Title :
Low Complexity MIMO Precoder Design with LDLH Channel Decomposition
Author :
Chou, Che-Chen ; Wu, Jen-Ming
Author_Institution :
Inst. of Commun. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Abstract :
To exploit the multiplexing and the diversity gains in a multiple-input multiple-output (MIMO) wireless system, the singular value decomposition (SVD) is typically used to decompose the MIMO channel into parallel eigen-modes. However, the dynamics of the frequency selective channel fading variations often make the decomposed subchannels ill-conditioned and lead to unsatisfied performance in terms of bit error rate (BER). Recently, two improved SVD-based decomposition schemes, i.e. the geometric mean decomposition (GMD) and the uniform channel decomposition (UCD), are developed which try to achieve uniform subchannel gains. Unfortunately, both of them require even higher complexity than that of SVD with power allocation. In this paper, we propose a decomposition method, called LDLH which has moderate subchannel gains uniformity while exhibits the lowest complexity compared with that of aforementioned SVD-based schemes. Simulations are also given to show that the proposed LDLH scheme is more robust than all other schemes at higher SNR as channel estimation errors become severe.
Keywords :
MIMO communication; channel estimation; decomposition; error statistics; fading channels; multiplexing; precoding; singular value decomposition; BER performance; GMD; LDLH channel decomposition; MIMO wireless system; SVD-based decomposition scheme; UCD; bit error rate performance; channel estimation error; diversity gain; frequency selective channel fading variation; geometric mean decomposition; low complexity MIMO precoder design; multiple-input multiple-output wireless system; multiplexing gain; parallel eigenmode; power allocation; singular value decomposition; subchannels ill-conditioned decomposition; uniform channel decomposition; uniform subchannel gain; Bit error rate; Complexity theory; Covariance matrix; MIMO; Matrix decomposition; Resource management; Signal to noise ratio;
Conference_Titel :
Communications (ICC), 2011 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-61284-232-5
Electronic_ISBN :
1550-3607
DOI :
10.1109/icc.2011.5963033