We develop a framework based on deep reinforcement learning (DRL) to solve the spectrum allocation problem in emerging integrated access and backhaul (IAB) architecture with large scale deployment dynamic environment. The available is divided into several orthogonal sub-channels, donor base station (DBS) all IAB nodes have same resource for allocation, where DBS utilizes those sub-channels links of associated user equipment (UE) as well nodes, an node can utilize its UEs. This one key...

Cell-free networks are considered to be a promising distributed network architecture satisfy the increasing number of users and high rate expectations in beyond-5G systems. However, further enhance capacity, an high-cost base stations (BSs) is required. To address this problem inspired by cost-effective intelligent reflecting surface (IRS) technique, we propose fully decentralized design framework for cooperative beamforming IRS-aided cell-free networks. We first transform centralized...

Millimeter Wave (mmWave) communications with full-duplex (FD) have the potential of increasing spectral efficiency, relative to those half-duplex. However, residual self-interference (SI) from FD and high pathloss inherent mmWave signals may degrade system performance. Meanwhile, hybrid beamforming (HBF) is an efficient technology enhance channel gain mitigate interference reasonable complexity. conventional HBF approaches for systems are based on optimization processes, which either too...

To handle the data explosion in era of Internet-of-things, it is interest to investigate decentralized network, with aim at relaxing burden central server along preserving privacy. In this work, we develop a fully federated learning (FL) framework an inexact stochastic parallel random walk alternating direction method multipliers (ISPW-ADMM). Performing more efficient communication and enhanced privacy preservation compared current state-of-the-art, proposed ISPW-ADMM can be partially immune...

The layered manganese-based lithium-rich oxide (LLO) cathode material is considered one of the most attractive candidates for next-generation lithium-ion batteries due to its high specific capacity. However, LLOs suffer from low coulombic efficiency as well cycle capacity decay oxygen release and structural transformation during first charge. Here, we report a simple method with 2-[4-(2-hydroxyethyl)-1-piperazinyl]ethanesulfonic acid (HEPES) treatment combined heat under H2 atmosphere LLO...

Due to the drastic increase of mobile traffic, wireless caching is proposed serve repeated requests for content download. To determine scheme decentralized networks, preference learning problem based on mobility prediction studied. We first formulate as a regularized multi-task (DRMTL) without considering terminals (MTs). The solved by hybrid Jacobian and Gauss-Seidel proximal multi-block alternating direction method (ADMM) algorithm, which proven conditionally converge optimal solution with...

The alternating direction method of multipliers (ADMM) has been recently recognized as a promising optimizer for large-scale machine learning models. However, there are very few results studying ADMM from the aspect communication costs, especially jointly with privacy preservation, which critical distributed learning. We investigate efficiency and privacy-preservation by solving consensus optimization problem over decentralized networks. Since walk algorithms can reduce load, we first...

Massive (or large-scale) multi-input multi-output (MIMO) is a promising means to improve the energy efficiency, spectral efficiency and throughput. However, complexity of detection increases exponentially with scale MIMO system. In this paper, we propose biased minimum mean-square error (MMSE) based on Jacobi iterative method (JIM) reduce massive detector. The proposed MMSE can provide post-equalized signal-to-interference-and-noise-ratio (SINR) without processing. Besides, if Gray-mapping...

Chinese remainder theorem (CRT) has been widely studied with its applications in frequency estimation, phase unwrapping, coding theory, and distributed data storage. Since traditional CRT is greatly sensitive to the errors residues due noises, problem of robustly reconstructing integers via erroneous intensively literature. In order reconstruct integers, there are basically two approaches: one introduce common divisors moduli other directly decrease dynamic range. this paper, we take further...

The alternating direction method of multipliers (ADMM) has recently been recognized as a promising approach for large-scale machine learning models. However, very few results study ADMM from the aspect communication costs, especially jointly with running time. In this letter, we investigate efficiency and time in solving consensus optimization problem over decentralized networks. We first review effort random walk (W-ADMM), which reduces costs at expense To accelerate convergence speed...

Future communication networks call for new solutions to support their capacity and delay demands by leveraging potentials of the millimeter wave (mmWave) frequency band. However, beam training procedure in mmWave systems incurs significant overhead as well huge energy consumption. As such, deriving an adaptive control policy is beneficial both delay-sensitive energy-efficient data transmission over networks. To this end, we investigate problem joint communications paper. Specifically,...

With the development of society, electricity has become an indispensable material, and reliability power grid more important. The ice-covered will lead to accidents such as broken poles other accidents, which seriously threaten safe operation. Therefore, a simple efficient detection method is urgently needed. To solve this problem, based on good performance convolution neural network, paper applies it network icing. A classification icing image proposed, can effectively classify recognize...

Hybrid beamforming (HBF) design is a crucial stage in millimeter wave (mmWave) multi-user multi-input multi-output (MU-MIMO) systems. However, conventional HBF methods are still with high complexity and strongly rely on the quality of channel state information. We propose an extreme learning machine (ELM) framework to jointly optimize transmitting receiving beamformers. Specifically, provide accurate labels for training, we first factional-programming majorization-minimization based method...

Big data, including applications with high security requirements, are often collected and stored on multiple heterogeneous devices, such as mobile drones, vehicles. Due to the limitations of communication costs it is paramount importance analyze information in a decentralized manner instead aggregating data fusion center. To train large-scale machine learning models, edge/fog computing leveraged an alternative centralized learning. We consider problem model parameters multiagent system...

The first dual nickel/photoredox-catalyzed enantioselective reductive cross-coupling of racemic α-chloro thioesters with aryl iodides has been developed. This strategy avoids the need for organometallic reagents or stoichiometric metal reductants. reaction could tolerate a wide range substrate scope excellent reactivity and high enantioselectivities (up to 91% ee) access variety chiral α-aryl thioesters. synthetic utility corresponding is demonstrated. Furthermore, we explored mechanism such...

A novel broadband compact lumped-element balun with a tail inductor is proposed in this letter. The employment of improves amplitude and phase balances for better performance. Furthermore, compared baluns utilizing conventional micro-strip approaches or second-order lattice topology, topology offers significant circuit size reduction. Theoretical analysis the optimized value presented to improve operation bandwidth. concept realized validated by 2.45 GHz surface mounted devices (SMD)....

This paper presents a G-band ON-OFF-keying transmitter and G-Band receiver in 65-nm bulk CMOS process. The proposed includes high-efficiency push-push voltage-controlled oscillator (VCO) with body-bias switch-based modulator using the folded coupled-line topology. benefits of switch design are theoretically analyzed proved. utilized topology based on envelope detector inverter-chain-based output buffer. standalone VCO demonstrates peak dc-RF efficiency 4.1% at 209 GHz 1.02 dBm power....

Wireless content caching in cellular networks is an efficient way to reduce the service delay and alleviate backhaul pressure.For benefits of sharing spectral storage resources, clustering cached has recently attracted significant research interests.Meanwhile, since multimedia (e. g.., video) may require a huge transmission rates, millimeter wave (mmWave) communication considered be scheme for cacheenabled networks.We investigate ergodic rate average typical user terminal (UT) clustered...

Edge computing provides a promising paradigm to support the implementation of Internet Things (IoT) by offloading tasks nearby edge nodes. Meanwhile, increasing network size makes it impractical for centralized data processing due limited bandwidth, and consequently decentralized learning scheme is preferable. Reinforcement (RL) has been widely investigated shown be solution decision-making optimal control processes. For RL in setup, nodes (agents) connected through communication aim work...

In recent years, the issue of carbon emissions has attracted worldwide attention. This innovative research idea is to input total emission data Mianyang City from 2000 2020 into GRU network model predict trend in next few years. view complexity neural training, this paper introduces adaptive coefficients dynamically adjust number units improve training efficiency and accuracy. Through processing analysis data, used transform internal relationship sequence a higher-order expression, thereby...

Wireless caching enables popular files to be stored at the base stations (BSs) in advance, which has been considered as an efficient way reduce service delay and alleviate heavy burdens on backhaul links. In this paper, we study BS clustering scheme for cooperative wireless networks (CWCNs) with heterogeneous file preference among users BSs, propose minimum cost (MC) based scheme. We first introduce weight-based function, characterizes trade-off between transmission cost, then formulate...