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Dynamic resource allocation with precoding and joint coding scheme for limited feedback‐based wireless multi‐antenna multicast system
Author(s) -
Chen Lei,
Wang Xiaoxiang,
He Gaoning
Publication year - 2013
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2012.0767
Subject(s) - multicast , computer science , precoding , subcarrier , computer network , telecommunications link , quality of service , resource allocation , distributed computing , algorithm , mimo , orthogonal frequency division multiplexing , channel (broadcasting)
In conventional multicast scheme (CMS), the total throughput of multicast group is constrained by the user with the worst channel quality. In order to overcome this problem of limited throughput, the authors introduce a resource allocation algorithm by exploiting layered coding combined with erasure correction coding for multicast services in the downlink of orthogonal frequency‐division multiple access‐based multi‐antenna system. To reduce the feedback overhead of uplink, the authors design a novel transmission scheme with limited feedback. Then, the joint subcarrier and power allocation problem for the data of base layer and enhancement layers are formulated, which is shown to be non‐deterministic polynomial‐ hard. Hence, in order to reduce the computational complexity, they propose a three‐phase suboptimal algorithm. The algorithm is designed to maximise the system throughput, whereas at the same time guarantee the quality of services (QoS) requirements of all multicast groups. It is composed of precoding scheme, proportional fairness subcarrier allocation algorithm and modified water‐filling power allocation algorithm with QoS guarantees (MWF‐Q). To further decrease the complexity of MWF‐Q, a power allocation algorithm with increased fixed power allocation algorithm with QoS guarantees is introduced. Simulation results show that the proposed algorithms based on limited feedback scheme significantly outperform CMS and any other existing algorithm with full feedback. Moreover, the proposed scheme can efficiently reduce 50% of the full feedback overhead.

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