective on the comparison between antimicrobial peptides and antimicrobial amino acid polymers, as well as some key challenges that still need to be addressed for possible clinical application of HDP-mimicking antimicrobial amino acid polymers. [Display omitted] [ABSTRACT FROM AUTHOR]

In a multicast scenario, all desired users are divided into $K$ groups. Each group receives its own individual confidential message stream. Eavesdropper group aims to intercept $K$ confidential message streams. To achieve a secure transmission, two secure schemes are proposed: Maximum group receive power plus null-space (NS) projection (Max-GRP plus NSP) and leakage. The former obtains its precoding vector per group by maximizing its own group receive power subject to the orthogonal constraint, and its AN projection matrix consist of all bases of NS of all desired steering vectors from all groups. The latter attains its desired precoding vector per group by driving the current confidential message power to its group steering space and reducing its power leakage to eavesdropper group and other $K-1$ desired ones by maximizing signal-to-leakage-and-noise ratio. And its AN projection matrix is designed by forcing AN power into the eavesdropper steering space by viewing AN as a useful signal for eavesdropper group and maximizing AN to leakage-and-noise ratio. Simulation results show that the proposed two methods are better than conventional method in terms of both bit-error-rate and secrecy sum-rate per group. Also, the leakage scheme performs better than Max-GRP-NSP, especially in the presence of direction measurement errors. However, the latter requires no channel statistical parameters and, thus, is simpler compared to the former. [ABSTRACT FROM AUTHOR]

Ultra-dense networks (UDNs) constitute one of the most promising techniques for supporting the 5G mobile system. By deploying more small cells in a fixed area, the average distance between users and access points can be significantly reduced; hence, dense spatial frequency reuse can be exploited. However, severe interference is the major obstacle in UDNs. Most contributions deal with the interference by relying on cooperative game theory. This article advocates the application of dense user-centric C-RAN philosophy to UDNs, thanks to the recent development of cloud computing techniques. Under dense C-RAN, centralized signal processing can be invoked for supporting CoMP transmission. We summarize the main challenges in dense user-centric C-RANs. One of the most challenging issues is the requirement of the global CSI for the sake of cooperative transmission. We investigate this requirement by only relying on partial CSI, namely, on inter-cluster large-scale CSI. Furthermore, the estimation of the intra-cluster CSI is considered, including the pilot allocation and robust transmission. Finally, we highlight several promising research directions to make the dense user-centric C-RAN become a reality, with special emphasis on the application of big data techniques. [ABSTRACT FROM AUTHOR]

The non-orthogonal multiple access (NOMA) allows one subcarrier to be allocated to more than one user at the same time in an orthogonal frequency division multiplexing (OFDM) system. NOMA is a promising technique to provide high throughput due to frequency reuse within a cell. In this paper, a novel interference cancellation (IC) technique is proposed for asynchronous NOMA systems. The proposed IC technique exploits a triangular pattern to perform the IC from all interfering users for the desired user. The bit error rate and the capacity performance analysis of an uplink NOMA system with the proposed IC technique are presented, along with the comparison to orthogonal frequency division multiple access (OFDMA) systems. The numerical and simulation results show that the NOMA with the proposed asynchronous IC technique outperforms the OFDMA. It is also shown that employing iterative IC provides significant performance gain for NOMA and the number of required iterations depends on the modulation level and the detection method. With hard decision, two iterations are sufficient, and however, with soft decision, two iterations are enough only for low modulation level, and more iterations are desirable for high modulation level. [ABSTRACT FROM AUTHOR]

This paper focuses on a reconfigurable intelligent surface (RIS)‐aided full‐duplex multi‐user massive multiple‐input multiple‐output system with transceiver hardware impairments (THWIs). Different from the existing works, the two‐timescale design scheme is considered. The phase shift at the RIS is designed only based on the statistical channel state information. Firstly, the closed‐form expression of the uplink and downlink achievable rate is derived. Then, the power scaling laws are revealed. Finally, the impact of THWIs on the system performance is analysed and genetic algorithm to maximize the achievable rate is used. [ABSTRACT FROM AUTHOR]

Over the last few years, fundamental research has demonstrated the great potential of cooperative wireless networking in increasing system capacity and enlarging the coverage area as well as enhancing quality of service (QoS) by taking advantage of cooperative diversity and multiplexing. Consequently, cooperative wireless networking has become one of the widely recognized features for the future wireless communication systems. While the conventional research mainly focuses on relatively simple cooperative relay topologies or the cooperation schemes under the existing infrastructure networks, cooperative networking for future wireless systems has its own unique spectrum of features. Specifically, frequent user cooperation and interaction empower mobile users with a new role as mobile service providers, comparing with their traditional role as only the consumers. In this sense, mobile users? cooperation strategy and decisions are sensitive to not only the QoS requirements of the end users? applications but also their own benefits as rewards for providing mobile services. Moreover, the cooperation provided by mobile users does not have to rely heavily on the infrastructure networks. [ABSTRACT FROM AUTHOR]

By grouping a number of adjacent subcarriers into a chunk, resource allocation can be carried out chunk by chunk in orthogonal frequency division multiple access (OFDMA) systems. Chunk-based resource allocation is an effective approach to reduce the complexity of resource allocation in OFDMA systems. In this paper, a chunk-based resource allocation scheme, i.e. joint chunk, power and bit allocation, is proposed and analyzed by maximizing the throughput under a total transmit power constraint. A scaling factor is introduced to achieve optimal allocation. Considering the digital nature of bits per symbol per subcarrier (bits/symbol/subcarrier), a digitization process is proposed to digitize the theoretically allocated bits/symbol/subcarrier to integer. System parameters, such as the power constraint, number of users, coherence bandwidth, number of subcarriers and number of chunks, are introduced and their impacts on the average throughput are studied. The performance of the dynamic power allocation scheme is compared with the fixed power allocation scheme. The numerical results show that the theoretical throughput of the fixed power allocation scheme is quite close to that of the dynamic power allocation scheme. However, when the digital nature of bits/symbol/subcarrier is considered, the average throughput of the dynamic power allocation outperforms the fixed power allocation scheme. [ABSTRACT FROM AUTHOR]

In this paper, we consider deploying an intelligent reflecting surface (IRS) to enhance the downlink (DL) energy transfer and uplink (UL) information transmission efficiency for secure multiple-input multiple-output (MIMO) wireless powered communication networks (WPCNs). We aim to maximize the secrecy throughput of all users by jointly optimizing the DL/UL time allocation, the energy transmit covariance matrix of hybrid access point (AP), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus IRS phase shifts for DL/UL. To tackle the non-convex problem, we first transform the original problem into an equivalent form based on the mean-square error (MSE) method given time allocation, and then apply the alternating algorithm to update the optimization variables iteratively. Specifically, the energy covariance matrix and the information beamforming matrix are obtained based on the dual subgradient method. For the IRS phase shifts, we investigate two IRS beamforming reflection setups, namely different DL/UL IRS beamforming and identical DL/UL IRS beamforming. For the former case, the second-order cone programming technique and the Majorization-Minimization algorithm/element by element iterative algorithm are applied to obtain the DL and UL IRS phase shifts, respectively. For the latter case, the IRS phase shifts are obtained by the successive convex approximation technique. To further reduce the computational complexity of the single-user system, we derive the closed-form solutions of IRS phase shifts in each iteration for the two different reflection setups. Simulation results show that all the proposed algorithms can greatly improve the secrecy throughput compared to the conventional system without IRS. [ABSTRACT FROM AUTHOR]

The paper studies a reconfigurable intelligent surface (RIS)-assisted multi-user uplink massive multiple-input multiple-output (MIMO) system with imperfect hardware. At the RIS, the paper considers phase noise, while at the base station, the paper takes into consideration the radio frequency impairments and low-resolution analog-to-digital converters. The paper derives approximate expressions for the ergodic achievable rate in closed forms under Rician fading channels. For the cases of infinite numbers of antennas and infinite numbers of reflecting elements, asymptotic data rates are derived to provide new design insights. The derived power scaling laws indicate that while guaranteeing a required system performance, the transmit power of the users can be scaled down at most by the factor $\frac{1}{M}$ when $M$ goes infinite, or by the factor $\frac{1}{MN}$ when $M$ and $N$ go infinite, where $M$ is the number of antennas and $N$ is the number of the reflecting units. Furthermore, an optimization algorithm is proposed based on the genetic algorithm to solve the phase shift optimization problem with the aim of maximizing the sum rate of the system. Additionally, the optimization problem with discrete phase shifts is considered. Finally, numerical results are provided to validate the correctness of the analytical results. [ABSTRACT FROM AUTHOR]

Recently, the development of mobile edge computing has enabled exhilarating edge artificial intelligence (AI) with fast response and low communication costs. The location information of edge devices is essential to support the edge AI in many scenarios, like smart home, intelligent transportation systems, and integrated health care. Taking advantage of deep learning intelligence, the centralized machine learning (ML)-based positioning technique has received heated attention from both academia and industry. However, some potential issues, such as location information leakage and huge data traffic, limit its application. Fortunately, a newly emerging privacy-preserving distributed ML mechanism, named federated learning (FL), is expected to alleviate these concerns. In this article, we illustrate a framework of FL-based localization systems as well as the involved entities at edge networks. Moreover, the advantages of such a system are elaborated. On the practical implementation of it, we investigate the field-specific issues associated with system-level solutions, which are further demonstrated over a real-word database. Moreover, future challenging open problems in this field are outlined. [ABSTRACT FROM AUTHOR]

In this paper, a robust uplink transmission scheme combining beamforming (BF) with rate splitting multiple access is proposed to improve the spectrum efficiency of a multibeam satellite system. By assuming that only imperfect channel state information is available, we first formulate an optimization problem to minimize the total transmit power under the constraints of individual transmit power budget and users’ rate requirements. Then, based on the successive convex approximation and difference-of-convex, we present an approach to convert the nonconvex constraints into convex ones, and obtain the BF vectors and power control parameters through iterative procedure. Finally, numerical results confirm the validity and superiority of our proposed scheme. [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 investigate the anti-jamming problem of a directional modulation (DM) system with the aid of intelligent reflecting surface (IRS). As an efficient tool to combat malicious jamming, receive beamforming (RBF) is usually designed by using the statistical properties of the jamming received by Bob. Thus, it is very necessary to estimate the receive jamming covariance matrix (JCM) at Bob. To achieve a precise JCM estimation, three JCM estimation methods, including eigenvalue decomposition (EVD), parametric estimation method by gradient descend (PEM-GD) and parametric estimation method by alternating optimization (PEM-AO), are proposed. Here, the proposed EVD is derived according to the rank-2 constraint of JCM. The PEM-GD method fully explores the structure features of JCM and the PEM-AO is proposed to decrease the computational complexity of the former via dimensionality reduction. The simulation results show that the proposed three methods perform better than directly using sample covariance matrix. Additionally, the proposed PEM-GD and PEM-AO outperform EVD method and the clutter and disturbance covariance estimator RCML. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is a revolutionary technology and can be used to assist communication systems by adaptively manipulating the wireless environment. In this paper, we propose a novel cascaded channel estimation algorithm for the RIS-assisted multiple-input multiple-output orthogonal frequency division multiplexing systems. Inspired by the channel compression idea, we can obtain a sub-sampled channel by turning off a fraction of RIS elements and then extrapolate it to the complete one, by which the pilot overhead is greatly reduced. The problem of channel extrapolation is transformed into recovering the physical parameters of the cascaded channel from the partial channel observations and is then formulated by the sparse Bayesian learning (SBL) framework. In order to circumvent the curse of high dimensional matrices inversion in the vector-matrix system, we further introduce the tensor structure into the SBL framework. Specially, by leveraging of the channel sparsity over the angle domain and delay domain, we derive the virtual channel expression in tensor form and model a Kronecker-structured prior distribution for the virtual channels. The multi-domain sparse properties of the virtual channel tensor can be effectively captured by a group of low-dimensional hyper-parameters, and thus reduce the computational complexity. In addition, the Cramer-Rao lower bound is derived for the proposed channel extrapolation. Simulation results show the superior performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

In secure spatial modulation with a malicious full-duplex attacker, how to obtain the interference subspace or channel state information (CSI) is very important for Bob to reduce or even completely cancel the interference from Mallory. In this paper, different from existing work with perfect CSI, the covariance matrix of malicious interference (CMMI) from Mallory is estimated to construct the interference subspace. To improve the estimation accuracy, a CMMI rank detector relying on the Akaike information criterion (AIC) is derived first. To achieve a high-precision CMMI estimation, two methods, principal component analysis-eigenvalue decomposition (PCA-EVD) and joint diagonalization (JD) are proposed. The proposed PCA-EVD is a rank deduction method whereas the JD method is a joint optimization method with improved performance in the low jamming-to-noise ratio (JNR) region at the expense of increased complexity. Simulation results show that the proposed PCA-EVD performs much better than existing methods like sample estimated covariance matrix (SCM) and EVD in terms of normalized mean square error (NMSE) and secrecy rate (SR). Additionally, the proposed JD has achieved a better NMSE performance than PCA-EVD in the low JNR region (JNR $\leq$ 0 dB) while the proposed PCA-EVD performs better than JD in the high JNR region. [ABSTRACT FROM AUTHOR]

To reduce the signal-to-interference-plus-noise ratio (SINR) loss of analog directional modulation (DM) with finite radio frequency (RF) phase shifters (PSs), a hybrid analog and digital (HAD) DM with mixed PSs is proposed. Using the law of large numbers, the closed-form expressions of SINR performance loss (PL), secrecy rate (SR), and bit error rate (BER) are derived. In accordance with the closed-form expression of SINR loss, it is clear that the SINR PL at desired receiver (Bob) gradually decreases as the fraction $\eta$ of the low-resolution phase shifter decreases, where $\eta$ is defined as the ratio of the number of low-resolution shifters to the total number of shifters. The simulation results show that the SINR PL, SR PL, and BER gradually decrease as the number of quantization bits increases. When the fraction of low-resolution shifters is equal to 50%, 2 bits is sufficient for low-resolution shifters to achieve a SINR PL less than 0.5 dB and a negligible BER degradation. Also, when the number of quantization bits of low-resolution shifters is equal to 2, the SR PL is about 0.3 bits/s/Hz. Thus, compared with analog DM, the HAD DM structure strikes a good balance between PL and circuit cost. [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 a green and secure wireless transmission method, secure spatial modulation is becoming a hot research area. Its basic idea is to exploit both the index of activated transmit antenna and amplitude phase modulation signal to carry messages, improve security, and save energy. In this article, we review its crucial challenges: transmit antenna selection, artificial noise projection, power allocation (PA), and joint detection at the desired receiver. We proposed a low-complexity maximum likelihood (ML) detector, which efficiently reduces the complexity of detection. Meanwhile, for the sake of improving further secrecy rate (SR) performance, a PA strategy is designed on the basis of a deep neural-network (DNN). Simulation results show that the proposed low-complexity ML detector achieves lower complexity but the same bit error rate performance, compared to the traditional ML method, while the proposed DNN method strikes a good balance between complexity and SR performance. [ABSTRACT FROM AUTHOR]

Radio resource allocation is very important in relay orthogonal frequency-division multiple-access (OFDMA) networks. Since perfect channel state information (CSI) is hardly obtained, the robust design that takes into account the CSI imperfection plays a crucial role in the development of efficient resource-allocation schemes. As to the chunk-based resource-allocation scheme, this paper focuses on the imperfect CSI-based resource-allocation problem to jointly optimize the chunk assignment, transmission link selection (direct or relay link), and power allocation in multirelay OFDMA systems. The optimization formulation minimizes the total transmit power with transmission requirement constraints and is considered a mixed-integer optimization problem, and a dual-maximization-based joint resource-allocation algorithm is proposed. The proposed dual-maximization-based algorithm is shown to be optimal. We also develop a low-complexity but near-optimal resource-allocation algorithm. The numerical results validate the performance gains offered by the proposed joint resource-allocation algorithms. The results also show that the impact of imperfect CSI is nonnegligible, which highlights the importance of robust designs in practical wireless networks. [ABSTRACT FROM PUBLISHER]

In this paper, an intelligent reflecting surface (IRS) is deployed to assist the terahertz (THz) communications. The sum-rate of user equipments (UEs) is maximized while guaranteeing the rate requirement of each UE. A block coordinate searching (BCS) algorithm is proposed to jointly optimize the IRS’s coordinates, phase shifts, THz sub-bands allocation and power control. Specifically, the relaxation with penalties based (RPB) algorithm is developed to obtain feasible coordinates of the IRS and guarantee the monotonicity of objective value. In addition, the IRS phase shifts are formulated as closed-form expressions with introduced pricing factors. Simulation results show that the proposed scheme can significantly enhance system performance. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are envisioned to be a disruptive wireless communication technique that is capable of reconfiguring the wireless propagation environment. In this paper, we study a free-space RIS-assisted multiple-input single-output (MISO) communication system in far-field operation. To maximize the received power from the physical and electromagnetic nature point of view, a comprehensive optimization, including beamforming of the transmitter, phase shifts of the RIS, orientation and position of the RIS is formulated and addressed. After exploiting the property of line-of-sight (LoS) links, we derive closed-form solutions of beamforming and phase shifts. For the non-trivial RIS position optimization problem in arbitrary three-dimensional space, a dimensional-reducing theory is proved. The simulation results show that the proposed closed-form beamforming and phase shifts approach the upper bound of the received power. The robustness of our proposed solutions in terms of the perturbation is also verified. Moreover, the RIS significantly enhances the performance of the mmWave/THz communication system. [ABSTRACT FROM AUTHOR]

Multi-UAV passive localization via received signal strength (RSS) is extremely important for wide applications such as rescue and battlefield combat. However, the energy consumption of UAVs is a key issue in this UAVs-enabled application. Usually, the communication overhead plays an important role in the energy consumption. To address this problem, we design two distributed methods for this multi-UAV system with considerable performance under low communication overhead. Firstly, a distributed majorize-minimization (DMM) method is proposed. To accelerate its convergence, a tight upper bound of the objective function from the primary one is derived. Furthermore, a distributed estimation scheme using the Fisher information matrix (DEF) is presented, only requiring one round of communication between edge UAVs and central UAV. Simulation results show that the proposed DMM outperforms the existing distributed iterative methods in terms of root of mean square error (RMSE) under low communication overhead. Moreover, the most communication-effective DEF with local search estimation performs much better than the proposed DMM in terms of RMSE, but has a higher computational complexity. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is of low-cost and energy-efficiency and will be a promising technology for the future wireless communications like sixth generation. To address the problem of conventional directional modulation (DM) that Alice only transmits single confidential bit stream (CBS) to Bob with multiple antennas in a line-of-sight channel, IRS is proposed to create friendly multipaths for DM such that two CBSs can be transmitted from Alice to Bob. This will significantly enhance the secrecy rate (SR) of DM. To maximize the SR (Max-SR), a general non-convex optimization problem is formulated with the unit-modulus constraint of IRS phase-shift matrix (PSM), and the general alternating iterative (GAI) algorithm is proposed to jointly obtain the transmit beamforming vectors (TBVs) and PSM by alternately optimizing one and fixing another. To reduce its high complexity, a low-complexity iterative algorithm for Max-SR is proposed by placing the constraint of null-space (NS) on the TBVs, called NS projection (NSP). Here, each CBS is transmitted separately in the NSs of other CBS and AN channels. Simulation results show that the SRs of the proposed GAI and NSP can approximately double that of IRS-based DM with single CBS for massive IRS in the high signal-to-noise ratio region. [ABSTRACT FROM AUTHOR]

Abstract: The Multi-Carrier Code Division Multiple Access (MC-CDMA) is becoming a very attractive multiple access technique for high-rate data transmission in the future wireless communication systems. This paper is focused on the joint channel and power allocation in the downlink transmission of multi-user MC-CDMA systems and considers the throughput maximization problem as a mixed integer optimization problem. For simple analysis, the problem is divided into two less complex sub-problems: power allocation and channel allocation, which can be solved by a suboptimal Adaptive Power Allocation (APA) algorithm and an optimal Adaptive Channel Allocation (ACA) algorithm, respectively. By combining APA and ACA algorithms, an adaptive channel and power allocation scheme is proposed. The numerical results show that the proposed APA algorithm is more suitable for MC-CDMA systems than the conventional equal power allocation algorithm, and the proposed channel and power allocation scheme can significantly improve the system throughput performance. [Copyright &y& Elsevier]

Spatial domain modulation employs spatial degree of freedom to convey information bits. Traditional spatial domain modulation schemes include spatial modulation, spatial shift keying (SSK), and variations of these two schemes. To fully make use of the spatial degree of freedom and improve the achievable data rate of traditional spatial domain modulation schemes, we propose a successive-coded SSK (SC-SSK) modulation scheme. The core of the proposed SC-SSK scheme is a multiple step coded modulation strategy, in which different information bits are mapped to the designed pattern in each step. The constellation of the transmit signals is designed. A QR decomposition based successive detection algorithm is proposed for this particular coded modulation strategy. The achievable rate, the error rate performance, and the computational complexity of the proposed SC-SSK scheme are analyzed in detail. Simulations are carried out to compare the proposed the SC-SSK scheme with the reference spatial domain modulation schemes, and reveal the advantages of the proposed SC-SSK scheme. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRSs) are regarded as one of the most promising and revolutionizing techniques for enhancing the spectrum and/ or energy efficiency of wireless systems. These devices are capable of reconfiguring the wireless propagation environment by carefully tuning the phase shifts of a large number of low-cost passive reflecting elements. In this article, we aim to answer four fundmental questions: 1) Why do we need RISs? 2) What is an RIS? 3) What are RIS's applications? 4) What are the relevant challenges and future research directions? In response, eight promising research directions are pointed out. [ABSTRACT FROM AUTHOR]

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