Link Interference Research Articles

Anxiety and fear of cancer recurrence as predictors of subsequent pain interference in early cancer survivorship: Exploring the moderating roles of cognitive and emotional factors.

Following treatment, cancer survivors often experience pain that negatively impacts their quality of life. Although both anxiety and fear of cancer recurrence (FCR) have been shown to exacerbate pain interference, less is known about either the temporal relationship between anxiety/FCR and pain interference or modifiable cognitive/emotional factors that might moderate that relationship among cancer survivors. This longitudinal study aims to advance our understanding of the impact of both anxiety and FCR following primary cancer treatment on subsequent pain interference. We also examined potentially modifiable moderators (i.e., cancer-related illness beliefs and emotion regulation difficulties) of the relationship between anxiety/FCR and subsequent pain interference. Adults (N = 397; 67% female; Mage = 59.1 years) diagnosed with breast, colorectal, or prostate cancer completed self-report measures at baseline (average of 2.5 months following treatment completion) and at 6-month follow-up. Both greater anxiety and FCR not only predicted subsequent pain interference, but also predicted increases in pain interference over time. Additionally, complex interaction patterns were observed between anxiety and the potential moderators on pain interference. Specifically, lower Personal Control beliefs and higher Consequences beliefs were associated with greater pain interference for those with lower levels of anxiety/FCR. Emotion regulation difficulties also moderated the anxiety-pain interference link (i.e., was more strongly associated with greater pain interference at lower levels of anxiety), but not the FCR-pain link. Chronicity beliefs did not interact with anxiety or FCR in predicting pain interference. This study advances our understanding of the role of anxiety/FCR on pain interference over time as well as potential psychological treatment targets for individuals at greater risk for longer-term pain following cancer treatment.

Resource allocation for device-to-device communications underlaying uplink cellular networks

Underlying cellular networks, device-to-device (D2D) communications are a practical network technology that can increase power efficiency and spectrum usage for close-proximity wireless services and applications. However, D2D link interference, when sharing resources with cellular users (CUs), poses a major challenge in such distribution situations. In this research, we primarily utilize wireless channel data that exhibits slowly shifting large-scale fading to conduct spectrum sharing and power allocation. The overall ergodic capacity of all cellular user equipment (CUE) links is initially considered as the optimization target in order to maximize the overall throughput of CUE links while ensuring the reliability of each D2D link. Then, the expansion of the minimum ergodic capacity is measured to ensure a more consistent capacity performance across all CUE links. We utilized algorithms that are resilient to channel fluctuations and produce optimal resource allocation. We use MATLAB, and the computer simulation validates its intended performance.

Research on collaborative multi-UAV localization method based on combination navigation information

In challenging environments, unmanned aerial vehicle (UAV) systems often encounter unstable satellite signals and communication link interference. This paper proposes an integrated navigation method that integrates inertial navigation system (INS), global navigation satellite system (GNSS), and visual navigation system (VNS). Utilizing data from onboard sensors, this method merges relative navigation information from feature tracking of multiple UAVs with each UAV’s absolute navigation data. It includes specially designed transmission rules to reduce data exchange between UAVs. Each UAV uses an adaptive unscented Kalman filter (AUKF) method, which is enhanced into a collaborative AUKF (C-AUKF) using a message passing-based approach. Experiments in a simulated mission scenario revealed that the C-AUKF, in comparison to using extended Kalman filter (EKF), significantly improved flight test performance across the entire testing area, with a cumulative deviation of only 10.22 m, about 0.85% of the total flight distance. These results demonstrate that the proposed method not only meets accuracy requirements for position and velocity in integrated navigation but also significantly enhances multi-UAV navigation precision, particularly in scenarios with global positioning system (GPS) interference.

Intelligent interference cancellation and ambient backscatter signal extraction for wireless-powered UAV IoT network

Unmanned aerial vehicles (UAVs) offer a new approach to wireless communication, leveraging their high mobility, flexibility, and visual communication capabilities. Ambient backscatter communication enables Internet of Things devices to transmit data by reflecting and modulating ambient radio waves, eliminating the need for additional wireless channels, and reducing energy consumption and cost for sensors. However, passive ambient backscatter communication has limitations such as limited range and poor communication quality. By utilizing UAVs as communication nodes, these limitations can be overcome, expanding the communication range and improving the quality of communication. Although some research has been conducted on combining UAVs and ambient backscatter, several challenges remain. One key challenge is the strong direct link interference in ambient backscatter under UAV conditions, which significantly affects communication quality. In this paper, we propose an intelligent backward and forward straight link interference cancellation algorithm based on NOMA decoding technique to enhance ambient backscatter communication quality under UAV conditions and extract more ambient energy for UAV energy supply. The paper includes theoretical derivation, algorithm description, and simulation analysis to validate the error bit rate of labeled information bits. The results demonstrate that the forward algorithm reduces the error bit rate by approximately 20% under low signal-to-noise ratio (SNR) conditions, while the backward algorithm reduces the error bit rate under high SNR conditions. The combination of the forward and backward algorithms reduces the error bit rate under both high and low SNR conditions. The proposed method contributes to improving the quality of ambient backscatter communication in UAV settings.

Direct Link Interference Suppression for Bistatic Backscatter Communication in Distributed MIMO

Backscatter communication (BC) is a promising technique for future Internet-of-Things (IoT) owing to its low complexity, low cost, and potential for energy-efficient operation in sensor networks. There are several network infrastructure setups that can be used for BC with IoT nodes. One of them is the bistatic setup where typically there is a need for high dynamic range and high-resolution analog-to-digital converters at the reader. In this paper, we investigate a bistatic BC setup with multiple antennas. We propose a novel transmission scheme, which includes a protocol for channel estimation at the carrier emitter (CE) as well as a transmit beamformer construction that suppresses the direct link interference between the two ends of a bistatic link (namely CE and reader), and increases the detection performance of the backscatter device (BD) symbol. Further, we derive a generalized log-likelihood ratio test (GLRT) to detect the symbol/presence of the BD. We also provide an iterative algorithm to estimate the unknown parameters in the GLRT. Finally, simulation results show that the required dynamic range of the system is significantly decreased, and the detection performance of the BD symbol is increased, by the proposed algorithm compared to a system not using beamforming at the CE.

Energy-Efficient Topology Control Mechanism for IoT-Oriented Software-Defined WSNs

In time-varying software-defined wireless sensor networks (SDWSNs) for Internet-of-Things (IoT) applications, the topology may change due to the interference or abnormal events, thus leading to network performance degradation. In this paper, an energy-efficient topology control (TC) mechanism applied for IoT-oriented SDWSNs is proposed to maximize the network energy efficiency (EE) during the dynamic topology maintenance. First, a hierarchical SDWSN architecture consisting of the cluster-based sensing network and the programmable relay network is presented. Second, two TC algorithms based on the link EE are proposed to apply in the cluster and relay sub-networks of SDWSN, respectively. In the cluster sub-network, the proposed distributed TC algorithm enables the link interference mitigation by employing power control and rate allocation in each cluster. In the relay sub-network, the proposed centralized TC algorithm first utilizes a specified model to construct the original topology. During the dynamic topology maintenance, the proposed centralized TC algorithm is realized by the value-iteration learning method based on a Markov decision process (MDP) model, upon which the state-transition probability (STP) of the relay sub-network is obtained, where the relay-network state is composed of the link, the queue, and the residual energy ratio states for all nodes in the relay sub-network. Finally, simulation results show that both two TC algorithms can improve the corresponding sub-network EE of time-varying SDWSN.

Exploiting Constructive Interference for Backscatter Communication Systems

Backscatter communication (BackCom), one of the core technologies to realize zero-power communication, is expected to be a pivotal paradigm for the next generation of the Internet of Things (IoT). However, the "strong" direct link (DL) interference (DLI) is traditionally assumed to be harmful, and generally drowns out the "weak" backscattered signals accordingly, thus deteriorating the performance of BackCom. In contrast to the previous efforts to eliminate the DLI, in this paper, we exploit the constructive interference (CI), in which the DLI contributes to the backscattered signal. To be specific, our objective is to maximize the received signal power by jointly optimizing the receive beamforming vectors and tag selection factors, which is, however, non-convex and difficult to solve due to constraints on the Kullback-Leibler (KL) divergence. In order to solve this problem, we first decompose the original problem, and then propose two algorithms to solve the sub-problem with beamforming design via a change of variables and semi-definite programming (SDP) and a greedy algorithm to solve the sub-problem with tag selection. In order to gain insight into the CI, we consider a special case with the single-antenna reader to reveal the channel angle between the backscattering link (BL) and the DL, in which the DLI will become constructive. Simulation results show that significant performance gain can always be achieved in the proposed algorithms compared with the traditional algorithms without the DL in terms of the strength of the received signal. The derived constructive channel angle for the BackCom system with the single-antenna reader is also confirmed by simulation results.

Modeling blockages and link dependency in millimeter wave communication networks using Matérn Hard-Core Point Process

With the pursuit of higher transmission rate, millimeter wave (mmWave) communication has become one of the propelling technologies in wireless communications. Due to its short wavelength, a mmWave signal suffers from significant path loss and is heavily affected by obstructions and reflections caused by blockages. Moreover, the interference links are dependent as the locations of base stations are not independent in practical deployment. And the link dependency in the densely deployed mmWave communication networks cannot be ignored, which makes coverage analysis even more complicated. In this paper, we investigate the coverage model incorporating the Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) links of both signal and interference, to comprehensively portray the performance of mmWave networks with randomly distributed blockages. Further, we capture the dependency between interfering links with the copula function to model the received aggregate interference more accurately. The probability density function of the received power, Signal-to-Interference-plus-Noise Ratio (SINR), and outage probability are characterized to theoretically quantify the impact of blockages and interference. The proposed analytical model perfectly models the impact of blockages and link dependency, and obtains the cumulative distribution function (CDF) of the SINR with a gap less than 0.2% compared to the Monte-Carlo simulation.

ROS-Based Collaborative Driving Framework in Autonomous Vehicular Networks

This paper investigates the optimal data transmission for collaborative driving in autonomous vehicular networks (AVNs). We consider that vehicles communicate with each other based on the definition of Robot Operating System (ROS), which is a pervasively adopted middleware operating system for autonomous vehicles such as Baidu Apollo. ROS defines a publish/subscribe scheme for inter-vehicular communications, in which vehicles subscribe to “topics” published by adjacent vehicles; a “topic” is related to the real-time sensing/computing data that a vehicle intends to share with nearby neighbors, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , radar or camera images captured. By sharing various sensing data using different topics at the real-time, vehicles in the same area therefore can collaboratively drive with cooperative perception and computing. However, multiple data flows for different topics would coexist along overlapping transmission paths during this process. As a result, a fundamental issue raised is how to schedule the contending data flows in the mobile and bandwidth-constrained vehicular networks. In this paper, we model the ROS-based publish/subscribe scheme as an optimization problem which jointly considers the power allocation and conflict avoidance of the communication process in AVNs. By applying the Lyapunov Optimization, we decompose the model to calculate the power and sub-carrier proportion on each node while avoiding link conflicts, and finally obtain the optimal resource allocation strategy. By combining the corresponding link conflict constraints, we are able to encapsulate the optimization model in a stable set to efficiently avoid link conflicts, and thereby reduce the resource waste caused by the link interference and data flow conflicts. Using simulations, we show that our method has good advantages in resource optimization.

Evolutionary generative adversarial network based end-to-end learning for MIMO molecular communication with drift system

Molecular communication (MC) is a novel paradigm for nano-communication networks. Compared with diffusion-based single-input single-out (SISO) systems, multiple-input multiple-output (MIMO) MC with drift systems can effectively mitigate the negative effects of inter symbol interference (ISI), inter link interference (ILI) and noise, further improving transmission efficiency. The modeling complexity of MIMO MC systems inspires the application of deep learning (DL) techniques to establish end-to-end architectures for signal recovery. However, training of the entire end-to-end system is limited by the unknown channel and small training sample size. In this paper, aiming at signal recovery of the newly developed mathematical MIMO MC with drift system model, a Kullback–Leibler divergence (KLD) evolutionary generative adversarial network (EGAN)-based end-to-end learning method is proposed. The end-to-end architecture can be trained offline with both the sampled and fake signals generated by KLD EGAN, even with a small training sample size, and then used to recover online transmitted signals directly. Besides, two traditional detection algorithms denoted as the maximum a posterior (MAP) detector and fixed threshold (FT) detector, are proposed as well for theoretical comparison. Experiments of the effect of different model parameters on the system performance have been carried out. Results validate the effectiveness and robustness of our proposed method compared to other DL-based methods, including the deep neural networks (DNN)-based, the original GAN-based, and the original EGAN-based, in terms of transmission accuracy.

On DoF Conservation in MIMO Interference Cancellation Based on Signal Strength in the Eigenspace

Degree-of-freedom (DoF)-based models have been proven to be highly successful in modeling and analysis of MIMO systems. Among existing DoF-based models, the number of DoFs used for interference cancellation (IC) is solely based on the number of interfering data streams. However, from both experimental and simulation results, we find that signal strengths of an interference link vary significantly in different directions in the eigenspace. In this paper, we exploit the difference in interference signal strengths in the eigenspace and perform IC with DoFs only on those directions with strong signals. To differentiate interference signal strengths on an interference link, we introduce a novel concept called ‘`effective rank threshold.’' Based on this threshold, DoFs are consumed only to cancel strong interferences in the eigenspace while weak interferences are treated as noise in throughput calculation. To better understand the benefits of this approach, we study a fundamental trade-off between network throughput and effective rank threshold for an MU-MIMO network. Our simulation results show that network throughput under optimal rank threshold is significantly higher than that under existing DoF IC models. To ensure the new DoF IC model is feasible at PHY layer, we propose an algorithm to set the weights for all nodes that can offer our desired DoF allocation.

Joint Effects of Co-Channel Interferences and Pointing Errors on Dual-Hop Mixed RF/FSO Fixed-Gain and Variable-Gain Relaying Systems

The performance of a dual-hop mixed radio frequency (RF)/free space optical (FSO) system with co-channel interferences (CCIs) is studied for both fixed-gain and variable-gain amplify-and-forward(AF) relaying scenarios. The RF link and interference link undergo the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> shadowed fading and the FSO link experiences the Fisher-Snedecor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\cal F}$</tex-math></inline-formula> distribution with pointing errors. For the considered system, we derive new closed-form expressions for the probability density function (PDF), cumulative distribution function (CDF), and average bit error rate (BER) of the end-to-end signal-to-interference-plus-noise ratio (SINR). In addition, efficient numerical expressions for the ergodic capacity are also obtained. Moveover, the asymptotic expressions for the CDF and average BER are derived. Our results can be regarded as a generalization of the previous results. Finally, numerical and simulation results are presented to verify the correctness of the proposed expressions.

RIS-Empowered Ambient Backscatter Communication Systems

Passive tags must harvest sufficient energy to operate. However, ensuring the tag’s energy needs and simultaneously suppressing the interference in ambient backscatter systems is challenging. To meet this, we employ a reconfigurable intelligent surface (RIS) to amplify the ambient source signal that reaches the tag. We maximize the achievable rate by optimizing the RIS phase-shifts subject to the tag’s energy harvesting constraint. Specifically, the phase-shifts are optimized to increase the tag’s received power while suppressing the direct-and-RIS-cascaded link interference. The optimization problem is non-convex, and we convexify it by means of fractional programming and a quadratic transformation. In comparison to a benchmark, our optimal phase-shift design provides ~150% and ~250% gains in harvested power and achieved rate, respectively, at 20 dB m transmit power.

Research on Performance of Wireless Ultraviolet Communication Interference Link

Research on Performance of Wireless Ultraviolet Communication Interference Link

Real-Time Fuzzy Logic Control of Two-Link Flexible Manipulators

This study investigates the development of a Fuzzy Logic Controller (FLC) for tracking a sinusoidal wave trajectory and suppressing the vibration of a Two Link Flexible Manipulator (TLFM). The TLFM was modeled using Lagrange's formalism and the Assumed Mode Method (AMM). A three-part apparatus consisting of a TLFM mathematical model, a real-world TLFM, and control software was designed and implemented. The FLC was applied to both the simulated and real-world TLFM. The robustness of the FLC was investigated by considering variable payload mass and link angular velocity in both constructive and destructive link interference trajectory cases. Simulation and experimental results show the effectiveness and robustness of the proposed FLC.

Network-Coded Cooperative Systems in Cognitive Radio Networks

We study the performance of a network-coded cooperative (NCC) system in an underlay cognitive radio network (CRN). The primary network (PN) consists of a single transmitter-receiver pair, and the secondary network (SN) is an NCC system with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> users, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> relays, and a single destination. The relays employ decode-and-forward (DF) protocol and use network coding (NC). We study the performance of the SN under two types of power constraints: i) the combined peak interference power constraint on the PN and maximum transmit power constraint at the SN; and ii) the single peak interference power constraint on the PN. For the SN, an exact closed-form expression and an asymptotically tight end-to-end outage probability are derived, and the diversity order and coding gain are quantified. Compared to the existing literature, the proposed CRN NCC has four main distinguishable features: i) it applies to general CRN NCC network settings with an arbitrary number of users and relays; ii) it considers general relay selection mechanism and independent and non-identically distributed (i.n.i.d.) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Nakagami-m$ </tex-math></inline-formula> fading channels; iii) it assumes secondary-to-primary and primary-to-secondary interference links; and iv) it provides a generalization of previous work and includes existing results in the literature as special cases.

Adaptively prioritizing candidate forwarding set in opportunistic routing in VANETs

Opportunistic routing (OR) paradigms in vehicular networks via opportunistic candidate set selection have a better performance over the pre-defined next-hop node in terms of packet delivery rate. Nevertheless, uneven vehicle distribution, highly dynamic topology, varying link interference, and bandwidth restrictions impose drastic challenges for satisfying applications requirements in static prioritizing candidate set selection policies. Besides, fulfilling quality of service (QoS) requirements of heterogeneous applications, due to the limited local topology perspective and many involving conflicting routing criteria, will be further compromised. Considering the candidate set selection policy as a Multi-Criteria Decision Making (MCDM) task, an adaptive two-hop cooperative forwarding set selection strategy called APFS is proposed in this paper. By developing a local topology perspective to the two-hop neighbor information, the APFS scheme jointly considers indicators of link stability, delay assessment, and link good-put as routing criteria. Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are employed in two different scenarios in prioritizing candidate forwarding sets. First, classical AHP-TOPSIS technique with a mutable pair-wise comparison matrix is applied, and then Neutrosophic Set (NS) is combined with the classical AHP-TOPSIS method to handle ambiguous vehicular environments. The simulation results show that the APFS strategy using both prioritization policies have significantly improved the performance of packet delivery ratio, average end-to-end delay, throughput, and hop counts as compared to other schemes.

Channel Measurements and Modeling for Low Terahertz Communications in an Aircraft Cabin

The low terahertz band (0.1–1 THz) offers very high data rates for novel mobile applications and constitutes a promising candidate to meet the requirements in aviation, enabling future wireless in-flight entertainment (IFE) systems. An extensive knowledge of the propagation effects in the radio channel in complex scenarios is a prerequisite to successfully design a communication system. This article presents a measurement campaign in a real aircraft investigating the radio channel at 300 GHz for different deployments of a wireless IFE system. The propagation effects as well as temporal and spatial channel characteristics are analyzed for likely communication links between an access point and a user equipment (UE). In the same way, interference links between two UEs are studied, reporting transmission and reflection losses for various components of the aircraft. A deterministic and geometry-based channel model is derived and extended to cover the effect of human blockage that suggests an integration of the access point into the passenger service unit. The measurement and realistic path loss models can be used in further link and system level simulations and contribute to the design of future IFE systems.

Outage Analysis of Multiuser MIMO-NOMA Transmissions in Uplink Full-Duplex Cooperative System

This letter merges the advantages of non-orthogonal-multiple-access (NOMA) and multi-antenna communication in a full-duplex (FD) uplink cooperative system, where two cellular users communicate with a base-station (BS). A cooperative FD relay is applied to assist the cell-edge user. To consider the effects of practical communications, interference links are regarded under imperfectly canceling mode. To remove the effect of interference signals at the BS, the zero-forcing (ZF) method is used. Outage probabilities are derived in closed-form. The simulation results reveal by applying ZF in BS and suppressing interference, FD mode achieves better outage performance than half-duplex (HD) in uplink cooperative multi-antenna NOMA communication.

The kinematics and design for isotropy of six-dof 3-CCC parallel mechanisms of general geometry and arbitrary actuation schemes

Parallel mechanisms (PMs) of the 3-CCC class exhibit many attractive features, such as decoupled motion, degenerated singularity, simple forward-kinematics relations and high dexterity, making them promising in many applications. However, in order to simplify the analysis, existing research mainly focuses on its several subclasses, leading to drawbacks such as limited choices of the architecture parameters, excessive link interference and limited orientation workspace. In this paper, a uniform formulation is proposed for the kinematics analysis of the whole class of 3-CCC PMs of general geometry and arbitrary actuation schemes; the geometric meanings of the relevant quantities are revealed, significantly simplifying the analysis of 3-CCC PMs. Next, the design for isotropy of the whole class of 3-CCC PMs is investigated, yielding a large set of isotropic designs, including a subset admitting a continuous isotropy locus; several typical layouts with attractive features are proposed thereafter, including designs admitting unlimited rotation about a fixed or an adjustable direction. The results above can also be applied to six-dof PMs with more sophisticated topologies, as long as they are kinematically equivalent to 3-CCC PMs.