DocumentCode :
1248150
Title :
Precoding by Pairing Subchannels to Increase MIMO Capacity With Discrete Input Alphabets
Author :
Mohammed, Saif Khan ; Viterbo, Emanuele ; Hong, Yi ; Chockalingam, Ananthanarayanan
Author_Institution :
Dept. of Electr. Eng. (ISY), Linkoping Univ., Linkoping, Sweden
Volume :
57
Issue :
7
fYear :
2011
fDate :
7/1/2011 12:00:00 AM
Firstpage :
4156
Lastpage :
4169
Abstract :
We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non diagonal precoder based on the 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 a 2 × 2 real rotation matrix for each pair (parameterized with a single angle). This precoding structure enables us 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 solved by: 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 pre coder by Cruz et al., and is significantly better than Mercury/waterfllling 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; channel capacity; channel coding; matrix algebra; precoding; singular value decomposition; Gaussian multiple-input multiple-output channels; MIMO capacity; X-codes; discrete input alphabets; mercury-waterfllling strategy; nondiagonal precoder; pairing subchannel scheme; parallel subchannels; power allocation; rotation matrix; singular value decomposition; Complexity theory; Encoding; Joints; MIMO; Mutual information; OFDM; Resource management; Condition number; multiple-input multiple-output (MIMO); mutual information; orthogonal frequency division multiplexing (OFDM); precoding; singular value decomposition (SVD);
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2011.2146050
Filename :
5895100
Link To Document :
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