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  3. Computational Intelligence and AI in Games
  4. Multiuser Precoding With Limited Cooperation for Large-Scale MIMO Multicell Downlink
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Category: Computational Intelligence and AI in Games
By MTech Projects
MTech Projects
15.May
Hits: 6

Multiuser Precoding With Limited Cooperation for Large-Scale MIMO Multicell Downlink

PROJECT TITLE :

Multiuser Precoding With Limited Cooperation for Large-Scale MIMO Multicell Downlink

ABSTRACT:

Multiple base stations (BSs) equipped with giant antenna arrays will perform cooperative downlink transmissions using beamforming for cell-edge users to provide high knowledge rate services. But, thanks to an excessive overhead for the channel state info (CSI) exchange between BSs, the cooperation with full CSI may not be sensible for large antenna arrays. Thus, primarily based on an existing precoding approach, 2 totally different precoding approaches with partial cooperation, where no CSI exchange is required, are proposed. One among them (called Sort III precoding) contains a higher performance, and its performance can be any improved by user allocation, which becomes potential by deriving a closed-kind expression for transmission power. For low-complexity implementations, an algorithm springs for the user allocation based on the greedy algorithm. Below sure channel conditions, closed-form expressions for average transmission powers also are derived to see asymptotic performance. Based on them, we have a tendency to will show that the average transmission power becomes $Q$ times more than that with full cooperation if precoding is administered with native CSI only, where $Q$ is the amount of BSs in cooperation, which would be thought-about as a penalty due to partial cooperation. Through simulations, it's shown that this penalty (i.e., the increase of transmission power) can be reduced by user allocation.

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