Gaussian mixture model-based Expectation-Maximization signal processing algorithm in power-efficiency networks-Reference-Cited by-同舟云学术

Gaussian mixture model-based Expectation-Maximization signal processing algorithm in power-efficiency networks

Published:2022-05-16 Issue: Volume: Page:
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Container-title:ICC 2022 - IEEE International Conference on Communications
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Author:

Gong Yi¹,Meng Fanke²,Li Qingyu¹,Yu Keping³,Mumtaz Shahid⁴,Muhaidat Sami⁵

Affiliation:

1. Ministry of Education, Beijing Information Science and Technology University,School of Information Communication Engineering, Key Laboratory of Modern Measurement & Control Technology,China

2. Xi’an University of Posts & Telecommunications

3. Waseda University,Global Information and Telecommunication Institute,Tokyo,Japan

4. Instituto de Telecomunicaces,Aveiro,Portugal

5. Khalifa University,Center for Cyber-Physical Systems,UAE

Funder

Beijing Information Science and Technology University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9837954/9838246/09838814.pdf?arnumber=9838814

Reference13 articles.

1. Censored Approximate Message Passing Based Multiuser Detection in Massive MIMO

2. Identification of Two-Dimensional Causal Systems With Missing Output Data via Expectation–Maximization Algorithm

3. Texas-Instruments, ADC/1000RF 12-bit, 3.2/2.0 GSPS RF Sampling ADC Data Manual,2013

4. Energy Efficient Hybrid Beamforming for Multi-User Millimeter Wave Communication With Low-Resolution A/D at Transceivers

5. DOA Estimation Aided by Magnitude Measurements

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