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Jia-Wei Chiang

dblp:185/2779 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

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

Computer networks · 1

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
Wireless networking · 61% Internet architecture and protocols · 30% Physical-layer communications · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless networking
cognitive radio
0.212016
Unified Opportunistic Scheduling for Layered Multicast over Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2016
Internet architecture and protocols › multicast
layered multicast
0.212016
Unified Opportunistic Scheduling for Layered Multicast over Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2016
Wireless networking
opportunistic scheduling
0.212016
Unified Opportunistic Scheduling for Layered Multicast over Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2016
Physical-layer communications › channel coding › adaptive coding › rate-adaptive coding
rateless coding
0.112016
Unified Opportunistic Scheduling for Layered Multicast over Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2016

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

simulation · 0.2optimization · 0.2
YearPublicationVenuePosition
2016 Unified Opportunistic Scheduling for Layered Multicast over Cognitive Radio Networks
abstract
We investigate the multicast of layered multimedia content in single hop cognitive radio (CR) networks and ways of improving the subscriber utility. The proposed unified opportunistic scheduling (UOS) aggressively utilizes diversity potential present in CR by exploiting two types of multiuser diversity (MUD), one between multicast groups and another between data stream subscribers in a group. As a result, the resource usage efficiency is significantly increased, and better utility can be achieved. According to derived effective average subscriber throughput under unified MUD, a scheduling algorithm is designed to approach the theoretical throughput improvement. We specifically introduce controlled competition between multicast groups to balance the increasing resource efficiency and the risk of overstretching the limited available spectrum. The algorithm combines prioritization, rateless coding, and data fragmentation to inherently cope with dynamic spectrum availability in CR. The presented simulation results show improved performance in various situations in comparison to other schemes not taking full advantage of the present MUD potential.
Pavol Polacek, Chih-Wei Huang, Jia-Wei Chiang
IEEE Trans. Mob. Comput.3