CSI Feedback Reduction for MIMO Interference Alignment

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. Most of the existing IA designs require full channel state information (CSI) at the transmitters, which induces a huge CSI signaling cost. Hence it is desirable...

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Vydáno v:IEEE transactions on signal processing Ročník 61; číslo 18; s. 4428 - 4437
Hlavní autoři: Rao, Xiongbin, Ruan, Liangzhong, Lau, Vincent K. N.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.09.2013
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Alignment
Antennas
Applied sciences
Channels
Coding, codes
Costs
CSI feedback dimension
Decorrelation
Design engineering
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Feedback
IA feasibility condition
Information, signal and communications theory
Interference
Interference alignment (IA)
Manifolds
Measurement
MIMO interference networks
Networks
Null space
partial CSI feedback
Quantization (signal)
Reduction
Signal and communications theory
Signal to noise ratio
Signal, noise
Streams
Telecommunications and information theory
Vectors
Performance evaluation
MIMO system
Parameter estimation
CSI feedback dimension
partial CSI feedback
Coding circuit
Transmitter
Feedback regulation
Signalling
MIMO interference networks
Interference alignment (IA)
Simulation
Coding
Channel estimation
First order
IA feasibility condition
Signal processing
Feasibility
Metric
Decorrelation
Pretreatment
Antenna
Signal to noise ratio
ISSN:1053-587X, 1941-0476
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Popis
Shrnutí:Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. Most of the existing IA designs require full channel state information (CSI) at the transmitters, which induces a huge CSI signaling cost. Hence it is desirable to improve the feedback efficiency for IA and in this paper, we propose a novel IA scheme with a significantly reduced CSI feedback. To quantify the CSI feedback cost, we introduce a novel metric, namely the feedback dimension. This metric serves as a first-order measurement of CSI feedback overhead. Due to the partial CSI feedback constraint, conventional IA schemes can not be applied and hence, we develop a novel IA precoder/decorrelator design and establish new IA feasibility conditions. Via dynamic feedback profile design, the proposed IA scheme can also achieve a flexible tradeoff between the degree of freedom (DoF) requirements for data streams, the antenna resources and the CSI feedback cost. We show by analysis and simulations that the proposed scheme achieves substantial reductions of CSI feedback overhead under the same DoF requirement in MIMO interference networks.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2013.2269902