Abstract | ||
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This paper proposes a way of applying interference- aware interference mitigation algorithms to device- to-device (D2D) communications in cellular networks for system throughput improvement. One of main purposes for using D2D communications is to offload throughput passing through a base station in cellular networks. In this sense, interference management between cellular and D2D signals is inevitable for both cellular and D2D mobile stations (MSs). Recently, interference-aware interference mitigation algorithms have been proposed in a theoretical aspect as well as a practical aspect. These algorithms operate based on interference information given at a MS, which can be obtained via network assistance or blind estimation. This paper explains how interference- aware algorithms can be applied to D2D communications in cellular networks. Moreover, this paper analyzes the throughput performance by deriving the rate upper-bounds. Simulation results demonstrate that the system throughput can be significantly improved while not losing the performance of a cellular MS too much. |
Year | DOI | Venue |
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2014 | 10.1109/VTCSpring.2014.7022956 | VTC Spring |
Keywords | Field | DocType |
base station,d2d communications,cellular radio,system throughput improvement,network assistance,interference information,device- to-device communications,cellular mobile stations,blind estimation,d2d signals,rate upper-bounds,d2d mobile stations,interference suppression,cellular signals,interference management,throughput passing,cellular networks,interference-aware interference mitigation algorithms,signal to noise ratio,throughput,lead,decoding,resource management | Radio resource management,Interference (communication),Base station,Computer science,Co-channel interference,Computer network,Electronic engineering,Cellular network,Interference (wave propagation),Throughput,Zero-forcing precoding | Conference |
ISSN | Citations | PageRank |
1550-2252 | 3 | 0.40 |
References | Authors | |
9 | 3 |
Name | Order | Citations | PageRank |
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Hyukjoon Kwon | 1 | 61 | 6.66 |
Jungwon Lee | 2 | 890 | 95.15 |
Inyup Kang | 3 | 304 | 32.39 |