Although millimeter-wave aerial base station(m Ae BS) gains rich wireless capacity, it is technically difficult for deploying several m Ae BSs to solve the surge of data traffic in hotspots when considering the amount...
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Although millimeter-wave aerial base station(m Ae BS) gains rich wireless capacity, it is technically difficult for deploying several m Ae BSs to solve the surge of data traffic in hotspots when considering the amount of interference from neighboring m Ae BS. This paper introduces coordinated multiple points transmission(Co MP) into the m Ae BS-assisted network for capacity enhancement and designs a two-timescale approach for three-dimensional(3D) deployment and user association of cooperative m Ae BSs. Specially, an affinity propagation clustering based m Ae BS-user cooperative association scheme is conducted on a large timescale followed by modeling the capacity evaluation, and a deployment algorithm based on multi-agent(MA) deep deterministic policy gradient(MADDPG) is designed on the small timescale to obtain the 3D position of m Ae BS in a distributed manner. Simulation results show that the proposed approach has significant throughput gains over conventional schemes without Co MP, and the MADDPG is more efficient than centralized deep reinforcement learning(DRL) algorithms in deriving the solution.
Integrated sensing and communication(ISAC) is regarded as a promising technology for sixth-generation(6G) *** channel modeling is essential for designing and evaluating the performance of ISAC systems. In December 202...
Integrated sensing and communication(ISAC) is regarded as a promising technology for sixth-generation(6G) *** channel modeling is essential for designing and evaluating the performance of ISAC systems. In December 2023, the 3rd Generation Partnership Project(3GPP)established a new industry specification group dedicated to ISAC. The group's objective is to research ISAC channel modeling, laying the technical foundations for 6G standardization. Compared to the traditional 5G communication channel, 6G ISAC channel requires accurate modeling of new properties.
User profiling has very important applications for many downstream tasks. Most existing methods only focus on modeling user profiles of one social network with plenty of data. However, user profiles are difficult to a...
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User profiling has very important applications for many downstream tasks. Most existing methods only focus on modeling user profiles of one social network with plenty of data. However, user profiles are difficult to acquire, especially when the data is scarce. Fortunately, we observed that similar users have similar behavior patterns in different social networks. Motivated by such observations, in this paper, we for the first time propose to study the user profiling problem from the transfer learning perspective. We design two efficient frameworks for User Profile transferring acrOss Networks, i.e., UPON and E-UPON. In UPON, we first design a novel graph convolutional networks based characteristic-aware domain attention model to find user dependencies within and between domains (i.e., social networks). We then design a dual-domain weighted adversarial learning method to address the domain shift problem existing in the transferring procedure. In E-UPON, we optimize UPON in terms of computational complexity and memory. Specifically, we design a mini-cluster gradient descent based graph representation algorithm to shrink the searching space and ensure parallel computation. Then we use an adaptive cluster matching method to adjust the clusters of users. Experimental results on Twitter-Foursquare dataset demonstrate that UPON and E-UPON outperform the state-of-the-art models.
None-line-of-sight (NLOS) ultraviolet (UV) communication has attracted increasing attention in recent years. The atmospheric turbulence will deteriorate the performance of NLOS UV communications. Existing works on the...
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None-line-of-sight (NLOS) ultraviolet (UV) communication has attracted increasing attention in recent years. The atmospheric turbulence will deteriorate the performance of NLOS UV communications. Existing works on the turbulent model of NLOS UV single-scattering channels only considered the narrow beam cases. In this letter, we propose a turbulent channel model using the equivalent scattering points (ESPs) approach to characterize the fluctuation effect on UV signals under large full-width beam divergence angles and field-of-view angles. An analytical turbulent scintillation index is derived considering the turbulent correlation between different ESPs and is verified by its numerical solutions. Numerical results demonstrate that the turbulent scintillation index will increase with the turbulent correlation distance. Besides, we demonstrate that a large common volume can mitigate the turbulent fluctuation effect on UV communications, which can be explained by an "equivalent spatial diversity effect" due to the large common volume.
In this letter, we investigate the resource allocation problem for multiple access in the cell-free multiple-input multiple-output (CF MIMO) system. To fully utilize multi-dimensional resources and meet the diverse de...
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In this letter, we investigate the resource allocation problem for multiple access in the cell-free multiple-input multiple-output (CF MIMO) system. To fully utilize multi-dimensional resources and meet the diverse demands of users, we extend the hybrid multiple access technology into the CF MIMO system based on its user-centric architecture, which unifies space division multiple access, non-orthogonal multiple access and orthogonal multiple access. Considering distinct expenses of different multiple access modes at receivers, we design a cost-aware utility function as the metric and develop a cost-aware utilization maximization optimization problem. To address this non-convex combinatorial optimization problem, an iterative resource allocation algorithm is proposed. This algorithm consists of a subchannel allocation algorithm based on matching theory and a power allocation algorithm based on Lagrange dual method. Simulation results validate the superiority of proposed scheme over fixed multiple access schemes.
The distributed prescribed-time orbit containment control for the satellite cluster flight with multiple dynamic leaders is *** directed information communication topology between followers is taken into account in th...
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The distributed prescribed-time orbit containment control for the satellite cluster flight with multiple dynamic leaders is *** directed information communication topology between followers is taken into account in the overall *** the satellite mass is assumed to be constant,a distributed prescribed-time orbit containment controller is,firstly,presented to drive the followers into the dynamic convex hull produced by multiple ***,the parameter uncertainty is considered,and a prescribed-time sliding mode estimator is introduced to estimate the desired velocity of each *** on the estimated state,a novel distributed adaptive prescribed-time orbit containment control scheme is *** Lyapunov stability theory is utilized to prove the prescribed-time stability of the closed-loop ***,several numerical simulations and comparison of different control methods are provided to verify the effectiveness and superiority of the proposed control method.
A new network monitoring technology called in-band network telemetry (INT) offers users the ability to gather precise, real-time data about the entire network. While several studies have used in-band network telemetry...
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A new network monitoring technology called in-band network telemetry (INT) offers users the ability to gather precise, real-time data about the entire network. While several studies have used in-band network telemetry for network-wide monitoring, it is insufficient for the growing number of massive networks that are resource-constrained. Finding the most valuable information with the least amount of resources is challenging. In this paper, We formalize the problem of in-band network-wide telemetry with low resource overheads. This formalized problem aims to achieve high freshness of network performance data using fewer resources and reducing deployment and maintenance costs for O&M personnel. We propose a heuristic method based on path reorganization to address this issue. The heuristic algorithm for planning paths starts from greedy path planning results and finds a more appropriate planning scheme by merging and reorganizing paths. Additionally, probabilistic insertion is considered to reduce the impact of intrusiveness of in-band network telemetry. Simulation results show that our approach is effective in improving resource utilization and reducing the cost of monitoring the network compared to similar studies.
This letter investigates the sparse channel estimation for holographic multiple-input multiple-output (HMIMO) systems. Given that the wavenumber-domain representation is based on a series of Fourier harmonics that are...
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This letter investigates the sparse channel estimation for holographic multiple-input multiple-output (HMIMO) systems. Given that the wavenumber-domain representation is based on a series of Fourier harmonics that are in essence a series of orthogonal basis functions, a novel wavenumber-domain sparsifying basis is designed to expose the sparsity inherent in HMIMO channels. Furthermore, by harnessing the beneficial sparsity in the wavenumber domain, the sparse estimation of HMIMO channels is structured as a compressed sensing problem, which can be efficiently solved by our proposed wavenumber-domain orthogonal matching pursuit (WD-OMP) algorithm. Finally, numerical results demonstrate that the proposed wavenumber-domain sparsifying basis maintains its detection accuracy regardless of the number of antenna elements and antenna spacing. Additionally, in the case of antenna spacing being much less than half a wavelength, the wavenumber-domain approach remains highly accurate in identifying the significant angular power of HMIMO channels.
This letter proposes an integrated sensing and communication (ISAC) beamforming method that senses multiple moving targets while simultaneously communicating with multiple user equipment (UE). The radar estimation rat...
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This letter proposes an integrated sensing and communication (ISAC) beamforming method that senses multiple moving targets while simultaneously communicating with multiple user equipment (UE). The radar estimation rate is combined with the communication achievable rate to assess ISAC system performance. Semidefinite relaxation (SDR) and successive convex approximation (SCA) are used to handle the non-convex rank constraint and convexify the objective function, respectively. To reduce the computational complexity, a manifold-based algorithm is proposed as an alternative. Simulation results validate the effectiveness of the proposed schemes.
Tactile sensing is an indispensable capability for humans or intelligent devices to engage in complex physical interactions. Mainstream tactile sensors are contact-based, which show limitation in measuring deformable ...
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Tactile sensing is an indispensable capability for humans or intelligent devices to engage in complex physical interactions. Mainstream tactile sensors are contact-based, which show limitation in measuring deformable objects and demanding high maintenance effort. As a complementary solution, a new paradigm of contactless tactile sensing is attracting much interest. While promising, they can only identify coarse-grained single tactile perception properties, either material type or surface roughness. In this paper, we propose airTac, which includes a novel contactless digital tactile receptor model, capable of simultaneously extracting these two basic tactile properties in a fine-grained resolution, by harnessing the massive bandwidth of terahertz(THz) frequency band. airTac is designed based on our key finding: while the impact of material type and surface roughness on THz signal intertwine with each other, they are actually separable, i.e., roughness manifests a certain pattern in distorting relative high-frequency components of the whole THz spectrum. Therefore, we custom-design a bio-inspired deep neural network model to decouple the intertwined THz signal, and distill the tactile perception properties embedded underlying the signal. We prototype airTac using a THz time domain spectroscopy, and perform extensive evaluation over 9 different daily material types with 39 different surface roughness. airTac achieves a material identification accuracy of 97.43% and a roughness classification accuracy of 91.46%, which demonstrates that airTac can identify common materials in daily life and exceed a fingertip spatial resolution of 1mm.
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