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Chung Duc Ho

dblp:190/7527 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2018
0000-0003-4279-4542ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 81% Internet of things and sensor networks · 19%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
energy efficiency
0.312018
Power Allocation for Multi-Way Massive MIMO Relaying · IEEE Trans. Commun. 2018
Physical-layer communications › MIMO
massive MIMO
0.312018
Power Allocation for Multi-Way Massive MIMO Relaying · IEEE Trans. Commun. 2018
Physical-layer communications
MIMO
0.312018
Power Allocation for Multi-Way Massive MIMO Relaying · IEEE Trans. Commun. 2018
Physical-layer communications › relaying
multi-way relaying
0.312018
Power Allocation for Multi-Way Massive MIMO Relaying · IEEE Trans. Commun. 2018
Physical-layer communications
power allocation
0.312018
Power Allocation for Multi-Way Massive MIMO Relaying · IEEE Trans. Commun. 2018
Physical-layer communications › channel state information
channel state information acquisition
0.112018
Power Allocation for Multi-Way Massive MIMO Relaying · IEEE Trans. Commun. 2018

Methods — techniques the papers use, named apart from their topics

successive interference cancellation · 0.3decode-and-forward relaying · 0.3convex optimization · 0.3
YearPublicationVenuePosition
2018 How to Scale up the Spectral Efficiency of Multi-Way Massive MIMO Relaying?
abstract
This paper considers a decode-and-forward (DF) multi-way massive multiple-input multiple-output (MIMO) relay system where many users exchange their data with the aid of a relay station equipped with a massive antenna array. We propose a new transmission protocol which leverages successive cancelation decoding and zero-forcing (ZF) at the users. By using properties of massive MIMO, a tight analytical approximation of the spectral efficiency is derived. We show that our proposed scheme uses only half of the time-slots required in the conventional scheme (in which the number of time-slots is equal to the number of users [1]), to exchange data across different users. As a result, the sum spectral efficiency of our proposed scheme is nearly double the one of the conventional scheme, thereby boosting the performance of multi-way massive MIMO to unprecedented levels. To improve the network energy efficiency, we also propose a power allocation scheme which maximizes the energy efficiency under a given peak power constraint at each user and the relay.
Chung Duc Ho, Hien Quoc Ngo, Michail Matthaiou, Long Dinh Nguyen
ICC1
2018 Power Allocation for Multi-Way Massive MIMO Relaying
abstract
We consider a multi-way decode-and-forward relaying network with very large antenna arrays at the relay station. In this system, each user and the relay operate in half-duplex and time-division duplexing modes. To exchange information among all users, we propose a new transmission protocol which combines massive multiple-input multiple-output technology with linear processing, self-interference cancelation, and successive cancelation decoding. Our proposed transmission protocol reduces the number of time-slots for data exchange among users by approximately 2 times, compared with the conventional data transmission protocol. For this new topology, we derive a very tight approximation of the spectral efficiency in closed-form assuming perfect channel state information (CSI). Then, a CSI acquisition method at the relay and the users is provided and analyzed. We show via numerical simulations, that the performance gap between imperfect and perfect CSI cases is small. The closed-form expression of the spectral efficiency enables us to design two power allocation schemes. In the first power allocation scheme, we choose the transmit powers at the users and the relay to maximize the sum spectral efficiency, subject to a given quality-of-service requirement for each user. In the second power allocation scheme, the objective is the energy efficiency taking into account the hardware power consumption. Both power allocation schemes can be efficiently executed by iteratively solving a sequence of convex problems. Numerical results verify the effectiveness of the proposed transmission protocol and the power allocation schemes compared with the state of the art.
Chung Duc Ho, Hien Quoc Ngo, Michail Matthaiou, Long Dinh Nguyen
IEEE Trans. Commun.1