M
Mugen Peng
Researcher at Beijing University of Posts and Telecommunications
Publications - 554
Citations - 16681
Mugen Peng is an academic researcher from Beijing University of Posts and Telecommunications. The author has contributed to research in topics: Relay & Resource allocation. The author has an hindex of 51, co-authored 501 publications receiving 12800 citations. Previous affiliations of Mugen Peng include Peking University & Chinese Ministry of Education.
Papers
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Proceedings ArticleDOI
Capacity Performance of Amplify-and-Forward MIMO Relay with Transmit Antenna Selection and Maximal-Ratio Combining
TL;DR: C capacity performance analysis is presented for multiple-input multiple-output (MIMO) relay channels with transmit antenna selection and maximal-ratio combining receive in amplify-and-forward (AF) relay networks operating over flat Rayleigh fading channels.
Proceedings ArticleDOI
Comparison of capacity between adaptive tracking and switched beam smart antenna techniques in TDD-CDMA systems
Mugen Peng,Wenbo Wang +1 more
TL;DR: In this article, a theoretical analysis of TDD-CDMA capacity constraint is presented firstly when employing the adaptive tracking and switched beam smart antenna techniques in both uplink and downlink.
Posted Content
Cloud Radio Access Network: Virtualizing Wireless Access for Dense Heterogeneous Systems
TL;DR: A succinct overview is presented regarding the state of the art on the research on C-RAN with emphasis on fronthaul compression, baseband processing, medium access control, resource allocation, system-level considerations and standardization efforts.
Journal ArticleDOI
Outage performance of orthogonal space-time block codes transmission in opportunistic decode-and-forward cooperative networks with incremental relaying
TL;DR: The results show that the proposed scheme outperforms traditional direct transmission and fixed ODF in arbitrary SNR region and the outage probability and diversity order depend directly on the relay number, antenna configuration and incremental relaying trigger value.
Journal ArticleDOI
Training Design and Channel Estimation in Uplink Cloud Radio Access Networks
TL;DR: Simulation results show that the proposed channel estimation algorithm can effectively decrease the estimation mean square error and increase the average effective signal-to-noise ratio (AESNR) in C-RANs.