Bi-Directional Training for Adaptive Beamforming and Power Control in Interference Networks

We study distributed algorithms for adapting transmit beamformers and linear receiver filters in a Time-Division Duplex Multiple-Input Multiple-Output (MIMO) interference network. Each transmitter transmits a single beam, and neither the transmitters nor receivers have a priori Channel State Informa...

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Vydané v:IEEE transactions on signal processing Ročník 62; číslo 3; s. 607 - 618
Hlavní autori: Changxin Shi, Berry, Randall A., Honig, Michael L.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.02.2014
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
adaptive beamforming
Algorithms
Applied sciences
Bidirectional control
Channel estimation
Channels
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Information, signal and communications theory
Interference
interference networks
MIMO
Multiplexing
Networks
Power control
precoder optimization
Receivers
Signal and communications theory
Signal to noise ratio
Signal, noise
Telecommunications and information theory
Training
Transmitters
Performance evaluation
Multiplexing
Parameter estimation
Bidirectional link
adaptive beamforming
Transmitter
Updating
interference networks
Beam forming
Implementation
Learning
Least squares method
Channel estimation
Pricing
MIMO
precoder optinization
MIMO system
Coding circuit
Weighting
Power control
Linear filter
Distributed algorithm
A priori estimation
Signal processing
Numerical simulation
Tariffication
Signal to interference plus noise ratio
ISSN:1053-587X, 1941-0476
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Popis
Shrnutí:We study distributed algorithms for adapting transmit beamformers and linear receiver filters in a Time-Division Duplex Multiple-Input Multiple-Output (MIMO) interference network. Each transmitter transmits a single beam, and neither the transmitters nor receivers have a priori Channel State Information (CSI). Given a fixed set of powers, we present an adaptive version of the Max-SINR algorithm: pilot symbols are alternately transmitted in the forward direction (transmitters to receivers) and in the reverse direction (receivers to transmitters). Unlike previous channel estimation schemes, transmissions in each direction are synchronized across the source or destination nodes, and the pilots are used to update the filters/beams directly using a least squares criterion. To improve the performance with limited training, we include exponential weighting of the least squares objective across data frames. In addition, bi-directional training can be used to implement analog interference pricing for power control: training in the forward direction is used to measure received signal-to-interference plus noise ratios (SINRs) and interference prices, and those estimates combined with synchronous backward training are used to update the powers. Given sufficient training this method achieves the same performance as interference pricing updates with perfect CSI. Numerical results are presented that illustrate the performance of these methods in different settings.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2013.2293122