Pair Of Users Research Articles

Decreased risk of treatment failure with vedolizumab and thiopurines combined compared with vedolizumab monotherapy in Crohn’s disease

ObjectiveWhile infliximab combined to thiopurines is more effective than infliximab monotherapy in patients with Crohn’s disease (CD) and UC, the impact of adding thiopurines to vedolizumab remains controversial. We emulated...

Improved recommender systems by denoising ratings in highly sparse datasets through individual rating confidence

Collaborative filtering (CF) is the most successful approach of Recommender Systems that has been applied in a wide range of applications. In this approach, historical rating data is exploited to calculate similarity between pairs of users and predict user preference over unseen items. The similarity is calculated using users' global preferences estimated from their previous interactions with items. To this end, commonly rated items by a given pair of users are utilized to calculate the similarity. In a sparse dataset, there are limited co-rated items. In addition, inconsistent behaviours of users in rating items may add some noise to data, which makes the ratings more untrustworthy leading to less accuraterecommendations. In this manuscript, we introduce an individual ratings confidence measure (IRC) to calculate the confidence of a given rating to each item by the target user. IRC consists of 5 factors that help to have more information about the interest and boredom of users. User ratings are denoised by prioritizing extreme and high-confidence ratings, and finally, the denoised ratings are used to obtain similarity values. This approach leads to a more accurate neighbourhood selection and rating prediction. We show the superiority of the proposed method when compared with state-of-the-art recommender algorithms over some well-known benchmark datasets.

NOMA and Coded Multicasting in Cache-Aided Wireless Networks

Coded multicasting is considered to be an effective approach to simultaneously serve multiple users in the same frequency/time/code resource, which is made possible by exploiting the information available in users’ caches. Recently, non-orthogonal multiple access (NOMA) has emerged as an alternative transmission technique for cache-aided network. In cache-aided NOMA system, cache-enabled interference cancellation (CIC) is employed to cancel the interference using the information in the cache, and thus enhance the user transmission rate, particularly for the weak users. Despite the enhanced spectral efficiency offered by both techniques, complexity issue arises from handling large number of users. Therefore, user pairing/clustering should be employed to limit the number of users served in the same time-frequency resource. However, the key question is which delivery technique performs better under different pairing scenarios. In this paper, the performance of NOMA and coded multicasting for two-user pairing are investigated in terms of probability of sum rate comparison and outage probability. In order to exploit the benefits of NOMA and coded multicasting, we also propose a hybrid delivery scheme, which select either NOMA or coded multicasting depending on the channel conditions of the paired users in each resource block (RB). A joint mode selection, power allocation and user pairing scheme is developed to enhance the performance of the hybrid scheme. Both analytical and simulation results demonstrate that NOMA outperforms coded multicasting when pairing users whose channel gains are highly distinctive, while coded multicasting is preferred when the paired users have similar channel gains. In addition, the hybrid scheme is demonstrated to offer enhanced sum rate performance in comparison to NOMA and coded multicasting.

Coverage Probability of Relay-Assisted NOMA Millimeter Wave Networks with Steerable-Beam

In this paper, we consider a relay-assisted non-standalone (NSA) 5G network, where source (S) intends to transmit signals to users by assistance with a relay R, which receives the signals from S operating in microwave frequency and transfers to target users by utilizing steerable-beam non-orthogonal multiple access (NOMA) scheme operating in millimeter-wave (mmWave) frequency. The steerable-beam NOMA scheme can flexibly switch between single-beam and multi-beam modes according to angle difference of users in NOMA group, i.e., when at least one angle difference is smaller than mmWave beamwidth of main lobe, R adopts a single-beam for achieving NOMA transmission, otherwise multi-beam scheme is used to complete NOMA transmission. For insight into the performance of steerable-beam NOMA scheme, we analyze the coverage probability of the system in-depth for deriving the analytical expressions and approximately closed-form solutions of target users’ coverage probabilities within a NOMA group, where the first user Uo is selected with the shortest distance to the S and the paired user Up is determined based on the minimum angle difference to the first user. However, when R adopts multi-beam, the user with the smallest angle difference to the Uo may not be the best paired user due to the influence of path attenuation and antenna allocation. We then propose a two-stage scheme to obtain optimal user pairing by jointly considering the angle, distance, and sum-rate, while optimizing power allocation subject to maximize the sum-rate. Simulation results illustrate the coverage performance of the system with steerable-beam NOMA scheme for different parameters, and demonstrate the advantages of the proposed two-stage strategy offers a significant improvement in terms of average sum-rate compared to other schemes.

Performance analysis for reconfigurable intelligent surface assisted downlink NOMA networks

In this paper, a reconfigurable intelligent surface (RIS) assisted downlink non-orthogonal multiple access (NOMA) network is considered, where a base station communicates with a pair of users with the assistance of a RIS. The performance of RIS-assisted downlink NOMA networks is investigated by exploiting the coherent phase shifting design. In particular, the central limit theorem based Gaussian approximation is introduced to model the sum of independent and identically distributed random variables and derive the approximate expressions of the outage probability for two users. Furthermore, the upper bounds for the outage probability are obtained based on the property of the Bessel function. Additionally, both the asymptotic outage probabilities and the asymptotic upper bounds at high signal-to-noise ratio are derived and the diversity order achieved by the network is obtained. Simulation results are provided to validate the theoretical findings and demonstrate that RIS-NOMA can achieve superior outage performance compared to RIS-assisted orthogonal multiple access and conventional full-duplex decode-and-forward relaying schemes. Moreover, it can be observed that the outage performance of RIS-NOMA can be tremendously enhanced with increasing the number of reflecting elements.

Resource Allocation for Throughput versus Fairness Trade-Offs under User Data Rate Fairness in NOMA Systems in 5G Networks

In this work, we present a resource allocation scheme for managing trade-offs between total throughput maximisation and system fairness in a non-orthogonal multiple access (NOMA) system for 5G networks. Our proposed approach is designed to improve throughput and fairness as performance metrics of NOMA in 5G networks. We apply integer linear programming for user pairing and adopt particle swarm optimisation as the power allocation scheme for reducing resource allocation complexity. To formulate the multi-objective problem, we use scalarisation of multi-objective optimisation, which exhibits flexibility in assigning different weights to a single objective—in the case of this study, either sum rate or fairness. Moreover, the problem is formulated with a penalty function to prevent optimisation violating the constraints of the optimisation function. Simulation results show that the proposed model outperformed the conventional approach by at least 17% in terms of throughput maximisation and fairness rate.

The Impact of User-Pairing on the Performance of Non-Orthogonal Multiple Access (NOMA) System

Non-orthogonal multiple access (NOMA) is being considered as a candidate to meet the expected traffic demand growth in 5G and beyond 5G (5GB) networks. Due to the complexity of applying multiuser detection at the NOMA receiver, a number of works have suggested applying user-pairing to simplify dealing with all users as a whole. This paper addresses the effect of applying user-pairing on the performance of NOMA assisted system in general proposes three different user pairing approaches to examine which one is best for boosting the performance of multiuser NOMA system and making it reaches its potential. This paper evaluates the performance of NOMA system with organized (uniform), random, and distance-based user pairing schemes. Simulation results show that the organized pairing assisted NOMA scheme offers the best performance as compared to its pairing peer techniques in terms of the overall sum rate and the energy efficiency.

Attention-based explainable friend link prediction with heterogeneous context information

Friend link prediction is an important research problem in recommender systems. Existing network embedding and knowledge embedding methods mainly consider the structural relationships of entities, ignoring the explanatory role of text contents. In this paper, we present an explainable friend link recommendation method that leverages direct and indirect similarity of user pairs via fusion embedding of heterogeneous context information. In social networks, while considering user content interests, first, a fusion user embedding method was developed by incorporating external knowledge semantics. Second, for a user pair, we calculate their direct similar relationship using fusion user embeddings. Additionally, based on intermediate neighbors, we compute their indirect similar relationship by using an attention mechanism, which explains neighbors’ bootable and transitive influences for learning the social relationship of user pairs. Then, a hybrid personalized and neighbor attention model for friend link prediction was proposed by considering direct and indirect factors. Finally, experiments were conducted on the Sina Weibo datasets, which indicates that the proposed method effectively predicts the friends of users and provides a good interpretation for link prediction recommendation results.

The connectivity network underlying the German\u2019s Twittersphere: a testbed for investigating information spreading phenomena

Online social networks are ubiquitous, have billions of users, and produce large amounts of data. While platforms like Reddit are based on a forum-like organization where users gather around topics, Facebook and Twitter implement a concept in which individuals represent the primary entity of interest. This makes them natural testbeds for exploring individual behavior in large social networks. Underlying these individual-based platforms is a network whose “friend” or “follower” edges are of binary nature only and therefore do not necessarily reflect the level of acquaintance between pairs of users. In this paper,we present the network of acquaintance “strengths” underlying the German Twittersphere. To that end, we make use of the full non-verbal information contained in tweet–retweet actions to uncover the graph of social acquaintances among users, beyond pure binary edges. The social connectivity between pairs of users is weighted by keeping track of the frequency of shared content and the time elapsed between publication and sharing. Moreover, we also present a preliminary topological analysis of the German Twitter network. Finally, making the data describing the weighted German Twitter network of acquaintances, we discuss how to apply this framework as a ground basis for investigating spreading phenomena of particular contents.

Quantum-inspired evolutionary algorithms for NOMA user pairing

This work proposes the utilization of the quantum-inspired evolutionary algorithm (QEA) for user pairing in non-orthogonal multiple access (NOMA). By exploiting quantum concepts such as superposition, it obtained a user pairing solution that approximates the highest achievable sum rate. Moreover, elitist QEA (E-QEA) is proposed to further enhance the performance by eliminating the risk of losing the best solution of the current iteration in the next iteration. Simulation result demonstrates that E-QEA and QEA yield higher average achievable sum rates compared to random user pairing.

A Gradual Resource Allocation Technique for Massive MIMO-NOMA

In this letter, a new perspective for channel allocation and user pairing is proposed for a crowded downlink system using massive multiple-input–multiple-output, nonorthogonal multiple access (NOMA), and zero-forcing beamforming. The proposed user clustering technique allocates users to subbands and beams by a gradual relaxation of the correlation constraints in such a way to enhance the conditioning of the channel matrix. Channel measurements are performed in this context to validate the proposed technique in an experimental setup. Results show an important gain in performance in terms of both throughput and fairness with respect to orthogonal multiple access and to two state-of-the-art NOMA clustering methods.

Performance Analysis of Opportunistic Beam Splitting NOMA in Millimeter Wave Networks

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

MAUIL: Multilevel attribute embedding for semisupervised user identity linkage

User identity linkage (UIL) across social networks has recently attracted an increasing amount of attention due to its significant research challenges and practical value. Most of the existing methods use a single method to express different types of attribute features. However, the simplex pattern can neither cover the entire set of different attribute features nor capture the higher-level semantic features in the attribute text. This paper establishes a novel semisupervised model, namely the multilevel attribute embedding for semisupervised user identity linkage (MAUIL), to seek the common user identity across social networks. MAUIL includes two components: multilevel attribute embedding and regularized canonical correlation analysis (RCCA)-based linear projection. Specifically, the text attributes for each network are first divided into three types: character-level, word-level, and topic-level attributes. Second, unsupervised approaches are employed to extract the corresponding three types of text attribute features, and user relationships are embedded as a complimentary feature. All the resultant features are combined to form the final representation of each user. Finally, target social networks are projected into a common correlated space by RCCA with the help of a small number of prematched user pairs. We demonstrate the superiority of the proposed method over state-of-the-art methods through extensive experiments on two real-world datasets. All the datasets and codes are publicly available online.11https://github.com/ChenBaiyang/MAUIL.

Intelligent Jamming Strategies for Secure Spectrum Sharing Systems

This paper investigates the secrecy performance of a spectrum sharing network, where <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> legitimate source-destination pairs orderly access the shared spectrum for communication, while an eavesdropper (E) attempts to tap the legitimate information transmission. To improve the physical layer security, we propose two jamming strategies that can intelligently switch between jamming and non-jamming, namely, suboptimal jammer selection (SJS) scheme and optimal jammer selection (OJS) scheme. Specifically, when a user pair is assigned to access the shared spectrum, another source is chosen as a friendly jammer in order to create intentional interference at E. For the purpose of comparison, we present the non-jammer selection (NJS) scheme as a benchmark. Analytical closed-form secrecy outage probability expressions of NJS, SJS and OJS schemes are derived over Nakagami-<inline-formula> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> fading channels. We further present an asymptotic secrecy outage probability analysis to evaluate the secrecy diversity gain performance of NJS, SJS and OJS schemes. Numerical results show that the secrecy outage probability performance of OJS scheme is better than SJS and NJS schemes in the low average channel power gain <inline-formula> <tex-math notation="LaTeX">${\mathop \Omega \nolimits _{D} }$ </tex-math></inline-formula> region. Furthermore, the secrecy outage probabilities of NJS as well as SJS and OJS schemes converge to each other with the increase of <inline-formula> <tex-math notation="LaTeX">${\mathop \Omega \nolimits _{D} }$ </tex-math></inline-formula>, due to the fact that the OJS and SJS scheme will switch to NJS scheme when <inline-formula> <tex-math notation="LaTeX">${\mathop \Omega \nolimits _{D} }$ </tex-math></inline-formula> tends to infinity.

Multi-Pair Two-Way Massive MIMO DF Relaying Over Rician Fading Channels Under Imperfect CSI

We investigate a multi-pair two-way decode-and-forward relaying aided massive multiple-input multiple-output antenna system under Rician fading channels, in which multiple pairs of users exchange information through a relay station having multiple antennas. Imperfect channel state information is considered in the context of maximum-ratio processing. Closed-form expressions are derived for approximating the sum spectral efficiency (SE) of the system. Moreover, we obtain the power-scaling laws at the users and the relay station to satisfy a certain SE requirement in three typical scenarios. Finally, simulations validate the accuracy of the derived results.

Moderate-intensity statin use for primary prevention for more than 5 years is associated with decreased all-cause mortality in 75 years and older

ObjectiveEvidence regarding the primary preventive effects of statin in the elderly is inadequate. This study aimed to determine the duration and intensity of statins beneficial in adults aged ≥75 years for primary prevention. MethodsThis is a retrospective longitudinal study, using the National Health Insurance Corporation-Senior Cohort data from 2002 to 2015. Exact block matching was used to select comparable subjects from statin users and non-users. ResultThe study subjects consisted of 685 pairs of statin non-users and users (total number of 1,370). During the follow-up (mean 8.7 years) period, the adjusted HR for mortality compared to non-user was 0.95 (p = 0.71) in low intensity statin users and 0.80 (p = 0.002) in the moderate intensity statin groups. The adjusted HR for MACE (Major Adverse Cardiovascular Events) compared to non-users was 1.10 (p = 0.39) in the low intensity statin group and 1.29 (p = 0.001) in the moderate intensity statin group. The risk of MACE disappeared five years after in moderate intensity statin users. Moderate intensity statin use was significantly associated with an increased risk of NODM (New Onset Diabetes Mellitus) (HR 1.50, p < 0.001) for up to three years, but the risk faded away after five years (HR 0.90, p = 0.52). ConclusionModerate intensity statins taken for five or more years for primary prevention would be associated with low risk of all-cause mortality in the 75+ years old. This result may support the evidence that initiation of statin for primary prevention in patients aged over 75 years is beneficial and tolerable.

Cache‐enabled reinforcement learning scheme for power allocation and user selection in opportunistic downlink NOMA transmissions

Non‐orthogonal multiple access (NOMA) allows multiple user equipment (UE) to simultaneously share the same resource blocks using varying levels of transmit power at the base station (BS) side. Proper allocation of transmission power and selection of candidate users for pairing over the same resource block are critical for an efficient utilization of the available resources. Optimal UE selection and power splitting among paired UEs can be made through an exhaustive search over the space of all possible solutions. However, the cost incurred by such approach can render it practically infeasible. Reinforcement learning (RL) deploying double deep‐Q networks (DDQN) is a promising framework that can be adopted for tackling the problem. In this article, an RL‐based DDQN scheme is proposed for user pairing in opportunistic access to downlink NOMA systems with capacity‐limited backhaul link connections. The proposed algorithm relies on proactive data caching to alleviate the throttling caused by backhaul bottlenecks, and optimized UE selection and power allocation are accomplished through the continuous interaction between an RL agent and the NOMA environment to increase the overall system throughput. Simulation results are presented to showcase the near‐optimal strategy achieved by the proposed scheme. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Analysis of user pairing non-orthogonal multiple access network using deep Q-network algorithm for defense applications

Non-orthogonal multiple access (NOMA) networks play an important role in defense communication scenarios. Deep learning (DL)-based solutions are being considered as viable ways to solve the issues in fifth-generation (5G) and beyond 5G (B5G) wireless networks, since they can provide a more realistic solution in the real-world wireless environment. In this work, we consider the deep Q-Network (DQN) algorithm-based user pairing downlink (D/L) NOMA network. We have applied the convex optimization (CO) technique and optimized the sum rate of all the wireless users. First, the near-far (N-F) pairing and near-near and far-far (N-N and F-F) pairing strategies are investigated for the multiple numbers of users, and a closed-form (CF) expression of the achievable rate is derived. After that, the optimal power allocation (OPA) factors are derived using the CO technique. Through simulations, it has been demonstrated that the DQN algorithms perform much better than the deep reinforcement learning (DRL) and conventional orthogonal frequency-division multiple access (OFDMA) schemes. The sum-rate performance significantly increases with OPA factors. The simulation results are in close agreement with the analytical results.

General logic-operation-based lightweight group-key distribution schemes for Internet of Vehicles

It is predicted that the trend of Internet of Vehicles (IoV) applications will keep on growing due to its flexibility in infrastructure. The security of IoV can protect the peer-to-peer (P2P) data transmitted over Internet. Since most Internet devices are components with low battery power, low communication and computational power, the key distribution scheme for IoV needs to be lightweight. Most conventional communications in Internet of Vehicles are one-to-one types of communications which involve only two communication entities. Proposals for key distribution schemes are mostly developed to establish a pairwise key for a pair of users. For example, Diffie-Hellman public-key distribution scheme proposed in 1976 and the quantum key distribution scheme (QKD) invented in 1984 (also called the BB84 scheme), can only enable two users to share a secret key used in conventional one-to-one communications. Modern communications have been evolved into many-to-many types of communications which involve more than two users. Group-key distributions enable multiple users to share a group key. Recently, a lightweight group-key distribution scheme has been proposed which needs only logic operations. But this scheme can only provide confidentiality of the group key. In this paper, we extend that scheme to propose the first lightweight authenticated group-key distribution scheme which needs only logic operations. Our proposed schemes can be built on top of any type of authenticated pairwise-key distribution schemes. We first propose a basic three-party authenticated group-key distribution scheme. Then, general three multiple-party authenticated group-key distribution schemes based on the basic scheme are proposed. Since our proposed schemes need only logic operations, they are all lightweight and are suitable for P2P IoV communication applications.

Simple Multiuser Twin-Field Quantum Key Distribution Network

Twin-field quantum key distribution (TFQKD) systems have shown great promise for implementing practical long-distance secure quantum communication due to its measurement-device-independent nature and its ability to offer fundamentally superior rate-loss scaling than point-to-point QKD systems. A surge of research and development effort in the last two years has produced many variants of protocols and experimental demonstrations. In terms of hardware topology, TFQKD systems interfering quantum signals from two remotely phase-locked laser sources are in essence giant Mach-Zehnder interferometers (MZIs) requiring active phase stabilization. Such configurations are inherently unsuitable for a TFQKD network, where more than one user-pair share the common quantum measurement station, because it is practically extremely difficult, if not impossible, to stabilize MZIs of largely disparate path lengths, a situation that is inevitable in a multi-user-pair TFQKD network. On the other hand, Sagnac interferometer based TFQKD systems exploiting the inherent phase stability of the Sagnac ring can implement asymmetric TFQKD, and are therefore eminently suitable for implementing a TFQKD network. In this work, we experimentally demonstrate a proof-of-principle multi-user-pair Sagnac TFQKD network where three user pairs sharing the same measurement station can perform pair-wise TFQKD through time multiplexing, with channel losses up to 58 dB, and channel loss asymmetry up to 15 dB. In some cases, the secure key rates still beat the rate-loss bounds for point-to-point repeaterless QKD systems, even in this network configuration. It is to our knowledge the first multi-user-pair TFQKD network demonstration, an important step in advancing quantum communication network technologies.