An efficient design method for vector broadcast systems with common information

We consider the problem of determining an optimal transmission scheme for broadcasting a common message over vector channels, given (perfect) channel knowledge at both the receive and transmit ends. We provide an efficient method for jointly designing a linear transmitter and and a set of linear receivers so as to minimize a weighted mean square error (WMSE) of the data estimates. The computational efficiency follows from the convex formulations that we develop. These formulations enable utilization of highly efficient interior point methods. For diagonal channel matrices, which appear in multicarrier systems that employ cyclic prefixing, we show that the optimal transmitter is obtained by subcarrier allocation and power loading. The set of minimum MSE transceivers for a vector broadcast system is parametrized by a unitary matrix degree of freedom. For the case of diagonal systems, we show how this unitary matrix can be chosen so that the symbol error rate is minimized (over the given set). This optimal unitary matrix ensures that, for each receiver, the subcarrier signal-to-noise ratios (SNRs) are all the same. Simulations indicate that our designs can provide significantly improved performance over standard designs.

[1]  G. Giannakis,et al.  Wireless Multicarrier Communications where Fourier Meets , 2022 .

[2]  H. Vincent Poor,et al.  Probability of error in MMSE multiuser detection , 1997, IEEE Trans. Inf. Theory.

[3]  Jos F. Sturm,et al.  A Matlab toolbox for optimization over symmetric cones , 1999 .

[4]  Akbar M. Sayeed,et al.  Optimal transceiver design for selective wireless broadcast with channel state information , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  John M. Cioffi,et al.  A practical discrete multitone transceiver loading algorithm for data transmission over spectrally shaped channels , 1995, IEEE Trans. Commun..

[6]  T. Davidson,et al.  Asymptotically minimum bit error rate block precoders for minimum mean square error equalization , 2002, Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002.

[7]  Andrea J. Goldsmith,et al.  The capacity region of broadcast channels with intersymbol interference and colored Gaussian noise , 2001, IEEE Trans. Inf. Theory.

[8]  John M. Cioffi,et al.  Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization , 2003, IEEE Trans. Signal Process..

[9]  Zhi-Quan Luo,et al.  Minimum BER block precoders for zero-forcing equalization , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[10]  Georgios B. Giannakis,et al.  Wireless multicarrier communications , 2000, IEEE Signal Process. Mag..

[11]  Zhi-Quan Luo,et al.  Transceiver optimization for block-based multiple access through ISI channels , 2004, IEEE Transactions on Signal Processing.

[12]  Zhi-Quan Luo,et al.  Trans-ceiver optimization for multiple access through ISI channels , 2001 .

[13]  Wei Yu,et al.  Sum capacity of Gaussian vector broadcast channels , 2004, IEEE Transactions on Information Theory.

[14]  F. Graybill,et al.  Matrices with Applications in Statistics. , 1984 .

[15]  F. Graybill,et al.  Matrices with Applications in Statistics. , 1984 .

[16]  David Tse,et al.  Optimal power allocation over parallel Gaussian broadcast channels , 1997, Proceedings of IEEE International Symposium on Information Theory.

[17]  Edwin K. P. Chong,et al.  Output MAI distributions of linear MMSE multiuser receivers in DS-CDMA systems , 2001, IEEE Trans. Inf. Theory.