The trend of using larger scale antenna arrays will continue toward 6G systems, where the number antennas be further scaled up to improve spectral efficiency. However, increase in bring new challenges physical layer, such as frequent feedback high-speed mobile communications, multiband coexistence overhead from sub-6 (gigahertz) GHz terahertz (THz), and energy consumption due increased components circuits. In this article, we introduce artificial intelligence (AI)-based channel extrapolation...

In order to support the future digital society, sixth generation (6G) network faces challenge work efficiently and flexibly in a wider range of scenarios. The traditional way system design is sequentially get electromagnetic wave propagation model typical scenarios firstly then do by simulation offline, which obviously leads 6G lacking adaptation dynamic environments. Recently, with aid sensing enhancement, more environment information can be obtained. Based on this, from radio perspective,...

Channel state information (CSI) is crucial for massive multi-input multi-output (MIMO) system. As the antenna scale increases, acquiring CSI results in significantly higher system overhead. In this letter, we propose a novel channel prediction method which utilizes wireless environment with pilot pattern optimization (WEI-CP). Specifically, distribution of scatterers around mobile station (MS) affecting CSI, represents information, acquired using multi-view images. Then, to dig out mapping...

As a virtual, synchronized replica of physical network, the digital twin network (DTN) is envisioned to sense, predict, optimize and manage intricate wireless technologies architectures brought by 6G. Given that properties channel fundamentally determine system performances from layer layer, it critical prerequisite invisible in world be accurately efficiently twinned. To support 6G DTN, this paper first proposes multi-task adaptive ray-tracing platform for (MART-6G) generate with features,...

Conventionally statistical path loss models are high-dimensional data-based without utilizing specific environment features. In this letter, a novel features-based model (EFBM) for prediction is presented. We connect the propagation and channel by representing with low-dimensional features: distance, deviation, volume, blockage. The features propagation-related, which can predict directly Random Forest (RF) method. Compared method, proposed method reduce Root Mean Squared Error (RMSE) 0.33...

With the growing demand for wireless communication, sixth-generation (6G) network will be more complex. The digital twin channel (DTC) is envisioned as a promising enabler 6G, it can create an online replica of physical characteristics in world, thereby supporting precise and adaptive communication decisions 6G. In this article, we systematically review summarize existing efforts realizing DTC, providing comprehensive analysis ray tracing (RT), artificial intelligence (AI), large model...

To reduce the downlink beam sweep overhead of mmWave systems, we propose a deep reinforcement learning based dynamic selection (DRL-DBS) method. A new motivation is presented by analyzing change laws high- and low-frequency channels in spatial domain: to learn index offset between optimal sub-6 GHz spectrum. In DRL-DBS method, novel action space where actions can dynamically adjust size subset according high-and channel propagation laws. Hence, method predict with size, beamforming from...

Blockage prediction is significant to support mobility for millimeter wave (mmWave) communications, while the range limited centimeters in current work. This letter proposes a long-range blockage scheme leveraging frequency-dependent diffraction fringe characteristics. Firstly, Fresnel-Kirchhoff introduced into communication scenario analyze received power of mobile terminal. An interesting phenomenon found that fluctuates with an increasing amplitude before occurs, and fluctuation...

Joint communication and sensing (JCAS), in which the share same frequency band, resources hardware, is envisioned as a promising technology beyond 5G 6G communication. For JCAS system design performance evaluation, accurate efficient channel models are crucial. Since sense realized through information interaction environment, modeling needs to consider effect of environment based on traditional methods. However, most existing studies regard clean background ignore channel. To research this...

Millimeter wave (mmWave) communication has been a promising technology of future fifth generation (5G) cellular networks. Due to the tremendous propagation loss mmWave communication, device-to-device (D2D) communications are widely used over directional networks improve network throughput. In this paper, new time resource sharing scheme is proposed based on Stackelberg game for interference D2D links further enhance The causing can access by paying higher price, while no also be scheduled in...

Accurate channel state information (CSI) is important for the coherent detection of multiple-input-multiple-output (MIMO) system. Especially in a high-speed scenario, fast time-varying CSI gotten by conventional estimation schemes tend to be out date, thus tracking and predicting are more attractive indispensable. Motivated those, MIMO fading prediction framework proposed this paper. The principle behind our scheme that cluster-based has spatial consistency property, which means small-scale...

Driven by the demands of efficient network operation and high service availability, convergence artificial intelligence (AI) with radio access networks (RANs) has drawn considerable attention. However, current academic research mainly focuses on applying AI into optimizing RANs a few discussions architecture design. This article surveys recent progress achieved industry in integrating RANs, proposes an AI-driven fog RAN (F-RAN) paradigm. Specifically, being wrappers Al-re-lated...

In view of the propagation environment directly determining channel properties, applications can also be solved with aid environmental information. Inspired by task-oriented semantic communication and machine learning (ML) powered environment-channel mapping methods, we aim to provide a new from level. This letter defines semantics (PES) as limited set symbols (PESS). The PESS is extracted, which oriented application tasks concerned properties foundation. For method validation, PES-aided...

In this paper, we propose a novel 3D scenario information based channel modeling method with deep learning for Vehicular-to-infrastructure (V2I) communications. Specifically, the vehicular scanning sensors are utilized to capture point cloud of directly, and then characteristics generated mapped by network. Benefited from above framework, complexity environment reconstruction geometric calculation can be reduced greatly. The simulation results show that prediction precision reflection has...

With the research of upcoming sixth generation (6G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on future channel modeling. Considering model is prerequisite for system design performance evaluation 6G technologies, we face a challenging task: how to accurately efficiently various scenarios? This paper tries answer it. Firstly, features cluster-nuclei (CN) principle based (CNCM) are introduced. Then,...

Recently, whether the channel prediction can be achieved in diverse communication scenarios by directly utilizing environment information gained lots of attention due to impacting propagation characteristics wireless channel. This paper presents an information-based (EICP) method for connecting with assisted graph neural networks (GNN). Firstly, effective scatterers (ESs) producing paths and primary (PSs) generating single are detected building scatterer-centered graphs (SC-CEGs), which...

The sensitivity of millimeter-wave (mmWave) to blockage and the requirement for communication system support mobility scenarios makes mmWave beam prediction necessary. In this paper, effect diffraction characteristics on improving is investigated. A dataset with created, a recurrent neural network (RNN) designed capture in dataset. Further, generalization ability RNN different researched. results show that accuracy both further improved by utilizing characteristics. addition, increased 1.5%...

The millimeter-wave (mm-wave) band is of great importance for the future wireless communication systems. Studies on channels are to mmwave technologies. In this paper, we investigate 3-D clustering phenomenon mm-wave propagation at 28 GHz in a conference room. results including cluster mechanisms, relationship between clusters and physical environment, intra-cluster statistics presented. Results show that mechanisms influenced by room geometry. last hop sub-paths same may locate different...

With the development of sixth generation (6G) networks toward digitalization and intelligentization communications, rapid precise channel prediction is crucial for network potential release. Interestingly, a dynamic ray tracing (DRT) approach has recently been proposed, which utilizes results traditional RT to extrapolate multipath geometry evolution. However, both priori environmental data regularity in evolution can be further utilized. In this work, an enhanced-dynamic (E-DRT) algorithm...

Channel state information (CSI) is crucial for massive multi-input multi-output (MIMO) system. As the antenna scale increases, acquiring CSI results in significantly higher system overhead. In this letter, we propose a novel channel prediction method which utilizes wireless environmental with pilot pattern optimization (WEI-CSIP). Specifically, scatterers around mobile station (MS) are abstracted from using multiview images. Then, an feature map extracted by convolutional neural network...