Pair Of Users Research Articles

Joint user association and pairing in multi-uav-assisted noma networks: a decaying-epsilon thompson sampling framework

Joint user association and pairing in multi-uav-assisted noma networks: a decaying-epsilon thompson sampling framework

RIS-Assisted Cooperative Time-Division Multiple Access.

Reconfigurable intelligent surface-aided communication systems have been intensively investigated to improve capacity, coverage, and energy efficiency via optimal controlling of phase shifts for passive reflecting elements. However, there are few studies on cooperative transmission incorporating RIS in TDMA systems, because RIS reflects all the incident signals, and it inadvertently leads to a boost in interference signals. In this paper, we propose RIS-assisted cooperative time-division multiple access, in which the required SINR of all users is guaranteed as much as possible by opportunistic use of RIS for cooperative transmission. The proposed scheme's primary function is that some time slots, i.e., cooperative time slots, serve a pair of users, i.e., a strong- and a weak-channel-conditioned user, using RIS. To support this functionality, we propose scheduling for non-cooperative and cooperative time slots, user pairing for scheduled cooperative time slots, and transmit beamforming vector design for the pair of UEs in each cooperative time slot. The simulation and numerical results demonstrate that the proposed scheme guarantees QoS for all UE as much as possible and minimizes the remaining required capacity indicating the amount of capacity that was not achieved compared with the required capacity.

Towards comprehensive cyberbullying detection: A dataset incorporating aggressive texts, repetition, peerness, and intent to harm

The increasing usage of social media networks has raised concerns about the growing frequency of cyberbullying incidents. The definition of cyberbullying lacks universal consensus, yet according to several authors, cyberbullying is characterized by aggressive, repetitive, and intentional communication among peers. However, existing cyberbullying detection datasets often focus solely on classifying texts as aggressive or non-aggressive, neglecting the other cyberbullying aspects, thus hindering research progress. This paper proposes a framework for designing a new dataset incorporating all four aspects of cyberbullying to address this gap. The text messages are sourced from a real dataset, while the users’ data is generated synthetically. The resulting dataset contains messages exchanged randomly among different pairs of users, thus inculcating repetition. Additionally, the degree of peerness, defined and calculated to measure the likelihood of two users being peers, is used. The intent of harm is quantified as a numeric value using the ratios of aggression and repetition. As a result, the proposed dataset encompasses all four aspects of cyberbullying by providing repeated aggressive messages among users along with quantitative values of the degree of peerness and intent to harm. The proposed dataset is adaptable, with adjustable threshold values for peerness, repetition, and intent to harm, offering flexibility for various applications. The paper concludes by presenting the results of some baseline machine-learning methods on the proposed dataset.

Precoding-Based Downlink OAM-MIMO Communications With Rate Splitting

Orbital angular momentum (OAM) and rate splitting (RS) are the potential key techniques for the future wireless communications. As a new orthogonal resource, OAM can achieve the multifold increase of spectrum efficiency to relieve the scarcity of the spectrum resource, but how to enhance the privacy performance imposes crucial challenge for OAM communications. RS technique divides the information into private and common parts, which can guarantee the privacies for all users. In this paper, we integrate the RS technique into downlink OAM-MIMO communications, and study the precoding optimization to maximize the sum capacity. First, the concentric uniform circular arrays (UCAs) are utilized to construct the downlink transmission framework of OAM-MIMO communications with RS. Particularly, users in the same user pair utilize RS technique to obtain the information and different user pairs use different OAM modes. Then, we derive the OAM-MIMO channel model, and formulate the sum capacity maximization problem. Finally, based on the fractional programming, the optimal precoding matrix is obtained to maximize the sum capacity by using quadratic transformation. Extensive simulation results show that by using the proposed precoding optimization algorithm, OAM-MIMO communications with RS can achieve higher sum capacity than the traditional communication schemes.

ViWise: Fusing Visual and Wireless Sensing Data for Trajectory Relationship Recognition

People usually form a social structure (e.g., a leader-follower, companion, or independent group) for better interactions among them and thus share similar perceptions of visible scenes and invisible wireless signals encountered while moving. Many mobility-driven applications have paid much attention to recognizing trajectory relationships among people. This work models visual and wireless data to quantify the trajectory similarity between a pair of users. We design a visual and wireless sensor fusion system, called ViWise, which incorporates the first-person video frames collected by a wearable visual device and the wireless packets broadcast by a personal mobile device for recognizing finer-grained trajectory relationships within a mobility group. When people take similar trajectories, they usually share similar visual scenes. Their wireless packets observed by ambient wireless base stations (called wireless scanners in this work) usually contain similar patterns. We model the visual characteristics of physical objects seen by a user from two perspectives: micro-scale image structure with pixel-wise features and macro-scale semantic context. However, we model characteristics of wireless packets based on the encountered wireless scanners along the user’s trajectory. Given two users’ trajectories, their trajectory characteristics behind the visible video frames and invisible wireless packets are fused together to compute the visual-wireless data similarity that quantifies the correlation between trajectories taken by them. We exploit modeled visual-wireless data similarity to recognize the social structure within user trajectories. Comprehensive experimental results in indoor and outdoor environments show that the proposed ViWise is robust in trajectory relationship recognition with an accuracy of above 90%.

Secure two-way transmission via untrusted UAV Relay: Joint path design and slot-pairing strategy

This paper proposes a novel two-way secure communication system that allows numerous pairs of ground users (GUs) communicate with one another using an untrusted UAV relay (UUR), where the UUR can eavesdrop on information while helping GUs perform two-way information transmission. We propose a safe scheme using slot pairing and joint path design to ensure the security of communication. Specifically, according to the physical-layer network coding (PNC) protocol, the collected information from GUs is cached in the UAV’s shock absorber before being transmitted as the UAV approaches optimal channel conditions. By matching the channel status of two-way transmission with the slot-pairing approach, our goal is to optimize the system’s secrecy sum rate (SSR). Due to the hybrid integer non-convex optimization problem, the formulated problem is difficult to address. As a result, we decompose it into three subproblems and propose an effective iterative algorithm that uses the block coordinate descent (BCD) approach and the sequential convex approximation (SCA) technique. The convergence and efficacy of our proposed scheme are demonstrated by numerical results.

User pairing impact on the performance of hybrid beamforming NOMA system

This paper proposes a new user pairing technique for a power domain nonorthogonal multiple access (NOMA) deploying fully connected and subconnected hybrid beamforming (HBF) structures for a typical urban microcell downlink of line-of-sight (LOS) and non-line-of-sight (NLOS) surroundings. NOMA system’s configurations are set up for two (multiple input single output) users per cluster down- linking base station equipped with 128 antennas. HBF processing adopts phased zero forcing (P-ZF) for both fully connected (HBFNOMA) structure (FCS) and sub-connected (HBF-NOMA) structure (SCS) precoders’ optimization, and successive interference cancellation zero forcing (SIC-ZF) schemes to optimize the SCS-HBF-NOMA precoder exploiting dynamic power allocation. The new users’ pairing exploits users’ distance to the base station, namely near and far clusters different from the benchmark angle of arrival- based users’ pairing. The proposed users’ pairing and the precoding schemes’ impact are investigated for finite-resolution HBF structures operating in LOS and NLOS surroundings. The execution under New York University (NYU) mmW channel model is explored for two users in a cluster with different angles of arrival. Results show that the users’ pairing based on AoA performs better than the newly proposed users’ pairing. However, the proposed users’ pairing scheme performs better than their corresponding OMA counterparts, which still make them beneficial for multiple access technique and a scenario, where one of the far cluster users need to access the base station for high data rate service and vice versa. Finally, the modified Liang processing scheme for quantizing SCS-HBF-NOMA precoder is capable of mitigating the quantization error arising from the NLOS environment and the nature of sub-connected (HBF) structure under a low SNR regime.

Distributed user pairing and effective computation offloading in aerial edge networks

Future Sixth-Generation (6G) mobile communication networks extremely require the global connectivity and the ground Base Stations (BSs) are difficult to develop in some specific areas, such as mountainous areas. Therefore, the aerial networks are the key framework for the future communications, in which the aerial vehicle could act as the access point. Additionally, Mobile Edge Computing (MEC) is also essential to enhance the data processing capabilities of aerial networks. In this paper, we study a comprehensive communication-computation resource management problem for jointly optimizing user pairing, power and time allocation in the MEC aided Cognitive Radio (CR) aerial networks, namely CR-MEC aerial networks. Explicitly, this multilevel optimization problem could be decomposed into the user pairing and power allocation as well as time allocation sub-problems. In the conceived CR-MEC aerial networks, we propose a User Pairing and Computation Offloading Management Algorithm (UPCOMA) based on three-sided matching theory, aiming to minimize the system’s energy consumption. At the first step of UPCOMA, multiple Primary Users (PUs) and Cognitive Users (CUs) on the ground negotiate to each other with the suitable power allocation coefficients and construct the stable user pairs. Moreover, the stable user pairs would match to a high altitude platform who act as the base station, which is for appropriately allocating Transmission Time Slots (TSs) at the second step of UPCOMA. Additionally, a hybrid offloading mode is proposed in our conceived networks in order to support ground users to offload their tasks adaptively according to their individual deadlines. Furthermore, the simulation results reveal that the relative performance of UPCOMA is close to that of the Brute-Force Search Algorithm (BFSA) with low complexity. Meanwhile, the hybrid offloading mode with less energy consumption supports much more ground user pairs to offload tasks compared to the binary mode.

Resource allocation algorithm in Heterogeneous Network Based on Non-orthogonal Multiple Access

The proposed resource allocation algorithm with joint power control and user pairing addresses the problem of degraded uplink user fairness due to cross-cell interference in NOMA uplink and improves user fairness. In the power control section, by decoupling power control from user pairing, the WOA algorithm is proposed in the statistical channel state scenario to solve the nonconvex optimization problem of intra-user pair fairness; in the user pairing section, the PTS algorithm is proposed to introduce randomness into the algorithm to improve the algorithm’s global search performance, solve the local optimum problem of integer programming, and improve inter-user pair fairness. Simulation results show that relative to the α-fairness comparison algorithm, the algorithm in this paper can improve fairness by about 5% under different interfering user densities, cell coverage radius, and tiny area transmit power.

Beta-blockers reduce severe exacerbation in patients with mild chronic obstructive pulmonary disease with atrial fibrillation: a population-based cohort study

Background and objectiveBeta-blockers (BBs) decrease mortality and acute exacerbation (AE) rates in patients with chronic obstructive pulmonary disease (COPD) and cardiovascular disease; however, information on their effects in patients with...

Metapath-guided multi-headed attention networks for trust prediction in heterogeneous social networks

Trust prediction facilitates the day-to-day functionality of diverse web-based applications, such as recommendation systems, market advertising and anomaly detection. However, existing works heavily rely on user–user trust interactions, which result in limited performance as the data sparsity. Previous studies have shown that the trust relationship between users is significantly affected by the category of items that the users interacted. In this paper, we propose a MetaTrust model, which generates redundant user-item interactions as the supplement of user–user trust to alleviate the data sparsity on trust prediction. Specifically, we propose category-aware metapaths, which generate abundant user–item–user interactions based on the common item category that users have interacted with. Further, Long Short Term Memory (LSTM) networks are utilized to mine features of multiple category-aware metapaths and their correlations. In order to filter the user–item–user interactions that are not related to the current task, the real trust relationship between users are embedd in the network with MLP. Finally, a multi-headed attention network is utilized to distinguish which metapath determines trust prediction between the current pair of users. Extensive experiments on three real-world dataset show that our proposed model can effectively achieve significant improvements over other competitive approaches and show the potential interpretability of trust building.

Risk of gastric cancer among long-term proton pump inhibitor users: a population-based cohort study.

To elucidate whether long-term proton pump inhibitor (PPI) users have an increased gastric cancer (GC) risk. We searched the 2009-2019 Korean National Health Insurance Services Database for patients aged > 40years who claimed for Helicobacter pylori eradication (HPE) during 2009-2014. The GC incidence following a PPI exposure of > 180 cumulative defined daily dose (cDDD) and that following an exposure of < 180 cDDD were compared. The outcome was GC development at least 1year following HPE. A propensity score (PS)-matched dataset was used for analysis within the same quartiles of the follow-up duration. Additionally, dose-response associations were assessed, and the mortality rates were compared between long-term PPI users and non-users. After PS matching, 144,091 pairs of PPI users and non-users were analyzed. During a median follow-up of 8.3 (interquartile range, 6.8-9.6) years, 1053 and 948 GC cases in PPI users and non-users, respectively, were identified, with the GC incidence (95% confidence interval (CI)) being 0.90 (0.85-0.96) and 0.81 (0.76-0.86) per 1000 person-years, respectively. The adjusted hazard ratio (aHR) for GC with PPI use was 1.15 (95% CI, 1.06-1.25). Among PPI users, patients in the highest tertile for annual PPI dose showed higher GC development than those in the lowest tertile (aHR (95% CI): 3.87 (3.25-4.60)). GC-related mortality did not differ significantly between PPI users and non-users. In this nationwide analysis in Korea, where the GC prevalence is high, long-term PPI use after HPE showed a significant increase in GC, with a positive dose-response relationship.

Outage analysis for user pairing based downlink C-NOMA network with receiver diversity techniques over $$\eta -\mu $$ fading channel

Outage analysis for user pairing based downlink C-NOMA network with receiver diversity techniques over $$\eta -\mu $$ fading channel

Acupuncture's long-term impact on depression prevention in primary dysmenorrhea: A 19-year follow-up of a Taiwan cohort with neuroimmune insights

BackgroundPrimary dysmenorrhea (PD) is a common gynecological condition causing depression. Acupuncture is an effective option for PD management but its effects on PD-associated depression remain unclear. MethodsA retrospective cohort study involving 35,099 propensity score-matched pairs of acupuncture users and non-users with PD was conducted using data from Taiwan's Longitudinal Generation Tracking Database 2000. Cox proportional hazard models were used to estimate depression risk, and bioinformatics analyses were performed to uncover underlying molecular mechanisms. ResultsThe risk of developing depression was reduced by 64 % in acupuncture users compared with non-acupuncture users during the 19-year follow-up period. The decrease was dose-dependent. Bioinformatics analyses identified 34 co-expressed targets for acupuncture, PD, and depression; and eight hub genes (coding for interleukin 6 and 1B, tumor necrosis factor, albumin, vascular endothelial growth factor A, C-reactive protein, prostaglandin-endoperoxide synthase 2, and brain-derived neurotrophic factor) potentially involved in the therapeutic effects of acupuncture. Several molecular pathways were found to be involved, including cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, cyclic adenosine 3′,5′-monophosphate signaling pathway, mitogen-activated protein kinase signaling pathway, serotonergic synapse, and estrogen signaling pathway. LimitationsBias in the selection of participants could have been introduced as a consequence of the retrospective nature of the study. Data were derived from a single national database, and acupuncture treatment details were unavailable. ConclusionAcupuncture may protect against the development of depression in patients with PD. This study provides insight into the potential molecular mechanisms underlying the therapeutic effects of acupuncture in PD management and depression prevention.

The impact of pre-ictal statin use on vasospasm and outcome in aneurysmal subarachnoid hemorrhage

BackgroundPleiotropic effects of statins may be beneficial in alleviating cerebral vasospasm (VS) and improving outcome after aneurysmal subarachnoid hemorrhage (aSAH). Initiation of statin treatment at aSAH is not recommended; however, the effect of pre-ictal and continued statin use is not fully investigated.MethodsRetrospective study comparing aSAH patients admitted in 2012 to 2021 with pre-ictal statin use versus those not using statins. Patient entry variables, radiological/sonological VS, symptomatic VS, and radiologically documented delayed cerebral ischemia (DCI) were registered. Outcome was scored in terms of mortality, modified Rankin score, Glasgow outcome score extended, and levels of fatigue. Patients were compared on group level and in a case–control design.ResultsWe included 961 patients, with 204 (21.2%) statin users. Statin users were older and had more often hypertension. Severe radiological/sonological VS, symptomatic VS, and DCI were less frequent in statin users, and their length of stay was shorter. Mortality, functional outcome, and levels of fatigue were similar in both groups. When analyzing 89 pairs of statin users and non-statin users matched for age, aSAH severity, gender, and hypertension, we confirmed decreased radiological/sonological and symptomatic VS as well as shorter length of stay in statin users. They also had more often a favorable functional outcome and lower levels of fatigue.ConclusionsPatients with pre-ictal and continued use of statins have a reduced occurrence of radiological/sonological and symptomatic VS, shorter length of stay, and more often favorable functional outcome, whereas mortality is similar to non-statin users. Even though larger multicenter studies with common, strict protocols for prevention, diagnosis, and treatment of vasospasm are needed to finally establish the value of statins in aSAH, continuation of pre-ictal statin use seems worthwhile.

Joint Trajectory Design and Power Allocation for UAV Assisted Network With User Mobility

This paper investigates the unmanned aerial vehicle (UAV) assisted wireless communications where the UAV acts as the aerial base station to provide downlink data service to the ground users. We consider a typical hot-spot scenario in which the ground users move towards the target points of interests (PoIs) in groups. The UAV can also fly in air to cope with the movement of users. To maximize the system throughput, an optimization problem is formulated to jointly determine the subchannel assignment, the trajectory of UAV and its power allocation per time slot, where the navigation power of UAV, the co-channel interference as well as the quality of service (QoS) requirements of users are taken into account. As the problem is non-convex and hard to solve, we propose a cascade approach. First, we design a user clustering and pairing algorithm to accomplish the subchannel assignment. Then, we apply the block coordinate descent (BCD) based framework to decompose the remaining problem into the power allocation sub-problem and the trajectory design one. The sub-optimal solution can be gradually achieved through alternatively solving these two sub-problems. As for the power allocation sub-problem, we opt to the difference of convex (DC) functions form and the successive convex approximation (SCA) method to solve it. While for the trajectory design sub-problem, the auxiliary variables and SCA method are utilized. Vivid simulation results reveal that the proposed iterative algorithm can well satisfy the QoS of users and achieve significant performance gain compared with other benchmark schemes.

A Unified NOMA Framework in Beam-Hopping Satellite Communication Systems

This paper investigates the application of a unified non-orthogonal multiple access framework in beam hopping (U-NOMA-BH) based satellite communication systems. More specifically, the proposed U-NOMA-BH framework can be applied to code-domain NOMA based BH (CD-NOMA-BH) and power-domain NOMA based BH (PD-NOMA-BH) systems. To satisfy dynamic-uneven traffic demands, we formulate the optimization problem to minimize the square of discrete difference by jointly optimizing power allocation, carrier assignment and beam scheduling. The non-convexity of the objective function and the constraint condition is solved through Dinkelbach's transform and variable relaxation. As a further development, the closed-from and asymptotic expressions of outage probability are derived for CD/PD-NOMA-BH systems. Based on approximated results, the diversity orders of a pair of users are obtained in detail. In addition, the system throughput of U-NOMA-BH is discussed in delay-limited transmission mode. Numerical results verify that: i) The gap between traffic requests of CD/PD-NOMA-BH systems appears to be more closely compared with orthogonal multiple access based BH (OMA-BH); ii) The CD-NOMA-BH system is capable of providing the enhanced traffic request and capacity provision; and iii) The outage behaviors of CD/PD-NOMA-BH are better than that of OMA-BH.

Energy-Aware Mode Selection for D2D Resource Allocation in 5G Networks

This paper proposes an energy-aware mode-selection mechanism for device-to-device (D2D) resource allocation in the coexisting 5G network environment of D2D users and traditional cellular users by taking into consideration the mechanisms of mode selection, transmit power, and spectrum resource allocation simultaneously. In the proposed approach, all spectrum resources are fully shared by traditional cellular users and D2D users. We first determine the communication mode of all users after considering the transmission opportunity of traditional cellular users and analyzing the interference degree of different D2D communication modes. Next, we divide all users into three tiers according to the distances between users and the base station to solve the interference problem generated by excessing transmit power in uplink transmission. Afterward, based on the different communication modes, corresponding spectrum resource allocation mechanisms using the Hungarian algorithm are developed. We simulate a single cell environment using Python language and perform several simulations for different pairs of traditional cellular users and D2D users. The simulation results reveal that the proposed approach outperforms the proposed approach by Hou et al. in system throughput. With power control, the energy efficiency of the proposed approach could be enhanced by 20%.

User group-based pilot allocation and data power optimization in cell-free massive MIMO for coexistence of UAVs and ground users

To address the pilot contamination issue in cell-free massive multi-input multi-output (MIMO) systems supporting simultaneous communication between unmanned aerial vehicles (UAVs) and ground users (GUEs), a user group-based pilot allocation algorithm is proposed. Furthermore, the system performance is enhanced by optimizing the data power. Initially, the distances between users and pilots are calculated based on the principles of maximizing spectral efficiency and utilizing the large-scale fading matrix. Ground users and UAVs are randomly divided into two groups: primary users and shared users. The contamination intensity between users is measured based on the distance between users and pilots, and shared user pairs that are allocated the same orthogonal pilots are generated. Next, a user-centric approach is employed to select a subset of access points (APs) to serve the users. The scalable fractional power optimization strategy is combined as a power optimization scheme for uplink data transmission, providing a controllable trade-off between user fairness and average spectral efficiency. Simulation results demonstrate that the user group-based pilot allocation algorithm significantly improves the system’s overall spectral efficiency, and the fractional power optimization algorithm enhances the average spectral efficiency of the system.

Preferential attachment with reciprocity: properties and estimation

Abstract Reciprocity in social networks is a measure of information exchange between two individuals, and indicates interaction patterns between pairs of users. A recent study finds that the reciprocity coefficient of a classical directed preferential attachment (PA) model does not match empirical evidence. Towards remedying this deficiency, we extend the classical three-scenario directed PA model by adding a parameter that controls the probability of creating a reciprocal edge. This proposed model also allows edge creation between two existing nodes, making it a realistic candidate for fitting to datasets. We provide and compare two estimation procedures for fitting the new reciprocity model and demonstrate the methods on simulated and real datasets. One estimation method requires careful analysis of the heavy tail properties of the model. The fitted models provide a good match with the empirical tail distributions of both in- and out-degrees but other mismatched diagnostics suggest that further generalization of the model is warranted.