Titlebook: Artificial Intelligence for Communications and Networks; First EAI Internatio Shuai Han,Liang Ye,Weixiao Meng Conference proceedings 2019 I

仲裁者

Millimeter Wave Massive MIMO Channel Estimation and Trackingrical results show that the performance can be considerably improved in the case of a large number of antennas over the conventional scheme. Furthermore, this algorithm also has better performance under traditional MIMO conditions.

patriot

補(bǔ)角

Design of Radar-Communication Integrated Signal Based on OFDMs consistent with the communication OFDM signal. The degree of system integration is high, and it achieves communication functions without reducing radar detection capability. For the high PAPR problem, we introduce CE-OFDM signals, and derive a radar signal processing algorithm based on FFT demodul

Insufficient

A Multicast Beamforming Algorithm to Improve the Performance of Group Service for Multicell B-TrunC up users, is obtained on the basis of semidefinite relaxation (SDR). Theoretical analysis and simulation results show that the proposed multicast beamforming algorithm based on same-frequency multicell coordination can significantly improve the SNR of cell-edge users and increase the group user chan

Delirium

Neural Networks in Hybrid Precoding for Millimeter Wave Massive MIMO Systemson results indicate that there is an optimal number of users which can minimize the performance deterioration. Moreover, the simulation results also show that slight deterioration in the throughput and energy efficiency of mmWave massive MIMO systems is caused by further decomposing the baseband pre

臭名昭著

expeditious

A New Two-Microphone Reduce Size SMFTF Algorithm for Speech Enhancement in New Telecommunication SysTM-RSMFTF algorithm in comparison with conventional TM-NLMS algorithm and almost similar performances with full-size TM-SFTF in terms of various objectives criteria such as Segmental SNR, System Mismatch, Segmental MSE.

accessory

1867-8211 lligence for Communications and Networks, AICON 2019, held in Harbin, China, in May 2019. The 93 full papers were carefully reviewed and selected from 152 submissions. The papers are organized in topical sections on artificial intelligence, mobile network, deep learning, machine learning, wireless c

共同確定為確

Fahrzeugreifen und Fahrwerkentwicklung fully shared decoder) to jointly predict target word and POS tag sequences. Experiments on Chinese-English and German-English translation tasks show that the fully shared decoder can acquire the best performance, which increases the BLEU score by 1.4 and 2.25 points respectively compared with the attention-based NMT model.

hauteur

Fahrzeugreifen und Fahrwerkentwicklungalso presented to generate a single-maximum beampattern. Simulation results verify the effectiveness. It shows that the proposed approach outperforms the multiple-input multiple-output (MIMO) radar in focusing the transmit energy on the far-field targets.