TY - JOUR
T1 - Filter Design for MIMO Sampling and Reconstruction
AU - Venkataramani, Raman
AU - Bresler, Yoram
N1 - Funding Information:
Manuscript received January 16, 2002; revised March 24, 2003. This work was supported in part by a grant from the Defence Advanced Research Projects Agency under Contract F49620-98-1-0498, administered by the Air Force Office of Scientific Research, and by the National Science Foundation under Infrastructure Grant CDA-24396. This work was performed while the first author was with the University of Illinois at Urbana-Champaign. The associate editor coordinating the review of this paper and approving it for publication was Dr. Helmut Bölcskei.
PY - 2003/12
Y1 - 2003/12
N2 - We address the problem of finite impulse response (FIR) filter design for uniform multiple-input multiple-output (MIMO) sampling. This scheme encompasses Papoulis' generalized sampling and several nonuniform sampling schemes as special cases. The input signals are modeled as either continuous-time or discrete-time multiband input signals, with different band structures. We present conditions on the channel and the sampling rate that allow perfect inversion of the channel. Additionally, we provide a stronger set of conditions under which the reconstruction filters can be chosen to have frequency responses that are continuous. We also provide conditions for the existence of FIR perfect reconstruction filters, and when such do not exist, we address the optimal approximation of the ideal filters using FIR filters and a min-max l2 end-to-end distortion criterion. The design problem is then reduced to a standard semi-infinite linear program. An example design of FIR reconstruction filters is given.
AB - We address the problem of finite impulse response (FIR) filter design for uniform multiple-input multiple-output (MIMO) sampling. This scheme encompasses Papoulis' generalized sampling and several nonuniform sampling schemes as special cases. The input signals are modeled as either continuous-time or discrete-time multiband input signals, with different band structures. We present conditions on the channel and the sampling rate that allow perfect inversion of the channel. Additionally, we provide a stronger set of conditions under which the reconstruction filters can be chosen to have frequency responses that are continuous. We also provide conditions for the existence of FIR perfect reconstruction filters, and when such do not exist, we address the optimal approximation of the ideal filters using FIR filters and a min-max l2 end-to-end distortion criterion. The design problem is then reduced to a standard semi-infinite linear program. An example design of FIR reconstruction filters is given.
KW - Filter design
KW - MIMO equalization
KW - Min-max criterion
KW - Multiband sampling
KW - Multichannel deconvolution
KW - Multiple source separation
KW - Multiple-input multiple-output (MIMO) channel
KW - Multirate signal processing
KW - Semi-infinite optimization
KW - Signal reconstruction
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U2 - 10.1109/TSP.2003.819002
DO - 10.1109/TSP.2003.819002
M3 - Article
AN - SCOPUS:0345306715
SN - 1053-587X
VL - 51
SP - 3164
EP - 3176
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 12
ER -