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Drones represent a rapidly developing industry. Devices initially designed for military purposes have evolved into a new area with a plethora of commercial applications. One of the biggest hindrances in the commercial developments of drones is legal uncertainty concerning the legal regimes applicable to the multitude of issues that arises with this new technology. This is especially prevalent in situations concerning autonomous drones (ie drones operating without a pilot). This article provides an overview of some of these uncertainties. A scenario based on the fictitious but plausible event of an autonomous drone falling from the sky and injuring people on the ground is analysed from the perspectives of both German and English private law. This working scenario is used to illustrate the problem of legal uncertainty facing developers, and the article provides valuable knowledge by mapping real uncertainties that impede the development of autonomous drone technology alongside providing multidisciplinary insights from law as well as software electronic and computer engineering. [ABSTRACT FROM AUTHOR]

When the users in a MIMO broadcast channel experience different spatial transmit correlation matrices, a class of gains is produced that is denoted transmit correlation diversity. This idea was conceived for channels in which transmit correlation matrices have mutually exclusive eigenspaces, allowing non-interfering training and transmission. This paper broadens the scope of transmit correlation diversity to the case of partially and fully overlapping eigenspaces and introduces techniques to harvest these generalized gains. For the two-user MIMO broadcast channel, we derive achievable degrees of freedom (DoF) and achievable rate regions with/without channel state information at the receiver (CSIR). When CSIR is available, the proposed achievable DoF region is tight in some configurations of the number of receive antennas and the channel correlation ranks. We then extend the DoF results to the $K$ -user case by analyzing the interference graph that characterizes the overlapping structure of the eigenspaces. Our achievability results employ a combination of product superposition in the common part of the eigenspaces, and pre-beamforming (rate splitting) to create multiple data streams in non-overlapping parts of the eigenspaces. Massive MIMO is a natural example in which spatially correlated link gains are likely to occur. We study the achievable downlink sum rate for a frequency-division duplex massive MIMO system under transmit correlation diversity. [ABSTRACT FROM AUTHOR]

The channel state information at the transmitter (CSIT) play an important role in the performance of wireless networks. The CSIT model can be delayed and imperfect‐quality, since the feedback link has a delay and the channel state information (CSI) feedback has distortion. In this paper, the degrees‐of‐freedom (DoF) region of the two‐user multiple‐input multiple‐output (MIMO) broadcast channel are characterised with delayed imperfect‐quality CSIT, where the antenna configurations can be arbitrary. The converse proof of DoF region is based on the enhancement of physically degraded channel. The achievability proof of DoF region is through a novel transmission scheme design, where the duration of each phase and the amount of transmitted symbols are configured based on the imperfect‐quality of delayed CSIT. As a result, it is shown that the DoF region with delayed imperfect‐quality CSIT is located between the DoF region with no CSIT and the DoF region with delayed CSIT. [ABSTRACT FROM AUTHOR]

The purpose of person re-identification (ReID) is to find the same person under different cameras and the basic difficulty lies in the need for large amounts of cross-camera pedestrian annotations. In reality, annotating cross-camera pedestrians is time-consuming especially in large-scale surveillance camera networks. This paper focuses on addressing the ReID problem under single-camera training (SCT) setting, where each person of the training set only appears in one camera. Due to the lack of cross-camera pedestrian annotations, it is difficult to effectively eliminate the camera style interference by narrowing the distance between the image features of the same person. To address this problem, we propose a close-set camera style distribution alignment (C2SDA) framework for SCT ReID. In order to reduce the camera-style interference from both instance- and distribution-levels simultaneously, we first design an instance-distribution camera style alignment module that directly aligns the feature distribution of input images under each camera and then trains the model at instance level with the aligned features. Secondly, we further design an augment close-set camera style distribution module that transforms the camera feature distribution alignment problem from open-set into close-set one, which preserving the discriminative ability of features during the alignment process. Experimental results verify that our framework can significantly improve the ReID performance under SCT setting and surpass the current SOTA methods. The source code is available at https://github.com/HongweiZhang97/CCSDA. [ABSTRACT FROM AUTHOR]

This paper addresses the optimization of distributed compression in a sensor network with partial cooperation among sensors. The widely known Chief Executive Officer (CEO) problem, where each sensor has to compress its measurements locally in order to forward them over capacity limited links to a common receiver is extended by allowing sensors to mutually communicate. This extension comes along with modified statistical dependencies among involved random variables compared to the original CEO problem, such that well-known outer and inner bounds do not hold anymore. Three different inter-sensor communication protocols are investigated. The successive broadcast approach allows each sensor to exploit instantaneous side-information of all previously transmitting sensors. As this leads to dimensionality problems for larger networks, a sequential point-to-point communication scheme is considered forwarding instantaneous side-information to only one successor. Thirdly, a two-phase transmission protocol separates the information exchange between sensors and the communication with the common receiver. Inspired by algorithmic solutions for the original CEO problem, the sensors are optimized in a greedy manner. It turns out that partial communication among sensors improves the performance significantly. In particular, the two-phase transmission can reach the performance of a fully cooperative CEO scenario, where each sensor has access to all measurements and the knowledge about all channel conditions. Moreover, exchanging instantaneous side-information increases the robustness against bad Wyner–Ziv coding strategies, which can lead to significant performance losses in the original CEO problem. [ABSTRACT FROM AUTHOR]

This paper studies the precoder design problem of achieving max-min fairness (MMF) amongst users in multigateway multibeam satellite communication systems with feeder link interference. We propose a beamforming strategy based on a newly introduced transmission scheme known as rate-splitting multiple access (RSMA). RSMA relies on multi-antenna rate-splitting at the transmitter and successive interference cancellation (SIC) at the receivers, such that the intended message for a user is split into a common part and a private part and the interference is partially decoded and partially treated as noise. In this paper, we formulate the MMF problem subject to per-antenna power constraints at the satellite for the system with imperfect channel state information at the transmitter (CSIT). We also consider the case of two-stage precoding which is assisted by on- board processing (OBP) at the satellite. Numerical results obtained through simulations for RSMA and the conventional linear precoding method are compared. When RSMA is used, MMF rate gain is promised and this gain increases when OBP is used. RSMA is proven to be promising for multigateway multibeam satellite systems whereby there are various practical challenges such as feeder link interference, CSIT uncertainty, per-antenna power constraints, uneven user distribution per beam and frame-based processing. [ABSTRACT FROM AUTHOR]

We consider the $K$ -user Multiple Input Multiple Output (MIMO) Gaussian interference channel with $M$ antennas at each transmitter and $N$ antennas at each receiver. It is assumed that channel coefficients are constant real numbers and are available at all transmitters and at all receivers. The main objective of this paper is to characterize the number of Degrees of Freedom (DoF) of this channel. Using the real interference alignment technique introduced in Motahari et al., 2014, we show that $\frac {MN}{M+N} K$ degrees of freedom can be achieved for almost all channel realizations. Also, a new upper-bound on the DoF of this channel is provided. This upper-bound coincides with our achievable DoF for $K\geq K_{u} \triangleq \frac {M+N}{\gcd (M,N)}$ , where $\gcd (M,N)$ denotes the greatest common divisor of $M$ and $N$. This gives an exact characterization of DoF for $M\times N$ MIMO Gaussian interference channel in the case of $K\geq K_{u}$. Since there is no cooperation between transmit (or receive) antennas of each user in our transmission scheme, this result shows that the DoF benefit of joint processing in collocated antennas vanishes when the number of users is greater than a certain threshold. [ABSTRACT FROM AUTHOR]

Resistive random-access memory is one of the most promising candidates for the next generation of non-volatile memory technology. However, its crossbar array structure causes severe “sneak-path” interference, which also leads to strong inter-cell correlation. Recent works have mainly focused on sub-optimal data detection schemes by ignoring inter-cell correlation and assuming sneak-path interference is independent between different array cells. In this paper, we propose a near-optimal data detection scheme that can approach the performance bound of the optimal detection scheme. Our detection scheme leverages a joint data and sneak-path interference recovery and can use all inter-cell correlations. The proposed scheme is suitable for data detection of large memory arrays with only linear operation complexity. [ABSTRACT FROM AUTHOR]

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

Person Re-identification (Re-ID) has attracted more and more attention thanks to its great practical value in the field of video surveillance. Most works have focused on solving the problem of supervised Re-ID on a single domain and made significant progress. However, the cross-domain Re-ID is still challenging due to the domain bias between the source and target domains. To this end, we propose a dictionary learning algorithm based on matrix factorization to eliminate the influence of style and pedestrian pose information on the cross-domain Re-ID. Specifically, the proposed approach includes two novel parts: (1) the original visual feature is decomposed into pose-invariant feature space, camera-style feature space and residual feature space to extract discriminant pose-invariant feature that is not affected by style and pedestrian pose information, such that the influence of interference information between pedestrians on recognition can be eliminated; (2) considering the domain-invariance of attribute, a hypergraph structure alignment is introduced to integrate pose-invariant feature, attribute and pedestrian identity into a dictionary learning framework. The relationship between pose-invariant feature and attribute is built so that the pedestrian attribute of the target dataset can be accurately predicted during testing. Finally, the pedestrian similarity measurement can be carried out by combining the pose-invariant feature and attribute of pedestrians. The effectiveness of the proposed algorithm is verified with the experiments on several benchmark Re-ID datasets. [ABSTRACT FROM AUTHOR]

Background: Amplicon sequencing of marker genes such as 16S rDNA have been widely used to survey and characterize microbial community. However, the complex data analyses have required many interfering manual steps often leading to inconsistencies in results. Results: Here, we have developed a pipeline, amplicon sequence analysis pipeline 2 (ASAP 2), to automate and glide through the processes without the usual manual inspections and user's interference, for instance, in the detection of barcode orientation, selection of high-quality region of reads, and determination of resampling depth and many more. The pipeline integrates all the analytical processes such as importing data, demultiplexing, summarizing read profiles, trimming quality, denoising, removing chimeric sequences and making the feature table among others. The pipeline accepts multiple file formats as input including multiplexed or demultiplexed, paired-end or single-end, barcode inside or outside and raw or intermediate data (e.g. feature table). The outputs include taxonomic classification, alpha/beta diversity, community composition, ordination analysis and statistical tests. ASAP 2 supports merging multiple sequencing runs which helps integrate and compare data from different sources (public databases and collaborators). Conclusions: Our pipeline minimizes hands-on interference and runs amplicon sequence variant (ASV)-based amplicon sequencing analysis automatically and consistently. Our web server assists researchers that have no access to high performance computer (HPC) or have limited bioinformatics skills. The pipeline and web server can be accessed at https://github.com/tianrenmaogithub/asap2 and https://hts.iit.edu/asap2, respectively. [ABSTRACT FROM AUTHOR]

In urban UAV networks, UAVs deployment locations and air-to-ground (AtG) communication links will possibly conflict with densely located buildings, which exacerbate network irregularity and make interference management more complicated. This paper proposes interference coordination via power control under 3D blockage effects in urban environments, where buildings are distributed according to Boolean model with heights ($H_k$) followed Rayleigh distribution. Specifically, a dynamic UAV group (UAVG) is organized to serve each user for interference coordination, which consists several nearest visible UAVs with line-of-sight (LOS) connections considering buildings blockage effects, and the modified distribution from user to its nearest unblocked UAV is derived. Power control is executed in UAVG where adjacent interfering UAVs within the group will mute their transmission for interference mitigation, and optimal UAVG radius coefficient $\mu$ is obtained, which reveals the trade-off between interference mitigation and resource utilization. Leveraging stochastic geometry, theoretical expressions of network metrics are derived with Nakagami- $m$ fading assumption, including network coverage probability and network connectivity. Analytical results show that in urban city scenario, comparing with traditional terrestrial networks, coverage performance can achieve 4.1× gain by deploying UAVs with optimal height, and achieve additional 26 $\%$ gain with respect to scenarios where power control is disabled. [ABSTRACT FROM AUTHOR]

We propose new transmission schemes and receiver algorithms for unsourced multiple access (UMA) in MIMO and massive MIMO channels. Each active transmitter’s information bits are first channel encoded. The coded bits are divided into sub-blocks and each sub-block is modulated and transmitted. For both MIMO and massive MIMO channels, the conventional nonlinear modulation can be employed where each sub-block of coded bits is mapped to a transmitted signal vector. For the massive MIMO channel, we propose a new hybrid modulation scheme to reduce the receiver complexity, where the first sub-block is nonlinearly modulated, and the subsequent sub-blocks are linearly modulated and spread by the first sub-block signal. We also propose sparsity-exploiting blind receiver algorithms. Specifically, for the MIMO case, we exploit the codeword sparsity inherent in the UMA system, and a channel clustering technique, to estimate the channel and the transmitted signal of each transmitter. For the massive MIMO, in addition to the codeword sparsity, we further exploit the channel sparsity and user sparsity in estimating the channel and transmitted signal of each transmitter. The proposed receiver algorithms for both MIMO and massive MIMO channels output either hard or soft estimates of the coded bits, and therefore single-user channel decoding of the information bits can be performed for each transmitter. Extensive simulation results are provided to demonstrate the performances of the proposed algorithms. [ABSTRACT FROM AUTHOR]

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC certainly results in a suboptimal solution while an exhaustive search method comes at the cost of high complexity, especially for systems of medium-to-large size. To address this problem, we develop two efficient unsupervised machine learning based UC algorithms, namely k-means++ and improved k-means++, to effectively cluster users into disjoint clusters in cell-free massive multiple-input multiple-output (CFmMIMO) system. Adopting full-pilot zero-forcing at access points (APs) to comprehensively assess the system performance, we formulate the sum SE optimization problem taking into account power constraints at APs, necessary conditions for implementing successive interference cancellation, and required SE constraints at user equipments. The formulated optimization problem is highly non-convex, and thus, it is difficult to obtain the global optimal solution. Therefore, we develop a simple yet efficient iterative algorithm for its solution. In addition, the performance of collocated massive MIMO-NOMA (COmMIMO-NOMA) system is also characterized. Numerical results are provided to show the superior performance of the proposed UC algorithms compared to baseline schemes. The effectiveness of applying NOMA in CFmMIMO and COmMIMO systems is also validated. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we consider the transmission over multiple access relay channel (MARC) in which the relay operates in half‐duplex mode. The main contribution of this paper is establishing the capacity of the multiple access half‐duplex relay channel (MAHRC). Toward achieving this goal, we first derive a new achievable rate region. While deriving the achievable rate region, well‐known encoding and decoding schemes, which are used for transmission and reception over the degraded broadcast channel and the multiple access channel, are used. In this transmission scheme, the transmission from the two sources via the half‐duplex relay, to the destination, is split into two phases. Afterwards, an outer bound to the transmission over the discrete memoryless MAHRC is developed. Consequently, we show that the achievable rate region matches the outer bound and therefore the capacity region is formed. Further, the capacity region is extended to the case of Gaussian channel. Additionally, many numerical examples are shown to validate our theoretical derivations. In particular, these numerical examples show that the achievable rate region, and then the capacity, that we derive is larger than the well‐known results in the literature. [ABSTRACT FROM AUTHOR]

The robust principles of treating interference as noise (TIN) when it is sufficiently weak, and avoiding it when it is not, form the background of this work. Combining TIN with the topological interference management (TIM) framework that identifies optimal interference avoidance schemes, we formulate a TIM-TIN problem for multilevel topological interference management, wherein only a coarse knowledge of channel strengths and no knowledge of channel phases is available to transmitters. To address the TIM-TIN problem, we first propose an analytical baseline approach, which decomposes a network into TIN and TIM components, allocates the signal power levels to each user in the TIN component, allocates signal vector space dimensions to each user in the TIM component, and guarantees that the product of the two is an achievable number of signal dimensions available to each user in the original network. Next, a distributed numerical algorithm called ZEST is developed. The convergence of the algorithm is demonstrated, leading to the duality of the TIM-TIN problem in terms of generalized degrees-of-freedom (GDoF). Numerical results are also provided to demonstrate the superior sum-rate performance and fast convergence of ZEST. [ABSTRACT FROM AUTHOR]

We formulate and study the problem of ON-OFF privacy. ON-OFF privacy algorithms enable a user to continuously switch his privacy between ON and OFF. An obvious example is the incognito mode in internet browsers. But beyond internet browsing, ON-OFF privacy can be a desired feature in most online applications. The challenge is that the statistical correlation over time of a user’s online behavior can lead to leakage of information. We consider the setting in which a user is interested in retrieving the latest message generated by one of $N$ sources. The user’s privacy status can change between ON and OFF over time. When privacy is ON the user wants to hide his request. Moreover, since the user’s requests depend on personal attributes such as age, gender, and political views, they are typically correlated over time. As a consequence, the user cannot simply ignore privacy when privacy is OFF. We model the correlation between user’s requests by an $N$ state Markov chain. The goal is to design query schemes with optimal download rate, that preserve privacy in an ON-OFF privacy setting. In this paper, we present inner and outer bounds on the achievable download rate for $N$ sources. We also devise an efficient algorithm to construct an ON-OFF privacy scheme achieving the inner bound and prove its optimality in the case $N=2$ sources. For $N > 2$ , finding tighter outer bounds and efficient constructions of ON-OFF privacy schemes that would achieve them remains an open question. [ABSTRACT FROM AUTHOR]

Uplink-downlink duality refers to the fact that under a sum-power constraint, the capacity regions of a Gaussian multiple-access channel and a Gaussian broadcast channel with Hermitian transposed channel matrices are identical. This paper generalizes this result to a cooperative cellular network, in which remote access-points are deployed as relays in serving the users under the coordination of a central processor (CP). In this model, the users and the relays are connected over noisy wireless links, while the relays and the CP are connected over noiseless but rate-limited fronthaul links. Based on a Lagrangian technique, this paper establishes a duality relationship between such a multiple-access relay channel and broadcast relay channel, under the assumption that the relays use compression-based strategies. Specifically, we show that under the same total transmit power constraint and individual fronthaul rate constraints, the achievable rate regions of the Gaussian multiple-access and broadcast relay channels are identical, when either independent compression or Wyner-Ziv and multivariate compression strategies are used. The key observations are that if the beamforming vectors at the relays are fixed, the sum-power minimization problems under the achievable rate and fronthaul constraints in both the uplink and the downlink can be transformed into either a linear programming or a semidefinite programming problem depending on the compression technique, and that the uplink and downlink problems are Lagrangian duals of each other. Moreover, the dual variables corresponding to the downlink rate constraints become the uplink powers; the dual variables corresponding to the downlink fronthaul constraints become the uplink quantization noises. This duality relationship enables an efficient algorithm for optimizing the downlink transmission and relaying strategies based on the uplink. [ABSTRACT FROM AUTHOR]

Unsourced random-access (U-RA) is a type of grant-free random access with a virtually unlimited number of users, of which only a certain number $K_{a}$ are active on the same time slot. Users employ exactly the same codebook, and the task of the receiver is to decode the list of transmitted messages. We present a concatenated coding construction for U-RA on the AWGN channel, in which a sparse regression code (SPARC) is used as an inner code to create an effective outer OR-channel. Then an outer code is used to resolve the multiple-access interference in the OR-MAC. We propose a modified version of the approximate message passing (AMP) algorithm as an inner decoder and give a precise asymptotic analysis of the error probabilities of the AMP decoder and of a hypothetical optimal inner MAP decoder. This analysis shows that the concatenated construction under optimal decoding can achieve a vanishing per-user error probability in the limit of large blocklength and a large number of active users at sum-rates up to the symmetric Shannon capacity, i.e. as long as $K_{a}R < 0.5\log _{2}(1+K_{a} { \mathsf {SNR}})$. This extends previous point-to-point optimality results about SPARCs to the unsourced multiuser scenario. Furthermore, we give an optimization algorithm to find the power allocation for the inner SPARC code that minimizes the ${\mathsf {SNR}}$ required to achieve a given target per-user error probability with the AMP decoder. [ABSTRACT FROM AUTHOR]

The optimal spectral efficiency and the number of independent channels for multiple-input–multiple-output (MIMO) antennas in isotropic multipath channels are investigated when bandwidth requirements are placed on the antenna. By posing the problem as a convex optimization problem restricted by the port Q-factor, a semianalytical expression is formed for its solution. The antennas are simulated by method of moments, and the solution is formulated both for structures fed by discrete ports and for design regions characterized by an equivalent current. It is shown that the solution is solely dependent on the eigenvalues of the so-called energy modes of the antenna. The magnitude of these eigenvalues is analyzed for a linear dipole array and a plate with embedded antenna regions. The energy modes are also compared to the characteristic modes to validate characteristic modes as a design strategy for MIMO antennas. The antenna performance is illustrated through spectral efficiency over the Q-factor, a quantity that is connected to the capacity. It is proposed that the number of energy modes below a given Q-factor can be used to estimate the degrees of freedom for that Q-factor. [ABSTRACT FROM AUTHOR]

In this paper, the sum-rate maximization problem is studied for wireless networks that use downlink rate splitting multiple access (RSMA). In the considered model, the base station (BS) divides the messages that can be transmitted to its users into a “private” part and a “common” part. Here, the common message is a message that multiple users want to receive and the private message is a message that is dedicated to only a specific user. The RSMA mechanism enables a BS to adjust the split of common and private messages so as to control the interference by decoding and treating interference as noise and, thus optimizing the data rate of users. To maximize the users’ sum-rate, the network can determine the rate allocation for the common message to meet the rate demand, and adjust the transmit power for the private message to reduce the interference. This problem is formulated as an optimization problem whose goal is to maximize the sum-rate of all users. To solve this nonconvex maximization problem with a single-antenna BS, the optimal power used for transmitting the private message to the users is first obtained in closed form for a given rate allocation and common message power. Based on the optimal private message transmit power, the optimal rate allocation is then derived under a fixed common message transmit power. Subsequently, an iterative algorithm is proposed to obtain a suboptimal solution of common message transmit power. To solve this nonconvex maximization problem with a multiple-antenna BS, a successive convex approximation method is utilized. Simulation results show that the RSMA can achieve up to 15.6% and 21.5% gains in terms of data rate compared to non-orthogonal multiple access (NOMA) and orthogonal frequency-division multiple access (OFDMA), respectively. [ABSTRACT FROM AUTHOR]

This work does the statistical quality-of-service (QoS) analysis of a block-fading device-to-device (D2D) link in a multi-tier cellular network that consists of a macro-BS ($BS_{_{MC}}$) and a micro-BS ($BS_{_{mC}}$) which both operate in full-duplex (FD) mode. For the D2D link under consideration, we first formulate the mode selection problem—whereby D2D pair could either communicate directly, or, through the $BS_{_{mC}}$ , or, through the $BS_{_{MC}}$ —as a ternary hypothesis testing problem. Next, to compute the effective capacity (EC) for the given D2D link, we assume that the channel state information (CSI) is not available at the transmit D2D node, and hence, it transmits at a fixed rate $r$ with a fixed power. This allows us to model the D2D link as a Markov system with six-states. We consider both overlay and underlay modes for the D2D link. Moreover, to improve the throughput of the D2D link, we assume that the D2D pair utilizes two special automatic repeat request (ARQ) schemes, i.e., Hybrid-ARQ (HARQ) and truncated HARQ. Furthermore, we consider two distinct queue models at the transmit D2D node, based upon how it responds to the decoding failure at the receive D2D node. Eventually, we provide closed-form expressions for the EC for both HARQ-enabled D2D link and truncated HARQ-enabled D2D link, under both queue models. Noting that the EC looks like a quasi-concave function of $r$ , we further maximize the EC by searching for an optimal rate via the gradient-descent method. Simulation results provide us the following insights: i) EC decreases with an increase in the QoS exponent, ii) EC of the D2D link improves when HARQ is employed, iii) EC increases with an increase in the quality of self-interference cancellation techniques used at $BS_{_{mC}}$ and $BS_{_{MC}}$ in FD mode. [ABSTRACT FROM AUTHOR]

In this paper, we consider a general K-user Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). We assume that the channel state is deterministic and known to all the nodes. While the private-message capacity region is well known to be achievable with dirty paper coding (DPC), we are interested in the simpler linearly precoded transmission schemes. In particular, we focus on linear precoding schemes combined with rate-splitting (RS). First, we derive an achievable rate region with minimum mean square error (MMSE) precoding at the transmitter and joint decoding of the sub-messages at the receivers. Then, we study the achievable sum rate of this scheme and obtain two findings: 1) an analytically tractable upper bound on the sum rate that is shown numerically to be a close approximation, and 2) how to reduce the number of active streams – crucial to the overall complexity – while preserving the sum rate to within a constant loss. The latter results in two practical algorithms: a stream elimination algorithm and a stream ordering algorithm. Finally, we investigate the constant-gap optimality of linearly precoded RS with respect to the capacity. Our result reveals that, while the achievable rate of linear precoding alone can be arbitrarily far from the capacity, the introduction of RS can help achieve the capacity region to within a constant gap in the two-user case. Nevertheless, we prove that the RS scheme’s constant-gap optimality does not extend to the three-user case. Specifically, we show, through a pathological example, that the gap between the sum rate and the sum capacity can be unbounded. [ABSTRACT FROM AUTHOR]

The fundamental capacity limits of intelligent reflecting surface (IRS)-assisted multi-user wireless communication systems are investigated in this article. Specifically, the capacity and rate regions for both capacity-achieving non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) transmission schemes are characterized by jointly optimizing the IRS reflection matrix and wireless resource allocation under the constraints of a maximum number of IRS reconfiguration times. In NOMA, all users are served in the same resource blocks by employing superposition coding and successive interference cancelation techniques. In OMA, all users are served by being allocated orthogonal resource blocks of different sizes. For NOMA, the ideal case with an asymptotically large number of IRS reconfiguration times is firstly considered, where the optimal solution is obtained by employing the Lagrange duality method. Inspired by this result, an inner bound of the capacity region for the general case with a finite number of IRS reconfiguration times is derived. For OMA, the optimal transmission strategy for the ideal case is to serve each individual user alternatingly with its effective channel power gain maximized. Based on this result, a rate region inner bound for the general case is derived. Finally, numerical results are provided to show that: i) a significant capacity and rate region improvement can be achieved by using IRS; ii) the capacity gain can be further improved by dynamically configuring the IRS reflection matrix. [ABSTRACT FROM AUTHOR]

In wireless networks, link strengths are often affected by some topological factors such as propagation path loss, shadowing and inter-cell interference. Thus, different users in the network might experience different link strengths. In this work we consider a K-user asymmetric interference channel, where the channel gains of the links connected to Receiver k are scaled with √Pαk, k = 1,2, ⋅⋅⋅ , K , for 0 < α1 ≤ α2 ≤ ⋅⋅⋅ ≤ αK. For this setting, we show that the optimal sum generalized degrees-of-freedom (GDoF) is characterized as dsum = ∑k=1K αk + αK− αK−1/2 which matches the existing result d∑ = K/2 when α1 = α2 = ⋅⋅⋅ = αK = 1. The achievability is based on multi-layer interference alignment, where different interference alignment sub-schemes are designed in different layers associated with specific power levels, and successive decoding is applied at the receivers. While the converse for the symmetric case only requires bounding the sum degrees-of-freedom (DoF) for selected two users, the converse for this asymmetric case involves bounding the weighted sum GDoF for selected J + 2 users, with corresponding weights (2J, 2J−1, ⋅⋅⋅ , 22, 21), a geometric sequence with common ratio 2, for the first J users and with corresponding weights (1, 1) for the last two users, for J ∈ {1,2, ⋅⋅⋅ , ⌈log K/2⌉. [ABSTRACT FROM AUTHOR]

The photon's frequency degree of freedom, being compatible with mature telecom infrastructure, offers large potential for the stable and controllable realization of photonic quantum processing applications such as the quantum internet. The Hong–Ou–Mandel effect, as a two‐photon interference phenomenon, serves as a central building block for such frameworks. A key element yet missing to enable meaningful frequency‐based implementations as well as scalability in the number of processed photons, is the demonstration of the Hong–Ou–Mandel effect between independently created photons of different frequencies. The experimental implementation of bosonic and fermionic frequency domain Hong–Ou–Mandel interference between independently generated single photons is reported here, with measured visibilities of 74.31% ± 3.56% and 86.44% ± 8.27%, respectively. This is achieved through a scalable photonic frequency circuit that creates two post‐selected pure single photons, which undergo frequency mixing at an electro‐optic phase modulator. The system is on‐the‐fly reconfigurable allowing to probe bosonic and fermionic Hong–Ou–Mandel interference in the same experimental setup. The work demonstrates the versatility of frequency domain processing and its scalability toward higher photon numbers, which enables new quantum gate concepts as well as the establishment of frequency‐based large‐scale quantum networks. [ABSTRACT FROM AUTHOR]

This paper studies distributed power control for the uplink of multi-cell non-orthogonal multiple access (NOMA) systems. Within a cell, the transmissions of different users are modeled as a Gaussian multiple access channel, treating inter-cell interference as additive Gaussian noise. By analyzing the geometry of the feasible power region, using successive interference cancellation at each base station is proved to be optimal in minimizing the total transmission power of all users under rate constraints. The decoding order at each base station, however, remains to be determined. If the decoding order is decided without base station cooperation, the overall control algorithm is fully distributed but is suboptimal in general. To achieve optimality, a partially distributed algorithm is designed, which requires base stations to exchange control messages. Given any feasible instance, the algorithm is proved to converge to the optimal solution. The performance of the fully distributed and partially distributed power control algorithms is compared by computer simulations. The fully distributed algorithm is nearly optimal in terms of outage probability. When a high data rate is required, the partially distributed algorithm is able to reduce the total power consumption by about 20%. [ABSTRACT FROM AUTHOR]

We study the problem of strong coordination of the actions of two nodes X and Y that communicate over a discrete memoryless channel (DMC) such that the actions follow a prescribed joint probability distribution. We propose two novel random coding schemes and a polar coding scheme for this noisy strong coordination problem, and derive inner and outer bounds for the respective strong coordination capacity region. The first scheme is a joint coordination-channel encoding scheme that utilizes the randomness provided by the communication channel to reduce the amount of local randomness required to generate the sequence of actions at Node Y. Based on this random coding scheme, we provide a characterization of the capacity region for a special case of the noisy strong coordination setup, namely, when the DMC is a deterministic channel. The second scheme exploits separate coordination and channel encoding where local randomness is extracted from the channel after decoding. Moreover, by leveraging the random coding results for this problem, we present an example in which the proposed joint encoding scheme is able to strictly outperform the separate encoding scheme in terms of achievable communication rate for the same amount of injected randomness into both systems. Thus, we establish the sub-optimality of the separation of strong coordination and channel encoding with respect to the communication rate over the DMC in this problem. Finally, the third scheme is a joint coordination-channel polar coding scheme for strong coordination. We show that polar codes are able to achieve the established inner bound to the strong noisy coordination capacity region and thus provide a constructive alternative to a random coding proof. Our polar coding scheme also offers a constructive solution to a channel simulation problem where a DMC and shared randomness are employed together to simulate another DMC. [ABSTRACT FROM AUTHOR]

For the two-user multiple-input multiple-output (MIMO) broadcast channel with delayed channel state information at the transmitter (CSIT) and arbitrary antenna configurations, all the degrees-of-freedom (DoF) regions are obtained. However, for the three-user MIMO broadcast channel with delayed CSIT and arbitrary antenna configurations, the DoF region of order-2 messages is still unclear and only a partial achievable DoF region of order-1 messages is obtained, where the order-2 messages and order-1 messages are desired by two receivers and one receiver, respectively. In this paper, for the three-user MIMO broadcast channel with delayed CSIT and arbitrary antenna configurations, we first design transmission schemes for order-2 messages and order-1 messages. Next, we propose to analyze the achievable DoF region of transmission scheme by transformation approach. In particular, we transform the decoding condition of transmission scheme w.r.t. phase duration into the achievable DoF region w.r.t. achievable DoF, through achievable DoF tuple expression connecting phase duration and achievable DoF. As a result, the DoF region of order-2 messages is characterized and an achievable DoF region of order-1 messages is completely expressed. Besides, for order-1 messages, we derive the sufficient condition, under which the proposed achievable DoF region is the DoF region. [ABSTRACT FROM AUTHOR]

The best-known achievable rate region for the two-user Gaussian interference channel corresponds to the Han-Kobayashi scheme. However, mathematical expressions that characterize the Han-Kobayashi rate region are complicated. This complexity hinders a comprehensive understanding of the rate region. For instance, when interference is weak, the maximum achievable sum-rate of the Han-Kobayashi scheme has been unknown. This paper studies the sum-rate of the Han-Kobayashi scheme with Gaussian inputs and fully characterizes the maximum achievable sum-rate, when no time sharing is used. The optimal power-splitting variables and the corresponding maximum achievable sum-rate are explicitly expressed in closed forms. With the same approach, the maximum weighted sum-rate is expressed that characterizes the boundary of the Han-Kobayashi region without time sharing. Moreover, when time sharing is used, the boundary is expressed in terms of the upper concave envelope of a function of transmitters’ powers. [ABSTRACT FROM AUTHOR]

In communication networks secrecy constraints usually incur an extra limit in capacity or generalized degrees-of-freedom (GDoF), in the sense that a penalty in capacity or GDoF is incurred due to the secrecy constraints. Over the past decades a significant amount of effort has been made by the researchers to understand the limits of secrecy constraints in communication networks. In this work, we focus on how to remove the secrecy penalty in communication networks, i.e., how to remove the GDoF penalty due to secrecy constraints. We begin with three basic settings: a two-user symmetric Gaussian interference channel with confidential messages, a symmetric Gaussian wiretap channel with a helper, and a two-user symmetric Gaussian multiple access wiretap channel. Interestingly, in this work we show that adding common randomness at the transmitters can totally remove the penalty in GDoF or GDoF region of the three settings considered here. The results reveal that adding common randomness at the transmitters is a powerful way to remove the secrecy penalty in communication networks in terms of GDoF performance. Common randomness can be generated offline before the real-time message communication. The role of the common randomness is to jam the information signal at the eavesdroppers, without causing too much interference at the legitimate receivers. To accomplish this role, a new method of Markov chain-based interference neutralization is proposed in the achievability schemes utilizing common randomness. From the practical point of view, we need to minimize the amount of common randomness used for removing the secrecy penalty in terms of GDoF performance. With this motivation, for most of the cases we characterize the minimal GDoF of common randomness to remove secrecy penalty, based on our derived converses and achievability. [ABSTRACT FROM AUTHOR]

Ultra-dense heterogeneous networks (UDHNs) have been widely regarded as a promising solution to enhance the reuse efficiency of spatial frequency and thus improve the overall network performance. In such networks, a load balancing problem caused by coexisting macrocells and small cells should be treated seriously, which means some effective user associations are essential for load balancing. To this end, we design two types of offloading (load balancing) schemes for UDHNs to maximize a logarithmic utility of long-term rates. To guarantee the load balancing gain, a frequency partitioning scheme is designed to degrade the cross-plane interference, and a time partitioning strategy is developed to eliminate the strong interference received by some users offloaded from macrocells. In these offloading schemes, the main difference between them is whether a time partitioning factor needs to be optimized. As for the problems formulated in these schemes, we design a distributed algorithm by utilizing dual decomposition and develop a centralized algorithm with a two-layer iteration. Then, we give some detailed convergence and complexity analyses for them. Numerical results show that the proposed schemes yield some significant performance gains relative to some traditional ones, and the centralized algorithm often achieves a better association performance than a distributed one since the former almost always tries to optimize a time partitioning factor. [ABSTRACT FROM AUTHOR]

Orthogonal time frequency space (OTFS) is a two-dimensional modulation scheme realized in the delay-Doppler domain, which targets the robust wireless transmissions in high-mobility environments. In such scenarios, OTFS signal suffers from multipath channel with continuous Doppler spread, which results in significant inter-symbol interference and inter-Doppler interference (IDI). In this article, we analyze the interference generation mechanism, and compare statistical distributions of the IDI in two typical cases, i.e., limited-Doppler-shift channel and continuous-Doppler-spread channel (CoDSC). Focusing on the OTFS signal transmission over the CoDSC, our study firstly indicates that the widespread IDI incurs a computational burden for the element-wise detector like the message passing in the state-of-the-art works. Addressing this challenge, we propose a block-wise OTFS receiver by exploiting the structure and characteristics of the OTFS transmission matrix. In the receiver, we deliberately design an iteration strategy among the least squares minimum residual based channel equalizer, reliability-based symbol detector and interference eliminator, which can realize fast convergence by leveraging the sparsity of channel matrix. The simulations demonstrate that, in the CoDSC, the proposed scheme achieves much less detection error, and meanwhile reduces the computational complexity by an order of magnitude, compared with the state-of-the-art OTFS receivers. [ABSTRACT FROM AUTHOR]

Most coding schemes proposed for the interference channel take advantage of joint decoding to enlarge rate region. However, decoding complexity escalates considerably when joint decoding is used. This paper studies the achievable sum-rate of the two-user Gaussian interference channel when joint decoding is replaced by successive decoding. First, the strong interference class is examined, and it is proved that if transmitters’ powers satisfy certain conditions, successive decoding is optimal and achieves the sum-capacity. The number of the required splits, the amount of power allocated to each split, and the order of decoding at receivers are explicitly determined. Second, the weak interference class is examined. A novel rate-splitting scheme is proposed that does not use joint decoding. The number of required splits and the amount of power allocated to each split are expressed in closed forms. It is shown that, for a wide range of transmitters’ powers, this scheme achieves the sum-rate of the Gaussian Han-Kobayashi scheme. Moreover, it is proved that the difference between the sum-rate of this scheme and that of the Gaussian Han-Kobayashi scheme is bounded, for all values of transmitters’ powers. [ABSTRACT FROM AUTHOR]

To cancel the negative effects of the friction torques, unmodeled dynamics, and coupling torques, affecting the gimbal precision of a double gimbal control moment gyro (DGCMG) system, this paper proposes a new control architecture to handle these exogenous/endogenous disturbances and to control the two gimbals of the system. It combines a backstepping controller with a nonlinear disturbance observer, which preserve the advantages of the two entities. Firstly, the state space equations of the DGCMG system are established with the friction torques considered exogenous disturbances and unmodeled dynamics regarded as endogenous disturbances. Secondly, a nonlinear observer is used for the estimation of the disturbances. Thirdly, using the observer estimation errors, a backstepping controller is designed to enhance the robustness of the control system, to handle the channel interferences, and to solve the mismatched problem without decoupling between the inner/outer gimbal channels. The obtained control architecture is software implemented and validated; the results show that the proposed control approach not only enhances the robustness in relation to the exogenous/endogenous disturbances, but also improves the angular velocity precision of the two gimbals of the DGCMG system. • The control methodology improves the angular velocity precision of the gimbals for DGCMG systems. • A backstepping controller is designed to enhance the robustness of the control system. • A nonlinear observer is designed for the estimation of the disturbances. • The stability of the control architecture is proved by using the Lyapunov theory. [ABSTRACT FROM AUTHOR]

A multistage biometric verification system uses multiple biometrics and/or multiple biometric verifiers to generate a verification decision. The core of a multistage biometric verification system is reject option which allows a stage not to give a genuine/impostor decision when it is not confident enough. This paper studies the effectiveness of symmetric rejection for multistage biometric verification systems. The symmetric rejection method determines the reject region by symmetrically rejecting equal proportion of genuine and impostor scores. The applicability of a multistage biometric verification system depends on how secure and user convenient it is, which is measured by the performance–cost trade-off. This paper analyzes the performance–cost trade-off of symmetric rejection method by conducting extensive experiments. Experiments are performed on two biometric databases: (1) publicly available NIST database and (2) a keystroke database. In addition, the symmetric rejection method is empirically compared with two existing rejection methods: (1) sequential probability ratio test-based method, which uses score-fusion and (2) Marcialis et al.'s method, which does not use score fusion. Results demonstrate strong effect of symmetric rejection method on creating a secure and user convenient multistage biometric verification system. [ABSTRACT FROM AUTHOR]

In the recommendation system. the inner product interaction of a single learning matrix de composition or the use of deep neural networks to capture user interaction with the project is not sufficient to effectively learn the potential characteristics of users and projects. In view of this problem. this paper proposes a collaborative filtering algorithm based on deep learning feature representation (DLFeaCF) based on display feedback and implicit feedback. The model first learns the inner product and outer product interaction between the user and the project. Then, based on the inner product, it uses the nonlinear interactive learning ability of the multi-layer perceptron (MLP) to obtain the two aspects from implicit mapping and feature mapping: on the basis of the outer product, CNN learning is used to capture the local features of the user and the project finally, combine the features in the fusion layer and obtain the prediction score, The experiments on the real MovieLens dataset show that the DLFeaCF model can achieve better recommendation performance. [ABSTRACT FROM AUTHOR]

In the fields of information theory and network coding, a complete characterization of the almost entropic region is a fundamental but inherently difficult open problem. This paper focuses on the characterization of this region via explicit inner bounds, optimization of functions over this region, and network code construction. One approach to study the entropic region is to put a constraint on the alphabets for involved random variables, enabling us to focus on a specific set of joint distributions. We present the notion of alphabet constrained entropic set and describe its properties, namely, its a closed and path-connected set. Motivated by the properties, a random local search algorithm is designed to find an entropic vector and associated distribution near to a given target vector and extended to optimize functions of joint entropies. We present significantly improved inner bound compared to known inner bounds for the almost entropic region involving four random variables using a refinement of our algorithm. Finally, another application of the algorithm is shown to construct network codes and index codes for a given rate vector in the capacity region. This approach to constructing network codes is novel and has an entirely different flavor than classical coding theoretic construction. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an $n$ -channel multilevel imperfect secret sharing problem, which can be regarded as a generalization of secret sharing and a variation of multilevel diversity coding. In this model, a discrete memoryless source (DMS) is encoded into $n$ encoded messages. To measure the secrecy of the system, we introduce a security level for each subset of encoded messages. In the paper, we focus on the $n$ -channel symmetric multilevel imperfect secret sharing (SMISS) problem, i.e., the security levels of all the subsets with the same cardinality are identical. First, we explicitly characterize the coding rate regions for 2-channel and 3-channel SMISS problems. However, it is difficult to characterize the explicit rate region for a general $n$ , since the complexity of designing optimal coding schemes can grow with $n$ exponentially. Nevertheless, we put forward an inner bound and an outer bound on the rate region of the general $n$ -channel SMISS problem. Moreover, we consider two special cases, i.e., the Two-SMISS problem and the linear SMISS problem, and prove that the inner and outer bounds are tight for these two problems, respectively. [ABSTRACT FROM AUTHOR]

Effective interference management in the multiuser interference channel strongly hinges on the channel state information’s availability at the transmitters (CSIT). In a broad range of emerging large-scale and distributed networks (e.g., the Internet of Things), acquiring the CSIT is prohibitive due to the extensive information exchange that it imposes. As a result, the interference management approaches that rely on the CSIT lose their effectiveness in such circumstances. This article focuses on the two-user interference channel and proposes a broadcast approach to interference management. Its hallmark is that the transmitters, unlike the receivers, are entirely oblivious to instantaneous channel states. Each transmitter splits its message into multiple superimposed encoded information layers, where each layer is adapted to a given possible state for the combined states of all channels. Depending on the relative gain between the direct and interfering channels, each receiver opportunistically decodes a subset of both transmitters’ received layers. An average achievable rate region is delineated, serving as an inner bound on the Gaussian interference channel’s average capacity region in the absence of CSIT. Finally, an upper bound on the gap between the achievable sum-rate and the sum-rate capacity is established. [ABSTRACT FROM AUTHOR]

We consider a setup in which condential i.i.d. samples X1; Xn from an unknown nite-support distribution p are passed through n copies of a discrete privatization channel (a.k.a. mechanism) producing outputs Y1;: ::; Yn. The channel law guarantees a local dierential privacy of ffl. Subject to a prescribed privacy level ffl, the optimal channel should be designed such that an estimate of the source distribution based on the channel outputs Y1;: ::; Yn converges as fast as possible to the exact value p. For this purpose we study the convergence to zero of three distribution distance metrics: f-divergence, meansquared error and total variation. We derive the respective normalized rst-order terms of convergence (as n ! 1), which for a given target privacy ffl represent a rule-of-thumb factor by which the sample size must be augmented so as to achieve the same estimation accuracy as that of a non-randomizing channel. We formulate the privacy-delity trade-o problem as being that of minimizing said rst-order term under a privacy constraint ffl. We further identify a scalar quantity that captures the essence of this trade-o, and prove bounds and data-processing inequalities on this quantity. For some specic instances of the privacy-delity trade-o problem, we derive inner and outer bounds on the optimal trade-o curve. [ABSTRACT FROM AUTHOR]

We consider the fundamental tradeoff between the storage cost and the download cost in private information retrieval (PIR) systems, without any explicit structural restrictions on the storage codes, such as maximum distance separable codes or uncoded storage. Our focus in this work is on the two extreme points: the point when the storage cost is minimal, and the point when the download cost is minimal. Two novel outer bounds are provided, which have the following implications at these two extreme points. When the messages are stored without any redundancy across the databases, the optimal PIR strategy is to download all the messages; on the other hand, for PIR capacity-achieving codes, each database can reduce the storage cost, from storing all the messages, by no more than one message on average. To better understand the second extreme point, we then focus on the two-message two-database case, and show that a stronger outer bound can be derived through a novel pseudo-message technique. This stronger outer bound suggests that a precise characterization of the storage-download tradeoff may require more sophisticated bounding techniques. [ABSTRACT FROM AUTHOR]

In Vehicular Ad-hoc Networks (VANETs), high frequent interaction of safety-related information is required among vehicles and imposes urgent demand on information update. In order to reduce communication delay and improve the capacity of concurrent communication, in this paper we propose that the multi-antenna vehicle could takeover the channel management as dynamic base station to apply Multiple-Input Multiple-Output communication and interference management approach in Vehicle to Vehicle (V2V) communications. Firstly, we construct an Markov decision process (MDP) model for multi-antenna vehicle to estimate whether it is appropriate to be dynamic base station. In addiction, Monte Carlo Tree Search algorithm is introduced to derive MDP policy. Thirdly, the V2V Interference Alignment (V2V-IA) model is constructed for dynamic base station to obtain IA scheme to manage V2V communications and IA in VANETs. To achieve the goal of improving frequency of information update, we propose an optimized problem to minimize total number of time slots, which is required for completing global safety-related information delivery. Simulation results show that the frequency of information update can be improved effectively by the proposed approach and the average improvement could go up to 40%. [ABSTRACT FROM AUTHOR]

This paper investigates subchannel allocation based on clustered interference alignment in dense small cell networks when all small cell user equipments (SUEs) have differentiated requirements for data streams. By imposing the condition that each cluster has a size not exceeding the maximum value achieved when each SUE needs only one data stream, we maximize the number of SUEs with guaranteed requirements for data streams, which is NP-hard. Hence, we propose a two-phase efficient solution with much lower complexity and reduced feedback overhead. First, similarity clustering is performed by graph partition, and then, subchannel allocation is done through a coloring algorithm. Numerical results show that the proposed solution offers a performance better than the related schemes and close to the approximate optimal solution. [ABSTRACT FROM AUTHOR]

While the problems of sum-rate maximization and sum-power minimization subject to quality of service (QoS) constraints in the multiple input multiple output interference broadcast channel (MIMO IBC) have been widely studied, most of the proposed solutions have neglected the user scheduling aspect assuming that a feasible set of users has been previously selected. However, ensuring QoS for each user in the MIMO IBC involves the joint optimization of transmit/receive beamforming vectors, transmit powers, and user scheduling variables. To address the full problem, we propose a novel formulation of a rate-constrained sum-utility maximization problem which allows to either deactivate users or minimize the QoS degradation for some scheduled users in infeasible scenarios. Remarkably, this is achieved avoiding the complexity of traditional combinatorial formulations, but rather by introducing a novel expression of the QoS constraints that allows to solve the problem in a continuous domain. We propose centralized and decentralized solutions, where the decentralized solutions focus on practical design and low signaling overhead. The proposed solutions are then compared with benchmarking algorithms, where we show the effectiveness of the joint scheduling and transceiver design as well as the flexibility of the proposed solution performing advantageously in several MIMO IBC scenarios. [ABSTRACT FROM AUTHOR]

For a hybrid magnetically suspended flywheel (MSFW) rotor suspended by permanent magnet biased active magnetic bearing (AMB) and passive magnetic bearing (PMB), the dynamic functions are nonlinear and coupling among different degrees of freedom (DOFs). In this article, the nonlinear dynamic functions in two controllable DOFs of the hybrid MSFW rotor are developed based on the equivalent magnetic circuit, and then the nonlinear dynamic function is linearized by using the state feedback exact linearization (SFEL) in order to minimize the coupling in two controllable DOFs. Furthermore, an optimal control based on the SFEL model is designed to reduce displacement runout and coupling among two controllable DOFs of the hybrid MSFW rotor at the rated speed. Finally, the simulation and experimental results validate the effectiveness of the optimal control based on SFEL model, and the stability of the hybrid MSFW rotor with an impulse-type disturbance is improved. [ABSTRACT FROM AUTHOR]

Secrecy transmission is investigated for a cooperative jamming scheme, where a multi-antenna jammer generates artificial noise (AN) to confuse eavesdroppers. Two kinds of eavesdroppers are considered: passive eavesdroppers who only overhear the legitimate information, and active eavesdroppers who not only overhear the legitimate information but also jam the legitimate signal. Existing works only treat the passive and active eavesdroppers separately. Different from the existing works, we investigate the achievable secrecy rate in presence of both active and passive eavesdroppers. For the considered system model, we assume that the instantaneous channel state information (CSI) of the active eavesdroppers is available at the jammer, while only partial CSI of the passive eavesdroppers is available at the jammer. A new zero-forcing beamforming scheme is proposed in the presence of both active and passive eavesdroppers. For both the perfect and imperfect CSI cases, the total transmission power allocation between the information and AN signals is optimized to maximize the achievable secrecy rate. Numerical results show that imperfect CSI between the jammer and the legitimate receiver will do more harm to the achievable secrecy rate than imperfect CSI between the jammer and the active eavesdropper. [ABSTRACT FROM AUTHOR]

Two kinds of fractional-order autonomous circuits are constructed by using fractional-order capacitor and fractional-order inductor respectively. The orders of the adopted fractional-order elements must be greater than one. The corresponding circuit simulations were developed and verified the proposed fractional-order autonomous circuits. • Two kinds of new fractional-order autonomous circuits are proposed. • The fractional-order autonomous circuits are based on fractional-order elements with order larger than one. • The operating frequency or resonant frequency of the circuits can be changed by adjusting the resistance. • The current and voltage of the circuits can be controlled by adjusting the orders of fractional-order elements. • The available simulations verify the effectiveness of the theoretical analysis. Fractional-order circuit is a kind of circuit which contains fractional-order elements. It has been proved that the fractional-order circuit has some characteristics which are hard to be achieved by integer-order circuits, such as higher degree of freedom in circuit design. For integer-order circuits, there are not only non-autonomous circuits, but also autonomous circuits. Since there are many applications of integral-order autonomous circuits in real world, it is also necessary to explore fractional-order autonomous circuits. However, few research focuses on fractional-order autonomous circuits. Therefore, this paper proposes two kinds of fractional-order autonomous circuits based on fractional-order elements with order larger than one. The corresponding mathematical models are also established based on fractional calculus and their characteristics are analyzed based on circuit theory. Finally, circuit simulation are performed to verify the correctness of theoretical analysis. [ABSTRACT FROM AUTHOR]

Many methods for machine learning rely on approximate inference from intractable probability distributions. Variational inference approximates such distributions by tractable models that can be subsequently used for approximate inference. Learning sufficiently accurate approximations requires a rich model family and careful exploration of the relevant modes of the target distribution. We propose a method for learning accurate GMM approximations of intractable probability distributions based on insights from policy search by using information-geometric trust regions for principled exploration. For efficient improvement of the GMM approximation, we derive a lower bound on the corresponding optimization objective enabling us to update the components independently. Our use of the lower bound ensures convergence to a stationary point of the original objective. The number of components is adapted online by adding new components in promising regions and by deleting components with negligible weight. We demonstrate on several domains that we can learn approximations of complex, multimodal distributions with a quality that is unmet by previous variational inference methods, and that the GMM approximation can be used for drawing samples that are on par with samples created by state-of-the- art MCMC samplers while requiring up to three orders of magnitude less computational resources. [ABSTRACT FROM AUTHOR]

So-called improper complex signals have been shown to be beneficial in the single-antenna two-user Gaussian interference channel under the assumptions that all input signals are Gaussian and that we treat interference as noise (TIN). This result has been obtained under a restriction to pure strategies without time-sharing, and it was extended to the case where the rates, but not the transmit powers, may be averaged over several transmit strategies. In this paper, we drop such restrictions and discuss the most general case of coded time-sharing, where both the rates and the powers may be averaged. Since coded time-sharing can in general not be expressed by means of a convex hull of the rate region, we have to account for the possibility of time-sharing already during the optimization of the transmit strategy. By means of a novel channel enhancement argument, we prove a surprising result: proper signals are optimal if coded time-sharing is allowed. In addition to establishing this result, we present an algorithm to compute the corresponding achievable rate region. [ABSTRACT FROM AUTHOR]