Predictive Coding of Bit Loading for Time-Correlated MIMO Channels With a Decision Feedback Receiver

In this paper, we consider variable-rate transmission over a slowly varying multiple-input multiple-output (MIMO) channel with a decision feedback receiver. The transmission rate is adapted to the channel by dynamically assigning bits to the subchannels of the MIMO system. Predictive quantization is...

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Veröffentlicht in:IEEE transactions on signal processing Jg. 63; H. 13; S. 3376 - 3386
Hauptverfasser: Li, Chien-Chang, Lin, Yuan-Pei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.07.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
bit loading
Channels
Correlation
Decomposition
differential feedback
Errors
Feedback
limited feedback
Load modeling
Loading
Mathematical models
Matrix decomposition
MIMO
predictive quantization
Quantization
Quantization (signal)
Receivers
Transmitters
variable rate transmission
ISSN:1053-587X, 1941-0476
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Zusammenfassung:In this paper, we consider variable-rate transmission over a slowly varying multiple-input multiple-output (MIMO) channel with a decision feedback receiver. The transmission rate is adapted to the channel by dynamically assigning bits to the subchannels of the MIMO system. Predictive quantization is used for the feedback of bit loading to take advantage of the time correlation inherited from the temporally correlated channel. Due to the use of decision feedback at the receiver, the bit loading is related to the Cholesky decomposition of the channel Gram matrix. Assuming the channel is modeled by a slowly varying Gauss-Markov process, we show that the nested submatrices generated during the process of Cholesky decomposition can be updated as time evolves. Based on the update, we derive the optimal predictor of the next bit loading for predictive quantization. Furthermore, we derive the statistics of the prediction error, which are then exploited to design the quantizer to achieve a smaller quantization error. Simulations are given to demonstrate that the proposed predictive quantization gives a good approximation of the desired transmission rate with a low feedback rate.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2015.2421471