TY - GEN
T1 - A Krylov subspace Multi-Stage decomposition of the transmit Wiener Filter
AU - Dietl, Guido
AU - Joham, Michael
AU - Kreuter, Philipp
AU - Brehmer, Johannes
AU - Utschick, Wolfgang
PY - 2004
Y1 - 2004
N2 - Besides methods based on eigensubspaces, the reduced-rank Multi-Stage Wiener Filter (MSWF) is a well-known approach for the approximation of the Wiener Filter, the op timum linear receive filter in the minimum mean square error sense, in a lower-dimensional subspace in order to reduce computational complexity and enhance performance in case of low sample support. Analogous, the Transmit Wiener Filter (TxWF) is the optimum linear filter at the transmitter side where the receiver is kept simple since it applies only a scalar weighting. In this paper, we use the principles of the MSWF to derive a multi-stage decomposition of the TxWF which we denote Transmit Multi-Stage Wiener Filter (TxMSWF). In addition, we will show that the reduced-rank TxMSWF can be seen as an approximation of the TxWF in a Krylov subspace. Simulation results reveal that the TxMSWF achieves near optimum performance for relatively low rank. Thus, it is an interesting alternative to low complexity approximations of the TxWF in eigensubspaces.
AB - Besides methods based on eigensubspaces, the reduced-rank Multi-Stage Wiener Filter (MSWF) is a well-known approach for the approximation of the Wiener Filter, the op timum linear receive filter in the minimum mean square error sense, in a lower-dimensional subspace in order to reduce computational complexity and enhance performance in case of low sample support. Analogous, the Transmit Wiener Filter (TxWF) is the optimum linear filter at the transmitter side where the receiver is kept simple since it applies only a scalar weighting. In this paper, we use the principles of the MSWF to derive a multi-stage decomposition of the TxWF which we denote Transmit Multi-Stage Wiener Filter (TxMSWF). In addition, we will show that the reduced-rank TxMSWF can be seen as an approximation of the TxWF in a Krylov subspace. Simulation results reveal that the TxMSWF achieves near optimum performance for relatively low rank. Thus, it is an interesting alternative to low complexity approximations of the TxWF in eigensubspaces.
UR - http://www.scopus.com/inward/record.url?scp=11244270538&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:11244270538
SN - 0780383273
SN - 9780780383272
T3 - 2004 ITG Workshop on Smart Antennas - Proceedings
SP - 247
EP - 252
BT - 2004 ITG Workshop on Smart Antennas - Proceedings
T2 - 2004 ITG Workshop on Smart Antennas - Proceedings
Y2 - 18 March 2004 through 19 March 2004
ER -