Aerial wardens could pose significant security threats to satellite-ground communications due to their stronger received signals than legitimate ground users. To address this issue, the signals from all jamming satellites in low Earth orbit satellite networks, i.e., full jamming strategy (FJS), are utilized to counter the detection of the aerial warden. However, this worsens the communication quality of ground users. To improve it, we utilize the difference in visible spherical crowns between the ground user and the aerial warden due to the Earth blockage to propose the safeguard-zone strategy (SGS) via merely muting the jamming satellites visible to the ground user. To evaluate the effectiveness of the proposed strategies, we propose a stochastic geometry-based analytical framework to derive the covert probability and connection probability. To capture the trade-off between covertness and reliability, the effective covert rate, defined as the product of transmission rate, covert probability, and connection probability, is also analyzed and optimized. The results validate the accuracy of the analytical expressions and illustrate that SGS outperforms the FJS in the connection probability and effective covert rate with a small loss in covert probability, which can be compensated by increasing the transmit power or the number of jamming satellites.

Ultra-wideband (UWB) based positioning with fewer anchors has attracted significant research interest in recent years, especially under energy-constrained conditions. However, most existing methods rely on discrete-time representations and smoothness priors to infer a robot's motion states, which often struggle with ensuring multi-sensor data synchronization. In this article, we present a continuous-time UWB-Inertial-Odometer localization system (CT-UIO), utilizing a non-uniform B-spline framework with fewer anchors. Unlike traditional uniform B-spline-based continuous-time methods, we introduce an adaptive knot-span adjustment strategy for non-uniform continuous-time trajectory representation. This is accomplished by adjusting control points dynamically based on movement speed. To enable efficient fusion of inertial measurement unit (IMU) and odometer data, we propose an improved extended kalman filter (EKF) with innovation-based adaptive estimation to provide short-term accurate motion prior. Furthermore, to address the challenge of achieving a fully observable UWB localization system under few-anchor conditions, the virtual anchor (VA) generation method based on multiple hypotheses is proposed. At the backend, we propose an adaptive sliding window strategy for global trajectory estimation. Comprehensive experiments are conducted on three self-collect datasets with different UWB anchor numbers and motion modes. The result shows that the proposed CT-UIO achieves$0.403m$,$0.150m$, and$0.189m$localization accuracy in corridor, exhibition hall, and office environments, yielding$17.2\%$,$26.1\%$, and$15.2\%$improvements compared with competing state-of-the-art UIO systems, respectively. The codebase and datasets of this work will be open-sourced athttps://github.com/JasonSun623/CT-UIO.

As uncrewed aerial vehicles (UAVs) are widely used in many communication scenarios, the issue of security has also caused much concern due to the line-of-sight propagation. Therefore, in this paper, we study an air-to-ground covert communication system, where a UAV transmitter Alice transmits messages covertly to a ground receiver Bob under the communication behavior detection of a ground warden Willie with location uncertainty and concurrent interference from other ground environmental nodes whose locations follow a two-dimensional Poisson point process. Under this setup, we first provide the approximate probability distribution of the aggregated interference power from all environmental co-channel nodes to facilitate the covert analysis. Then, we derive the average covert probability separately for two cases: case 1 assumes that Willie knows the received power from Alice; case 2 assumes that Willie knows the probability distribution of the received power from Alice. Next, we derive the connection probability and the covert throughput which is the maximal transmission rate under the covertness and reliability constraints. Numerical results demonstrate the feasibility of air-to-ground covert communication with location and interference uncertainty. The results also show the average covert probability and covert throughput in case 2 are higher than that in case 1, especially for a sparse deployment of interfering nodes.

The combination of reconfigurable intelligent surface (RIS) and integrated sensing and communication (ISAC) can improve the resource utilization in non-line-of-sight scenarios. To sense the target with high accuracy, it is necessary to directionally reflect the sensing signal toward the sensing target via the RIS, improving the sensing performance. However, enhancing signal quality may increase the risk of information leakage when the sensing target is the warden. Against this background, we investigate a covert transmission problem in an RIS assisted ISAC system. Specifically, we obtain a tractable form of covertness constraint in terms of minimum detection error probability via the optimal detection threshold. Then, we maximize the sum covert transmission rate by jointly optimizing the beamforming of confidential signal and jamming signal as well as the RIS’s phase shift, while ensuring the reliability, covertness and sensing constraints. Owing to the effectiveness of the deep reinforcement learning algorithm in processing high-dimensional data and making intelligent decision, we propose a twins-deep deterministic policy gradient-based joint covert beamforming and the phase shift of RIS optimization (TD3-CBP) algorithm to solve the above non-convex problem. Finally, simulation results demonstrate the effectiveness of the proposed TD3-CBP algorithm in the covertness performance, achieving an average of 16.1 % higher sum covert transmission rate than the benchmark algorithms.

The long propagation delay makes the delay characteristics of data transmission in low Earth orbit (LEO) satellite networks limited by retransmission. Therefore, this paper focuses on the retransmission delay characteristics through analyzing the local delay, defined as the mean times required for the serving satellite successfully transmitting the message to the ground user. We propose a general analytical framework to evaluate the local delay in massive LEO satellite-to-ground downlink networks. Specifically, binomial point process is used to model the locations of satellites. Considering Nakagami fading and directional transmission, we derive the conditional success probability under a given network topology. On this basis, we first give an exact expression for the local delay and further provide an asymptotic analysis when the signal-to-interference-plus-noise ratio tends to zero and infinity. Additionally, we analyze the local delay in three special cases: noise-limited, Rayleigh fading and infinite antenna array of satellite. Numerical results verify our analysis and show that Rayleigh fading model and the asymptotic analysis can simplify and effectively approximate the exact result of the local delay under Nakagami fading.

Integrated sensing and communication (ISAC) is expected to enable the fifth-generation (5G) networks to provide ubiquitous communication and sensing. However, some high-dynamic scenarios hinder applications of conventional ISAC schemes owing to the high overhead and poor real-time performance. In this paper, we design a novel ISAC architecture and propose a large language model (LLM) based two-stage beamforming prediction scheme. Specifically, in the first stage, we develop an LLM-based approach to predict the future channel state information (CSI) according to the history echoes. Via the data preprocessing and supervised fine-tuning, the LLM can achieve effective channel prediction task with unstructured data. In the second stage, according to the predicted/estimated CSI, we formulate a beamforming optimization problem to maximize the achievable sum rate while satisfying the quality of service (QoS). Then, we propose a Primary-dual network with the unsupervised adversarial learning to handle it, facilitating the on-line beamforming. Simulation results verify that, compared with the benchmarks, our proposed beamforming prediction scheme not only enjoys a higher channel prediction accuracy but also achieves a better balance between the performance and computational complexity.

Proactive wardens can generate interference to enhance the detection performance, posing severe security threats to the legitimate transmission. Fortunately, an intelligent reflecting surface (IRS) can facilitate the covert transmission towards the proactive wardens by reconfiguring wireless channels. In this paper, we propose an IRS-assisted covert communication scheme with finite blocklength, where a proactive warden is monitoring and jamming the transmission simultaneously. Based on the warden’s optimal threshold, we can minimize the detection error probability, which is the worst case for the covert transmission. We then derive two constraints on the average covertness utilizing the Gaussian-Chebyshev integral and upper bound scaling, respectively. Subsequently, we calculate the average decoding error probabilities for both the optimal and random IRS phases. To improve the effective throughput while ensuring the covertness, the transmit power, transmission rate, and blocklength are jointly optimized. After deriving the optimal transmit power and transmission rate, the blocklength can be obtained in a closed form or via the numerical searching based on its serving range. Simulation results are presented to demonstrate the superiority of the proposed scheme, and the tradeoff between the covertness and the effective throughput is revealed.

A robust secure beamforming scheme for the IRS-aided ISAC with imperfect channel state information (CSI) is investigated in this paper, where a device-to-device (D2D) pair is utilized as a cooperative jammer to interfere with the eavesdropping target. Based on a statistical CSI error model, an optimization problem is formulated to minimize the transmit power by jointly optimizing the transmit beamforming and IRS phase shifts, subject to the constraints on the secrecy rate, the D2D communication rate, and the echo signal-to-noise ratio. To address this non-convex problem, we first utilize the Bernstein-type inequality to convert the robust probabilistic constraints into linear matrix inequality forms. Then, it is decomposed into two subproblems, and an alternating optimization algorithm based on the semi-definite relaxation is developed to solve them iteratively. Numerical results verify the effectiveness and robustness of the proposed scheme for secure ISAC.

The combination of reconfigurable intelligent surface (RIS) and integrated sensing and communication (ISAC) can improve the resource utilization in non-line-of-sight scenarios. However, the private information in this situation raises security concerns when the transmission behavior is detected by wardens. Against this background, we investigate a covert transmission problem in an RIS assisted ISAC system. Specifically, we obtain a tractable form of covertness constraint in terms of minimum detection error probability via the optimal detection threshold, paving the way for optimization process. Then, the sum covert transmission rate is maximized by jointly optimizing the beamforming of confidential signal and jamming signal as well as the RIS’s phase shift. To solve the above non-convex problem, we propose a joint covert beamforming and the phase shift of RIS optimization-based twins-deep deterministic policy gradient (CBP-TD3) algorithm. Finally, simulation results demonstrate the effectiveness of the proposed CBP-TD3 algorithm in the covertness.

Abstract Driven by the vision of ubiquitous connectivity and wireless intelligence, the evolution of ultra-dense constellation-based satellite-integrated Internet is underway, now taking preliminary shape. Nevertheless, the entrenched institutional silos and limited, nonrenewable heterogeneous network resources leave current satellite systems struggling to accommodate the escalating demands of next-generation intelligent applications. In this context, the distributed satellite information networks (DSIN), exemplified by the cohesive clustered satellites (CCS) system, have emerged as an innovative architecture, bridging information gaps across diverse satellite systems, such as communication, navigation, and remote sensing, and establishing a unified, open information network paradigm to support resilient space information services. This survey first provides a profound discussion about innovative network architectures of DSIN, encompassing distributed regenerative satellite network architecture, distributed satellite computing network architecture, and reconfigurable satellite formation flying, to enable flexible and scalable communication, computing and control, fundamentally enhancing network resilience. The DSIN faces challenges from network heterogeneity, unpredictable channel dynamics, sparse resources, and decentralized collaboration frameworks. To address these issues, a series of enabling technologies is identified, including channel modeling and estimation, cloud-native distributed MIMO cooperation, new waveform design, grant-free massive access, nonorthogonal multicast, distributed phased array antennas, high-speed inter-satellite communication, network routing, and the proper combination of all these diversity techniques. Furthermore, to heighten the overall resource efficiency, the cross-layer optimization techniques are further developed to meet upper-layer deterministic, adaptive and secure information services requirements. In addition, emerging research directions and new opportunities are highlighted on the way to achieving the DSIN vision.

In this paper, we analyze the covert UAV-to-UAV (U2U) communication with the ground warden under a Poisson field of ground interferers and the blockage effect of air-to-ground propagations. With the aid of stochastic geometry, we derive the average covert probability and connection outage probability to quantify the covert communication performance for the scenarios with and without interference. By comparing the two scenarios, the introduction of interference increases the minimum average covert probability. Increasing both the density and transmission power of interferers can improve the average covert probability. However, the improvement of covertness is achieved by increasing the connection outage probability. To capture the competing requirements of covertness and reliability, we analyze the effective covert communication rate defined as the product of the average covert probability, connection success probability, and data transmission rate. The UAV transceiver can also flexibly raise its flight altitude to improve effective covert communication rate. Moreover, our results reveal that covert U2U communication performs better in high blockage environments such as dense urban. In summary, this study provides theoretical guidance for designing covert U2U communication systems.

In cellular networks, the performance of cell-edge users is notably deficient, especially for those receiving almost comparable signal strengths from the serving base station (BS) and interfering BS(s). To improve their performance, a cell-edge UAV deployment scheme is proposed, where the UAVs are deployed to hover over these cell-edge users to serve them. Specifically, the locations of BSs are modeled using a Poisson point process (PPP) and the Voronoi cells are formed. We consider two distinct types of cell-edge users positioned at the Voronoi vertices and boundaries, corresponding to the worst-case and boundary users, respectively. Due to the intractable spatial distribution of the interfering UAVs, we utilize the PPP and binomial point process (BPP) approximations to characterize their interference. Subsequently, we derive the success probabilities for these two types of cell-edge users. The results show the similar effectiveness of the two approximate models for the locations of the UAVs. Furthermore, we obtain the asymptotic success probabilities to analyze the performance in high-reliability regimes and propose an effective approximation based on the asymptotic behavior to simplify the analytical expressions. The results highlight the substantial performance enhancement through the proposed UAV deployment scheme for cell-edge users.

To address the poor performance experienced by cell-corner users located equidistantly to the serving base station (BS) and the nearest interfering BSs, this paper proposes a flexible and general air-ground cooperation scheme based on unmanned aerial vehicles and dynamic BS coordination in the form of BS silencing (BSS) or joint transmission (JT). To show the role of unmanned aerial vehicle (UAV) in the cooperation, we define the UAV-to-BS power ratio (UBPR) as a critical parameter to measure whether introducing the UAV can improve the user’s performance. Using stochastic geometry tools, we derive the success probability of the user located at the corner of the Voronoi diagram, called the worst-case user, in Poisson cellular networks. To facilitate the comparison between different modes of cooperation, we further analyze the cooperation gain including the diversity and power gains through the asymptotic outage probability in the high-reliability regime. Furthermore, to reflect the impact of the cooperation scheme on the overall network performance, we analyze the normalized spectral efficiency, which, unlike those adopted in existing works, accounts for the costs of both resource occupancy and data exchange. Numerical results validate the accuracy of our analytical findings and demonstrate the effectiveness of the proposed scheme for cell-corner users.

In cellular networks, the performance of cell-boundary users with almost equal distance from the serving base station (BS) and the nearest interfering BS(s) is extremely poor. In order to improve the performance of these users, this paper proposes a cell-boundary UAV deployment scheme. To quantify the performance enhancement, the locations of BSs are modeled as a Poisson point process forming Voronoi cells. Two distinct types of cell-boundary users located at the vertices and boundaries of Voronoi cells are served by a UAV-mounted BS hovering over them, and the success probabilities of these two types of users are derived with the stochastic geometry tool. Furthermore, the asymptotic success probabilities are obtained to analyze the performance in high-reliability regime and an effective approximation is proposed based on the asymptotic behavior to simplify the performance evaluation. Finally, the re-sults highlight the substantial performance enhancement achieved through UAV-assisted communication for the cell-boundary users.

To address the poor performance experienced by cell-edge users located equidistantly to the serving base station (BS) and the nearest interfering BS(s), this paper proposes an air-ground coordinated multipoint scheme assisted by unmanned aerial vehicles and the dynamic coordinated BSs selected from the sets of the serving and the equidistant interfering BSs. Using stochastic geometry tools, we derive success probabilities in a Poisson cellular network for the users located at corners of the Voronoi diagram called worst-case users served using non-coherent joint transmission. To reflect the impact of the coordinated transmission on the overall network performance, we also deduce the normalized spectral efficiency. Numerical results validate the accuracy of our analytical findings and show the superior performance of the proposed scheme for the worst-case users.

Combining intelligent reflecting surface (IRS) with an unmanned aerial vehicle to form aerial IRS (AIRS) swarms is an effective way to enable panoramic full-angle reflection, high configuration flexibility and reliable air-ground line-of-sight (LoS) connections, especially in millimeter wave (mmWave) bands. In this paper, we use stochastic geometry to provide a performance analytical framework for AIRS swarm-assisted mmWave cellular networks, where each base station (BS) has an AIRS swarm to assist downlink communications. To capture the swarm property of AIRSs and the dependence between AIRS swarms and BSs, the AIRSs in each swarm are uniformly and randomly distributed in a finite circular area centered on their assisting BS. Incorporating different LoS/non-LoS propagation characteristics, a two-step user association policy is proposed to pursue an efficient communication link between the BS and its users with the assistance of AIRS swarm. We derive the coverage probability and area spectral efficiency (ASE) by considering three types of interference which are directly from interfering BSs, reflected by active AIRSs of other swarms and reflected by the assisting AIRS for the typical user, respectively. The results reveal that AIRS swarms enhance both coverage and ASE performance and have the optimal height and density that maximize the coverage probability in mmWave cellular networks.

To alleviate the time overhead of the handover and beam reselection caused by user mobility, a velocity-based association policy has been adopted in heterogeneous networks. However, it might introduce severe interference from cross-tier interfering base stations which are closer to the users than the serving one. To deal with this problem, we propose two cross-tier interference coordination (CTIC) schemes for mobile users in heterogeneous networks: one jointly considers the transmit power and path loss (TPL-CTIC), and the other further incorporates the directional antenna gain (TPG-CTIC). Considering the beam misalignment and the time overhead caused by user mobility, we derive the overall coverage probability and the average effective Shannon rate (ESR) of mobile users to characterize the user-perceived performance. Taking the cost of the proposed CTIC schemes into account, we further derive the average normalized throughput to evaluate the overall network performance. Numerical results demonstrate that compared with the case without CTIC, the proposed schemes significantly improve the overall coverage probability in the low signal-to-interference-plus-noise ratio regime and the average ESR. To capture the expense of proposed schemes, we define the average normalized throughput. Although TPL-CTIC performs better in terms of the overall coverage probability and the average ESR, TPG-CTIC outperforms in terms of the average normalized throughput.

Intelligent reflecting surface (IRS) has been regarded as an efficient technology to enhance the network performance. Since the IRS can assist transmitters to communicate in a directional reflection way, its deployment usually has a strong correlation with the locations of transmitters. In order to well capture the directional transmission and the spatial correlation while guaranteeing the analytical tractability, we propose an IRS-assisted network model based on a Gauss-Poisson process and a simple yet effective IRS reflected model. Under this setup, we derive the success probabilities for two association policies, namely the dedicated transmitter-receiver pairs with fixed-distance and the nearest associations. To highlight the impact of the IRS, we also derive the success probabilities of three special cases, i.e., without deploying IRSs, ignoring the IRS interference, and blocked direct link between transceivers. The results show that deploying IRS improves the success probability, especially in the cases of IRSs deployed near the transmitters and blocked direct link, and the IRS interference cannot be ignored which becomes the bottleneck factor in the case of transmitters equipped with massive antenna arrays. Owing to the proposed model, the impact of the correlation between IRSs and transmitters is well studied, which provides useful guidance for integrating IRSs into wireless networks.

To relieve the high backhaul load and long transmission time caused by the huge mobile data traffic, caching devices are deployed at the edge of mobile networks. The key to efficient caching is to predict the content popularity accurately while touching the users’ privacy as little as possible. Recently, many studies have applied federated learning in content caching to improve data security. However, they still give away some privacy of participants, especially ignoring the private data leakage in the trained model. To solve this problem and further improve the cache hit ratio, we propose an efficient content popularity prediction of privacy-preserving (CPPPP) scheme based on federated learning and Wasserstein generative adversarial network (WGAN), which achieves a high cache hit ratio. Benefited by the Federated-WGAN and the generated fake samples, the private data, the content preferences of individual users, and so on are well protected. In particular, gradient clipping and model parameter limitation are introduced in the model training, and the security of the modified model is greatly improved compared with the original model. Results show that the proposed scheme has a higher cache hit ratio than the existing federated learning-based methods while limiting the privacy leakage caused by the trained model to a quite low level.

Intelligent reflecting surface (IRS) is a promising technology to provide line-of-sight (LOS) links for blocked paths, especially in millimeter wave (mmWave) cellular networks. However, in practice, it is difficult for IRSs to arbitrarily adjust the reflection angle to align served users. A promising solution is to deploy distributed IRSs to increase the probability that the users lie in the reflection directions. This paper develops a stochastic geometry-based approach for studying the coverage enhancement in mmWave cellular networks via distributed IRSs. Specifically, the locations of IRSs are modeled through a binomial point process centered at a base station, and the reflection beam of each IRS is pointed to a certain direction. Considering the difference between LOS and non-LOS mmWave transmissions, we propose a received signal strength indicator based association strategy to guarantee that the users receive the strongest average power. After characterizing the association probabilities and distance distributions, we derive the coverage probability for an arbitrary user and perform simplifications for enhancing the computation efficiency. The results are validated by simulations and reveal that distributed deployment of IRSs can achieve a better coverage probability than that of the centralized deployment, which validates the feasibility of enhancing system performance through distributed IRSs.

Air platforms, such as unmanned aerial vehicles, airships, and balloons are expected to complement traditional ground networks to provide flexible coverage solutions. However, most existing models for air-ground integrated networks (AGINs) neglect the spatial dependence caused by the complementary deployment of the aerial and ground nodes. Accordingly, in this paper, we propose two AGIN models with horizontal dependence that differ in the vertical dimension, namely uniformly independent altitudes and location-dependent altitudes. The air platforms serve as aerial base stations, distributed as a marked Poisson hole process, and provide flexible beam coverage through varying altitudes. Under this setup, we propose a region-based user association scheme and derive the association probabilities as well as the serving distance distributions of an arbitrarily located user. Considering Nakagami fading and air-to-ground propagation properties, we characterize the signal-to-interference ratio and area spectral efficiency for each model. Using the proposed analytical framework, we demonstrate the importance of deploying the air platforms more sensibly to provide targeted services and flexible beam coverage in reducing the load of base stations and improving the user coverage and network capacity performance.

The low Earth orbit (LEO) satellite constellation in the terahertz (THz) band is one of the promising technologies to provide global coverage and high-rate transmission to the airplane, whose key performance evaluation is required before realistic deployment. In this paper, we consider a downlink THz LEO satellite-airplane network with directional antennas, where the satellites follow a binomial point process on a spherical surface. Incorporating the distinctive THz propagation properties and directional beams in the two scenarios with/without molecular absorption noise, we propose an analytical framework to evaluate the coverage probability and average achievable rate of an arbitrary airplane. The analytical results are expressed in terms of the Laplace transforms of the interference-plus-molecular absorption noise and interference. Specifically, considering a frequency reuse strategy, we first provide the probability distributions of the distances from an arbitrary satellite, the serving satellite and any non-serving satellite to the target airplane, and calculate the probabilities of whether an interfering satellite is blocked by the Earth. Numerical results verify the accuracy of the analytical expressions and show that fewer orthogonal channels and lower LEO satellite altitude lead to better coverage and rate performance. As a key parameter in network design, the number of satellites has two competing effects on coverage and rate, and an optimum satellite number exists. Overall, this study provides theoretical guidance for deploying and planning THz satellite constellations.

To support the emerging applications with the coming of the Beyond-5G (B5G) era, e.g., Ultra Reliable Low Latency Communications (URLLC) services, our telecommunications networks have witnessed a serious spectrum shortage problem. According to our spectrum measurement campaign, we note that many bands are actually extremely under-utilized, even for the operators’ ones, e.g., LTE spectrums. Thus, it is expected to share the idle spectrums for the B5G services. Nevertheless, how to determine an effective sharing strategy is non-trivial. It is necessary to jointly consider the spectrum requirement of primary networks and the traffic demand of secondary networks when making the sharing decision, which, however, are both uncertain and hardly known precisely in advance. In this paper, taking the uncertain network environment into account, we propose a Proactive Dynamic Spectrum Sharing (PDSS) scheme to employ the under-utilized LTE spectrums for URLLC service provisioning. We take the long-term overall utility as the objective to achieve a trade-off between two networks to avoid the performance degradation of primary networks, while fulfilling as many URLLC services as possible with quality of service (QoS) guarantee. To deal with the environment uncertainty, we develop a model-free deep reinforcement learning (DRL) based solution, which can proactively capture the feature of the uncertain environment and achieve the best sharing decision autonomously. Based on the real spectrum data, simulation results have shown the effectiveness of the proposed DRL based PDSS scheme.

In order to evaluate the impacts of swarm distribution characteristics of unmanned aerial vehicles (UAVs) and the complexity of millimeter wave (mmWave) propagations on the coverage performance of UAV networks, this paper develops a stochastic geometry-based approach for the modeling and analysis of single- and multi-swarm UAV networks with mmWave communications. We first utilize binomial point processes (BPPs) to model the locations of UAVs in a finite area as a single-swarm UAV network and allow for arbitrary user locations. Then, we define multi-BPPs and extend our model to multi-swarm UAV networks. We consider an open-access strategy, where users access the closest UAV in all swarms, and derive the distance distributions of serving and interfering UAVs. Moreover, a three-dimensional (3D) blockage model and a 3D sectorized antenna model are introduced to completely depict the characteristics of air-to-ground channel in mmWave band. Based on the distance distributions and the Laplace transform of interference, coverage probabilities in considered networks are derived. Our results reveal that, there exists optimal height and density of UAV swarms that maximize the coverage probability. When densely deployed, the interference from inter-swarm cannot be negligible in the multi-swarm UAV network.

In millimeter-wave (mm-wave) cellular networks, directional antenna arrays are typically adopted to mitigate the severe propagation loss. However, the interference caused by such highly directional beams may, in turn, result in a significant number of transmission failures, especially for dense networks. To tackle this problem, we propose two inter-cell interference coordination (ICIC) schemes in mm-wave bands: one is merely based on the path loss incorporating the blockage effect (PL-ICIC); the other considers both path loss and directivity gain (PG-ICIC). To fully investigate both schemes, we first derive an exact expression for the success probability (reliability) of the typical (served) user. We further provide an asymptotic analysis for the success probability and propose an effective approximation based on the asymptotic signal-to-interference ratio (SIR) gain relative to no ICIC. Secondly, to incorporate the cost of ICIC schemes, we derive the approximate normalized throughput taking into account that some users cannot be served due to limited resources. Numerical results show that the two proposed schemes provide significant reliability improvements in the low-SIR regime, and the higher the number of antennas, the wider the SIR range for which there is an improvement. In addition, compared with PL-ICIC, PG-ICIC balances the available resources among all users well.

The spatial correlation of the energy harvested from RF transmitters, named energy correlation, plays a key role in the performance evaluation of wirelessly powered networks. This paper introduces an analytical framework with foundations in stochastic geometry to characterize the energy correlation based on the energy correlation coefficient (ECC). For a model where RF power sources are distributed according to a Poisson point process and employ beamforming techniques to transfer energy directionally, we focus on two cases: i) each power source points the beam in a random direction; ii) each power source points the beam to an RF-powered node located in its Voronoi cell. We first analyze the ECC of the two cases, and then give the asymptotic results with respect to the antenna array size. It turns out that in both cases the harvested energy at two locations exhibit positive correlation, and when the antenna array size tends to infinity, the correlation in the first case vanishes while the one in the second case is still positive. Numerical results give useful insights into the effect of several system parameters on the energy correlation from directed wireless energy transfer.

In UAV-assisted cellular networks (UACNs), the UAV tier should be flexibly adjusted to the terrestrial tier, which causes location dependence between UAVs and ground base stations (GBSs). To capture it, this paper proposes a 3D UACN model with inter-tier dependence and analyzes the performance of such UAV-assisted network via stochastic geometry. Specifically, UAVs with random altitudes are deployed outside the exclusion regions of GBSs to avoid the strong inter-tier interference, and accordingly, the locations of GBSs and UAVs follow a PPP and a marked Poisson hole process (MPHP), respectively. Under this setup, we propose a division region-based user association scheme, and provide analytical results for the association probability, link distance distribution, and success probability which are verified through simulations. Numerical results unveil that: 1) the exclusion region should be carefully designed to achieve the optimal access probability and 2) significant gains (especially for cell edge users) can be obtained if UAVs are introduced and deployed agilely.

In UAV-enabled mmWave networks, the locations of UAVs are usually modeled by a Poisson point process or a Poisson cluster process in an infinite area. However, some typical scenarios merely deploy a fixed number of UAVs in a finite area such as hotspot areas and disaster response. To capture these characteristics, we propose a 3D UAV-enabled mmWave network model in a finite area where UAVs follow a Binomial point process (BPP). Under this setup, we derive the expression of the coverage probability for the target user at an arbitrary location rather than the region center, and further provide simplified analysis in three special cases including interference-limited case, noise-limited case and the case with the target user located at the region center. Numerical results show that the location of the target user has a significant impact on coverage probability, and a maximum coverage probability can be obtained by adjusting the height and number of UAVs.

This paper provides a deep analysis for millimeter-wave device-to-device (mm-wave D2D) underlaid cellular networks to investigate how the performance of individual users or link percentiles under constraints are affected by the interaction between D2D and cellular communication modes integrated with the salient mm-wave features. Under a general Nakagami fading model, we derive the upper bounds for the$b$-moments of the conditional signal-to-interference-noise ratio (SINR) distributions for the two modes given the network realization, and further calculate the upper bounds of SINR meta distributions (MDs). Moreover, we extend the MD-based analysis to evaluate the fine-grained performance for the transmission effectiveness, through deriving the bounding results for the user-perceived rate MD and spatial rate capacity (SRC), the latter of which is defined as the effective density of users satisfying a given transmission rate requirement with a certain probability. Numerical results validate the tightness of the proposed bounds and reveal the different effects of the network configuration parameter associated with mm-wave on the link and network performances from the view of individual users.

Energy correlation critically affects the performance of a wirelessly powered network due to its key effect on the spatial distribution of concurrent RF-powered transmitters. This paper introduces a powerful analytical framework with foundations in stochastic geometry to characterize the energy correlation in a general wirelessly powered network. Unlike the commonly used pair correlation function (pcf)-based method, it is based on theenergy correlation coefficient(ECC) and yields the energy correlation distance that gives a sufficiently small ECC. Specifically, we focus on the spatial correlation of the energy harvested from a Poisson field of RF power sources with directional beams under two cases: i) each power source points the beam in a random direction; ii) each power source points the beam to an RF-powered node located in its Voronoi cell. The results demonstrate that the energized RF-powered nodes in both cases exhibit positive correlation that is weaker than in the omni-directional case due to the introduction of energy beamforming. As an application, we provide an ECC-based method using the energy correlation distance to approximate the success probability and area spectral efficiency in the communication phase. It turns out that the ECC-based approximation matches the exact result well, and, more importantly, it can deal with the energy correlation in more general and complicated scenarios (where the pcf analysis is infeasible) due to its superior tractability.

With the growing popularity of traditional Chinese medicine (TCM) in the world and the increasing awareness of intellectual property protection, the number of TCM patent application is growing year by year. TCM patents contain rich medical, legal, and economic information. Effective text mining of TCM patents is of great theoretical and practical significance (e.g., the R&D of new medicines, patent infringement litigation, and patent acquisition). Named entity recognition (NER) is a fundamental task in natural language processing and a crucial step before indepth analysis of TCM patent. In this paper, a method combining Bidirectional Long Short‐Term Memory neural network with Conditional Random Field (BiLSTM‐CRF) is proposed to automatically recognize entities of interest (i.e., herb names, disease names, symptoms, and therapeutic effects) from the abstract texts of TCM patents. By virtue of the capabilities of deep learning methods, the semantic information in the context can be learned without feature engineering. Experiments show that the BiLSTM‐CRF‐based method provides superior performance in comparison with various baseline methods.

In the analysis of large-scale wirelessly powered networks, the energy correlation is often ignored for analytical tractability. Accounting for the energy correlation, this paper introduces and promotes the Poisson disk process (PDP) as a model for the active RF-powered nodes that succeed in harvesting energy. To show that the model leads to tractable results in several cases of interest, we derive the density and second moment density of the PDP and find the key property that the PDP can be fully characterized by its first- and second-order statistics. Tight bounds for its probability generating functional (PGFL) are also provided. To show that the model is relevant for wirelessly powered networks that exhibit positive energy correlation, we fit the PDP to a given energized point process incorporating practical energy harvesting factors and derive the information transmission success probability. It turns out that the resulting PDP can closely model the distribution of actual energized RFpowered nodes in terms of the success probability and other statistics while preserving analytical tractability.

The information freshness, quantified by the emerging idea of Age of Information (AoI), has recently received widespread attentions from both academia and industry. However, most prior works on AoI considered the single source-destination pair model and provided the performance analysis merely through queueing-theoretic models, which do not lend themselves to the analysis of large-scale wireless networks. This paper focuses on the AoI analysis in a large-scale setting using random spatial models in stochastic geometry. Specifically, we first adopt rateless coding for packet delivery to improve the transmission reliability while reducing the transmission delay. Then, to quantify the enhancement of the information freshness by rateless coding, we derive the average peak age of information (PAoI), which characterizes the maximum value of AoI immediately before an update packet is received, accounting for the spatial variation of network nodes and temporal dynamics of service packets. Numerical results show the significant benefits of rateless codes relative to the commonly used fixed-rate codes in terms of the PAoI.

Despite of the promising benefits brought by device-to-device (D2D) technique, the attainable performance gains in an underlaying network may still be eroded by the severe mutual interference between cellular and D2D communications. To address this critical issue, we first propose an exclusion-based D2D activation (EDA) scheme with hybrid spectrum allocation to suppress the mutual interference and improve the user performance, where only the D2D users outside the exclusion regions are active and share the frequency band with the cellular users within the exclusion regions. Secondly, we establish a stochastic geometry-based analytical framework and analyze the success probabilities of both cellular and D2D users, where the distribution of the activated D2D pairs follows a bipolar Poisson hole process. The results demonstrate the significant performance improvement and the effectiveness on the interference suppression brought by the proposed EDA scheme and the hybrid spectrum allocation.

Pattern regeneration is one of the applications of reverse engineering technology in the textile field, which realises the process of textile‐pattern regeneration‐textile, and fundamentally provides an intelligent design means of textile. At present, the method of pattern regeneration in the jacquard fabric is to use the image segmentation algorithm to segment the image digitalised by unidirectional imaging, and then the segmented pattern could be identified to regeneration for the design of new fabrics. However, due to the concave and convex pattern textures on the surface of jacquard fabric, the traditional unidirectional imaging method cannot be used for the full characterisation of its structural information, resulting in unsatisfactory pattern segmentation effect. To solve this problem, a novel segmentation algorithm for jacquard patterns based on multi‐view image fusion was proposed in this study. Based on multi‐view image acquisition and fusion, the pattern image of jacquard fabric could be cluster‐segmented by extracting the complete texture information of the fused image and the actual colour information of the calibrated image. Compared with the traditional unidirectional imaging method, the experimental results show that the enhanced texture information of the fused image is more workable for the pattern segmentation, it validates the effectiveness of the proposed method.

In the analysis of large-scale wirelessly powered networks, the energy correlation is often ignored. While this leads to remarkably simple results for key performance metrics, it is typically not realistic and accurate. Considering the accuracy, tractability, and practicability tradeoffs, this paper introduces and promotes the Poisson disk process (PDP) as a model for the energized nodes that succeed in harvesting energy. To show that the model leads to analytically tractable results in several cases of interest, we derive its first and second moment densities, which fully characterize the PDP. Besides, we also provide tight bounds for its probability generating functional as well as its contact and nearest-neighbor distance distributions. Then, to show that the model is relevant for wirelessly powered networks-which all have positive energy correlation-we provide two approaches to fit the PDP to a given energized point process incorporating practical energy harvesting factors. Further, we derive the success probability in the information transmission phase, where the distribution of the active transmitters is modeled by a PDP. It turns out that the resulting PDP can closely model the distribution of actual energized nodes in terms of the success probability and other statistics while preserving analytical tractability.

This paper studies the spatial correlation of the energy harvested from a Poisson field of millimeter-wave (mm-wave) RF power sources which employ beamforming techniques to transfer energy directionally. In particular, each node harvests and stores energy from its nearest RF transmitter and uses it to power the information transmission. Under this setup, we show how the actual point process of nodes that successfully harvest energy looks visually and provide an accurate characterization of its density and pair correlation function theoretically. Surprisingly, it turns out that the process of the energized nodes exhibits repulsive correlations for small distances which wears off as the distance increases. Therefore, we further approximate the energized point process with a fitted β-Ginibre point process, which is shown to provide a good approximation of the success probability in the information transmission. A useful insight is that there are energy correlations caused by the directional energy transfer, which should be reflected accurately in modeling the active mm-wave RF-powered nodes.

In millimeter-wave (mm-wave) cellular networks, high-gain beamforming, realized with directional antenna arrays, is typically adopted to mitigate the severe propagation loss. However, the interference caused by such highly directional beams may, in turn, result in a significant number of transmission failures, especially for dense networks. To tackle this problem, we propose two inter-cell interference coordination (ICIC) schemes in mm-wave bands: one is merely based on the path loss incorporating the blockage effect (PL-ICIC); the other considers both path loss and directivity gain (PG-ICIC). To fully investigate the performance of both schemes, we first derive the exact expression for the success probability (reliability) of the typical user that is served. Secondly, to reflect the cost of interference coordination, we further derive the overall success probability taking into account that some users cannot be served due to limited resources. Numerical results show that both the proposed two schemes provide significant reliability improvements in the low signal-to-interference ratio (SIR) regime, in particular, the higher the number of antennas, the wider the range of SIR threshold for which there is an improvement. In addition, compared with PL-ICIC, PG-ICIC balances the available resources among all users well.

This paper investigates the spatial correlation of the energy harvested from a Poisson field of RF power sources. Specifically, we focus on two energy harvesting models-one dependent on distance alone and the other with more practical factors taken into account-with the aim of showing how the actual point process of nodes that successfully harvest energy looks visually and characterize the pair correlation functions for such point process under the two models theoretically. It turns out that for both models the resulting process of the energized nodes exhibits positive correlations. Therefore, we further approximate the point process formed by active RF-powered nodes with a fitted Poisson cluster process, which is shown to provide a good approximation of the success probability in the information transmission. An important conclusion is that though the Poisson point process has been widely used to model the spatial configuration of energized nodes, it is inadequate for modeling the locations of the active RF-powered nodes due to the positive correlation.

Unlike earlier works on rateless codes that mostly considered finite networks or ignored the traffic dynamics, this paper focuses on the end-to-end delay performance of rateless codes in large-scale wireless ad hoc networks with traffic dynamics. Specifically, the end-to-end delay is divided into two parts, namely the packet waiting time before transmission and the transmission time, whose statistical distributions are given by exact results as well as simple yet accurate approximations. This way, the statistics of the end-to-end delay are fully investigated. The proposed analytical framework and the end-to-end performance metric help obtain more insights on the role of scheduling, queueing, and coding scheme in practical networks. The approximations are verified to be effective and reliable through simulations. Overall, the results show the significant benefits of rateless codes relative to the fixed-rate codes in terms of the end-to-end delay performance.

As a key enabling technology for truly sustainable operation of devices, wireless energy and information transfer (WEIT) has attracted significant attention in wireless communication networks. Previous works on WEIT network analysis mostly concentrated on the energy outage probability or the expectation of the transferred energy at the typical wirelessly powered device using stochastic geometry. These calculations are relatively straightforward, but they only provide limited information on the energy extracted by the individual devices. This paper considers a WEIT-enabled device-to-device (D2D) network with the ambient RF transmitters distributed according to a Poisson point process and focuses on the meta distribution of the transferred energy, which is the distribution of the conditional energy outage probability given the locations of the RF transmitters, to show what fraction of devices in the network satisfy the target energy outage constraint if the required transmission energy is given. Furthermore, we derive the meta distribution of the transmission rate under an energy outage constraint and introduce a new notion of transmission efficiency, termed wirelessly powered spatial transmission efficiency, which is defined as the density of concurrently active links that rely on the wireless energy transfer technique and satisfy a certain reliability constraint that has a rate greater than a predefined threshold. Our analysis provides insightful guidelines for the most efficient way to operate a WEIT-enabled self-sustainable D2D communication network.

This paper focuses on the meta distributions of the signal-to-interference-plus-noise ratio (SINR) and user-perceived rate in heterogeneous cellular networks (HCNs) with multiple tiers of base stations. On the one hand, it is desirable to offload users to small cells to alleviate the congestion in macrocells; on the other hand, such offloading would in turn cause an SINR degradation of the offloaded users, which needs to be mitigated through interference avoidance based on resource partitioning. Thus, in consideration of both aspects, we provide a general framework for modeling and analyzing joint spectrum allocation and offloading in an HCN using the K-tier homogeneous-independent Poisson model. With it, we derive the per-tier and overall moments of the conditional SINR and rate distribution given the point process, based on which the exact meta distributions are given. We show that the conventional SINR or rate performance evaluated at the typical user (averaging over all tiers and links in the HCN), by itself, is insufficient, and a much sharper version provided by the meta distribution is required in conjunction with the expected value to give a thorough assessment of the benefits of joint resource partitioning and offloading in HCNs.

Rateless coding is a promising forward error correction technique to meet both delay and reliability requirements of emerging wireless applications. However, existing works on rateless codes mostly considered finite networks or ignored the traffic dynamics. In this paper, we present a comprehensive investigation of the end-to-end performance for rateless codes in Poisson bipolar and cellular networks. Specifically, we propose the notion of theend-to-end success probability, which is the success probability given an end-to-end delay requirement, to jointly evaluate the delay performance and transmission reliability of rateless codes. To fully characterize the end-to-end delay, we divide it into two parts, namely the packet waiting time and the transmission time, and provide tractable yet accurate approximations to their statistical distributions. Compared with the previous works, the proposed general framework and the end-to-end performance metric help obtain insights on the role of scheduling, queueing, and coding scheme in practical radio access networks. The approximations are verified to be effective and reliable through simulations. Overall, the results show the significant benefits of rateless codes relative to the fixed-rate codes in terms of the transmission reliability with an end-to-end delay requirement.

The actual antenna pattern model makes it difficult to investigate the performance of directional antenna arrays in the large-scale networks. In this paper, we propose a novel antenna pattern, named multi-level flat-top (MLFT) antenna pattern, to approximate the actual antenna pattern, and apply it to millimeter wave (mm-wave) cellular networks. To study the benefits of directional antenna arrays in depth, we derive the exact expression for the coverage probability of the typical user and its upper bound as well as their corresponding asymptotic expressions. The results show that the proposed antenna pattern provides a better tradeoff between the accuracy and the tractability in terms of both antenna pattern and theoretical analysis than previous models. In addition, the coverage probabilities for different antenna sizes can be asymptotically characterized by a horizontal shift (in dB) with each other for identical Nakagami fading parameter.

This paper focuses on the meta distribution of the signal-to-interference-plus-noise ratio (SINR) and rate in heterogeneous cellular networks (HCNs) with multiple tiers of base stations, where disjoint frequency bands are allocated among tiers and users are associated with each tier with a biased average received power. The meta distribution provides a much sharper version of the “SINR/rate performance” than that merely considered at the typical user through spatial averaging, which gives deep insight into the impacts of heterogeneity, resource coordination, user association, etc., on the performance of individual users. Using tools of stochastic geometry, we develop a general and tractable framework for a fine-grained analysis for HCNs with joint resource partitioning and offloading. With it, we derive exact analytical expressions as well as their asymptotic behaviors for the overall and per-tier moments of the conditional SINR and rate distribution given the point processes, based on which the exact meta distributions are given. We show that although the offloaded users suffer from SINR degradation, the rate performance of all individual users can be improved via load balancing in conjunction with appropriate resource partitioning.

This paper focuses on the success probability (or, equivalently, the signal-to-interference-plus-noise ratio (SINR) distribution) at the typical receiver in millimeter wave (mm-wave) device-to-device (D2D) networks. Unlike earlier works, we consider a more general and realistic case where devices in the network are equipped with heterogeneous antenna arrays so that the concurrent transmission beams are varying in width. Specifically, we first establish a general and tractable framework for the target network with Nakagami fading and directional beamforming. Next, we investigate the interactions among beams with different widths and their sensitivities to the adopted model for the antenna pattern. In addition, to show the impact of heterogeneous antenna arrays on the link performance, we derive the success probability of the typical receiver as well as its bounds to get deep insights on the performance of the network.

Device caching has recently been proposed as an efficient way to offload traffic from congested cellular networks. However, previous works usually ignore the fact that, in practice, the user device may not be willing to help others due to the limited battery capacity. In this paper, we introduce cooperation among the device-to-device (D2D) transmitters and propose two novel hybrid caching strategies-single-point caching combined with two-point cooperative caching with joint transmission (SPC-CCJT) or multi-stream transmission (SPC-CCMT)-aiming at saving the energy cost of content deliverers. Using tools from stochastic geometry, we propose an analytical framework of the hybrid caching strategies by modeling the locations of the D2D transmitters as a Gauss-Poisson process (GPP) to accurately capture the clustering and cooperative behaviors. First, we consider a probabilistic caching placement and optimize the caching distribution to maximize the cache hit probability. Second, to compare the performance between different content delivery strategies, we derive the success probability and per-user capacity for SPC, CCJT, and CCMT, respectively. These results are then applied to evaluate the offloading gain and the distribution of the content retrieval delay for SPC-CCJT and SPC-CCMT in the GPP-based D2D networks. It turns out that significant offloading gain and delay improvement can be achieved by hybrid caching with cooperation while the energy cost of each cooperator is kept low.

Millimeter-wave (mm-wave) device-to-device (D2D) communication is considered one of the most promising enabling technologies to meet the demanding requirements of future networks. Previous works on mm-wave D2D network analysis mostly considered the case that all devices were equipped with exactly the same number of antennas, whereas real networks are more complicated due to the coexistence of diverse devices. In this paper, we present a comprehensive investigation on the interference characteristics and link performance in mm-wave D2D networks where the concurrent transmission beams are varying in width. First, we establish a general and tractable framework for the target network with Nakagami fading and directional beamforming. To fully characterize the interference, we derive the mean and variance of the interference and then provide an approximation of the interference distribution by a mixture of the inverse gamma and the log-normal distributions. More importantly, the coexistence of varied beamwidths renders their interactions and thus the interference quite complicated and sensitive to the antenna pattern, highlighting the significance of adopting an accurate model for the antenna pattern. Second, to show the impact of heterogeneous antenna arrays on the link performance, we derive the signal-to-interference-plus-noise ratio and rate distributions of the typical receiver as well as their asymptotics, bounds, and approximations to get deep insights on the performance of the network.

In this paper, the meta distribution of the signal-to- interference-plus-noise ratio (SINR) in millimeter wave (mm-wave) device-to-device (D2D) networks is studied, which is the distribution of the conditional SINR distribution given a realization of the point process modeling the network. This analysis provides much more fine-grained information on the performance of individual links than just the mean that is usually evaluated. Modeling the D2D transmitters as a Poisson point process (PPP) and considering the unique mm-wave features, moments of the conditional SINR distribution given the point process are derived in order to calculate analytical expression for the meta distribution. It turns out that when the size of the antenna array tends to infinity, the noise is totally suppressed and the node density becomes the dominating factor affecting the interference in the network. Closed-form approximations of the meta distribution with the beta distribution are also provided. Numerical results give interesting insights into the effects of mm-wave features on the performance of D2D communication.

Enabling device-to-device (D2D) communications in millimeter-wave (mm-wave) networks is of critical importance for the next-generation mobile networks to support very high data rates (multi-gigabits-per-second) for mobile devices. In this paper, we provide a fine-grained performance analysis of the mm-wave D2D communication networks. Specifically, we first establish a general and tractable framework to investigate the performance of mm-wave D2D networks using the Poisson bipolar model integrated with several features of the mm-wave band. To show what fraction of users in the network achieve target reliability if the required signal-to-interference-plus-noise ratio (SINR) (or QoS requirement) is given, we derive the meta distributions of the SINR and the data rate. Interestingly, in mm-wave D2D networks, the standard beta approximation for the meta distribution does not work very well when highly directional antenna arrays are used or the node density is small. To resolve this issue, we provide a modified approximation by using higher moments of the conditional SINR distribution, which is shown to be closer to the exact result. On this basis, we also derive the mean local delay and spatial outage capacity to provide a comprehensive investigation on the impact of mm-wave features on the performance of D2D communication.

The explosive growth of cellular network users and traffic stimulates the current network architecture to be more spectral-, energy-, and operation efficient and flexible. In this paper, we propose a transformium network architecture comprising transformium core, body and cloud, where the core dynamically schedules the body and cloud orchestrated with wireless network environment. To enable the transforming ability, some new emerging technologies, including software defined networking, network virtualization are employed in the proposed architecture. As a consequence, the transforimium network is a promising network architecture to improve the network capacity, quality of service and solve the network ossification problem.

The current cellular networks have evolved to be more randomly, irregularly, and heterogeneously deployed to meet the exponential growth of mobile data traffic and the demand for seamless coverage, making the signal-to-interference ratio (SIR) distribution more challenging to analyze. Therefore, in this paper, we propose two simple approximative approaches to the SIR distribution of general heterogeneous cellular networks (HCNs) based on the ASAPPP method, which stands for “approximate SIR analysis based on the Poisson point process” and the MISR (mean interference-to-signal ratio)-based gain for each individual tier of the HCNs. Specifically, we first establish a per-tier ASAPPP approximation to general HCNs and then present an effective gain ASAPPP method as a further simplification when the path loss exponents are the same for all the tiers, that is, we give an explicit expression for the effective gain Geffof general HCNs such that the SIR distribution is obtained by scaling the SIR threshold θ to θ/Geff. The asymptotic behavior for the tail of the SIR distribution is also given. Furthermore, to highlight the simplicity and effectiveness of the approximative approaches, we derive the exact distribution of the SIR in the two-tier HCNs modeled by β-Ginibre and Poisson point processes and compare it with the approximate results. The results demonstrate that the proposed approaches give a simple yet excellent approximation for the SIR distribution.

The crushing demands for mobile data traffic drive the current cellular networks to become more heterogeneous, making the signal-to-interference ratio (SIR) distribution more difficult to analyze. In this paper we propose a simple approximative approach to the SIR distribution of heterogeneous cellular networks (HCNs) based on the ASAPPP method which stands for ``approximate SIR analysis based on the Poisson point process'' and the MISR (mean interference-to-signal ratio)-based gain for each individual tier of the HCN. The results demonstrate that this approach gives a tight approximation and asymptotically a lower bound for the coverage probability.

The frequency reuse technique is a fundamental and classical issue in the interference management of cellular networks, and has never experienced any fundamental shifts from the first generation to the current LTE. With the development of 5G, the classic frequency reuse (FR) is no longer suitable for heterogeneous cellular networks (HCNs). In this paper, we propose a unified frequency reuse (UFR) model for a heterogeneous networking architecture in future wireless cellular communications, where the HCN is divided into different tiers with different frequency band assigned. Then, we take an HCN with different overlapped tiers of densely deployed base stations as an example and analyze the spectral efficiency, transmission ability and energy efficiency of the network when the proposed UFR scheme is applied. The numerical results demonstrate that the proposed model is not only beneficial to the frequency allocation but also achieves higher performance for future 5G wireless communications.

In this paper, we propose a novel Over Frequency Ruse (OFR) scheme in a heterogeneous network structure for 5G to increase the cell spectral efficiency and transmission ability. Specifically, we first derive an explicit expression of the interference characteristic in the cellular networks based on the cell interference depth (CID) model. And then, we analyze the performance of the proposed OFR including the cell spectral efficiency, the area throughput and the energy efficiency, and compare them with those of the traditional FFR cellular networks. The results demonstrate that the proposed OFR scheme improves the performance effectively, no matter the spectral efficiency or the energy efficiency, and is compatible with the traditional FR and FFR in 3G and 4G.

Due to its tractability, a multitier model of mutually independent Poisson point processes (PPPs) for heterogeneous cellular networks (HCNs) has recently been attracting much attention. However, in reality, the locations of the BSs, within each tier and across tiers, are not fully independent. Accordingly, in this paper, we propose two HCN models with inter-tier dependence (Case 1) and intra-tier dependence (Case 2), respectively. In Case 1, the macro-base station (MBS) and the pico-base station (PBS) deployments follow a Poisson point process (PPP) and a Poisson hole process (PHP), respectively. Under this setup and conditioning on a fixed serving distance (distance between a user and its nearest serving BS), we derive bounds on the outage probabilities of both macro and pico users. We also use a fitted Poisson cluster process to approximate the PHP, which is shown to provide a good approximation of the interference and outage statistics. In Case 2, the MBSs and the PBSs follow a PPP and an independent Matern cluster process, respectively. Explicit expressions of the interference and the outage probability are derived first for fixed serving distance and second with random distance, and we derive the outage performance, the per-user capacity, and the area spectral efficiency (ASE) for both cases. It turns out that the proposed Case 2 model is a more appropriate and accurate model for a HCN with hotspot regions than the multitier independent PPP model since the latter underestimates some key performance metrics, such as the per-user capacity and the ASE, by a factor of 1.5 to 2. Overall, the two models proposed provide good tradeoffs between the accuracy, tractability, and practicability.

The spatial structure of transmitters in wireless networks plays a key role in evaluating mutual interference and, hence, performance. Although the Poisson point process (PPP) has been widely used to model the spatial configuration of wireless networks, it is not suitable for networks with repulsion. The Ginibre point process (GPP) is one of the main examples of determinantal point processes that can be used to model random phenomena where repulsion is observed. Considering the accuracy, tractability, and practicability tradeoffs, we introduce and promote the β-GPP, which is an intermediate class between the PPP and the GPP, as a model for wireless networks when the nodes exhibit repulsion. To show that the model leads to analytically tractable results in several cases of interest, we derive the mean and variance of the interference using two different approaches: the Palm measure approach and the reduced second-moment approach, and then provide approximations of the interference distribution by three known probability density functions. In addition, to show that the model is relevant for cellular systems, we derive the coverage probability of a typical user and find that the fitted β-GPP can closely model the deployment of actual base stations in terms of coverage probability and other statistics.

In heterogeneous cellular networks (HCNs), the macrocell network is usually assumed to be overlaid by multiple independent tiers of small cells. However, in reality, the locations of the base stations (BSs) belonging to different tiers are not fully independent. Accordingly, in this paper, we propose a two-tier HCN model with inter-tier dependence, where the macro-BS (MBS) and the pico-BS (PBS) deployments follow a Poisson point process (PPP) and a Poisson hole process (PHP), respectively. Under this setup, we derive bounds on the outage probabilities of both macro users and pico users, and then use a fitted Poisson cluster process to approximate the PHP, which is shown to provide a good approximation of the interference and outage. The results show that the model with inter-tier dependence appears closer to the real deployment than the two extremes with full regularity (the triangular lattice) and complete randomness (the PPP). An important conclusion is that significant gains can be obtained if PBSs are deployed smartly (away from MBSs).

Though cooperative relaying is believed to be a promising technology to improve the energy efficiency of cellular networks, the relays' static power consumption might worsen the energy efficiency therefore can not be neglected. In this paper, we focus on whether and how the energy efficiency of cellular networks can be improved via relays. Based on the spatial Poisson point process, an analytical model is proposed to evaluate the energy efficiency of relay-assisted cellular networks. With the aid of the technical tools of stochastic geometry, we derive the distributions of signal-to-interference-plus-noise ratios (SINRs) and mean achievable rates of both non-cooperative users and cooperative users. The energy efficiency measured by “bps/Hz/W” is expressed subsequently. These established expressions are amenable to numerical evaluation and corroborated by simulation results.

Energy efficiency in cellular networks has recently received a significant attention and incorporating cooperative relays in cellular networks is believed to be a promising technology to greatly lower the energy consumption of cellular networks while sustaining high data rates. In this paper, we focus on improving energy efficiency of a single cellular system assisted by relays. We propose a novel relay deployment strategy and a corresponding relay selection procedure. Using coded cooperation as the transmission scheme, we derive the area power consumption under a target area spectral efficiency. Besides, the impact of different parameters such as cell radius, target area spectral efficiency, number and position of relays on the area power consumption is also studied. Compared with direct transmission and decode-and- forward (DF) relaying, our work significantly improves the energy efficiency of cellular systems and sheds key insights into the tradeoff between the energy consumption and the spectral efficiency via dynamically adjusting the resource allocation between BS and relay in coded cooperation.

Though opportunistic relaying coded cooperation is known as an efficient cooperation scheme for cooperative multi-relay networks, the existing works have the disadvantage of low resource utilization or high system complexity. In this paper, we focus on how to achieve a balance between resource utilization and system complexity by proposing an novel opportunistic relaying coded cooperation with selective source-to-destination parity transmission over Nakagami-m fading channels without additional cost. We derive closed-form expressions of the outage probability and explicit upper bounds on bit error probability using the statistical characteristic of the signal-to-noise ratios (SNRs) and confirm that the proposed scheme outperforms both opportunistic amplify-and-forward (AF) and opportunistic decode-and-forward (DF). Simulation results on the unbalanced generalized Nakagami-m fading conditions show that both system complexity and resource utilization are ameliorated with a better performance compared to the previous works.

The mashup is a hot research topic in recent years. In this paper, we propose an efficient Mashup Resource Discovery(MRD) approach to facilitating mashup searching. Basing on an index library, MRD acts high performance in response time. By an external ontology base and a synonym base, we apply a semantics discovery, avoiding semantics annotation in mashup description files. By evaluating the prestige of mashups(especially for mashup api), we rank the results and make mashups with high prestige get higher ranking. The experimental evaluation shows that our MRD act high performance both in time consuming and r-p curve statistics.

During the design procedure of BPEL (Business Process Execution Language) processes, there may be control dependency deadlocks among the activities in BPEL. We design a novel Agree/Refuse Matrix (ARM) to real-timely detect control dependency deadlocks. Online detection approach can be integrated into Active BPEL Designer to extend their functions and improve the accuracy of BPEL processes. Most importantly, this method's real-time property can help avoiding detecting the whole process from scratch caused by process's partial modifications.

Web service evaluation is one of the key problems in web service discovery and selection research fields. In this paper, we propose an approach to evaluate the web service performance. Different from traditional evaluation methods, our approach is based on users experience, and we apply the idea and result in common webs evaluation fields to help construct our evaluation system. We import the Alexa ranking to help evaluate the information providing performance of web services, we import the idea of Page Rank to help designing our evaluation method for the function sharing performance of web services.

We propose a Discovery approach to find web services composition flows sorted by similarity. The approach extracts information from BPEL files. When creating new web services composition, the discovery result can be reused directly or provide reference. We import the lexical semantic in matching keywords. By analysis and proof, we show that our keyword splitting method can extend the application of lexical semantics matching to a large extent and our approach can provide higher precision ratio than traditional search engine.