DocumentCode
3063876
Title
Precoding with X-codes to increase capacity with discrete input alphabets
Author
Mohammed, Saif Khan ; Viterbo, Emanuele ; Hong, Yi ; Chockalingam, Ananthanarayanan
Author_Institution
Indian Inst. of Sci., Bangalore, India
fYear
2010
fDate
13-18 June 2010
Firstpage
2148
Lastpage
2152
Abstract
We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non-diagonal precoder based on X-Codes in to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using Singular Value Decomposition (SVD) and X-codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and the 2 × 2 real rotation matrices for each pair (parameterized with a single angle). This precoding structure enables to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is equivalent to i) optimizing the rotation angle and the power allocation within each pair and ii) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal precoder by Cruz et al., and significantly better than mercury/waterfilling strategy by Lozano et al.. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.
Keywords
Gaussian channels; MIMO communication; precoding; singular value decomposition; Gaussian multiple-input multiple-output channels; MIMO channels; X-codes; discrete input alphabets; nondiagonal precoder; singular value decomposition; Channel state information; Communication channels; DSL; Decoding; MIMO; Matrix decomposition; Mutual information; OFDM; Singular value decomposition; Transmitters; MIMO; Mutual information; OFDM; condition number; precoding; singular value decomposition;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2010 IEEE International Symposium on
Conference_Location
Austin, TX
Print_ISBN
978-1-4244-7890-3
Electronic_ISBN
978-1-4244-7891-0
Type
conf
DOI
10.1109/ISIT.2010.5513452
Filename
5513452
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