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Coordinated Non-Orthogonal Multiple Access (CO-NOMA)

Authors: Anthony Beylerian; Tomoaki Ohtsuki;

Coordinated Non-Orthogonal Multiple Access (CO-NOMA)

Abstract

We propose a Coordinated Non-Orthogonal Multiple Access (CO-NOMA) scheme for resource allocation in the context of mobile networks. NOMA refers to schemes where multiple users can access the wireless channel in the same frequency band simultaneously. In this study, we consider NOMA with power domain multiplexing, where the near- far property in space is exploited through appropriate power allocations. Moreover, the space domain is further exploited by coordinating transmissions from several distributed radio units. This approach, known as Coordinated Multi- Point (CoMP), can complement NOMA in order to further make use of the available degrees of freedom. Therefore, we discuss and propose a suboptimal scheduling strategy that achieves NOMA with coordinated transmitters in the downlink, with linear complexity, and compare performances with other schemes. The proposed scheme is shown to enhance performances for low to medium number of users per cell, as observed from system level simulations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Top 10%
Top 10%
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