On improving the BER performance of rate-adaptive block transceivers, with applications to DMT

Two strategies for improving the (uncoded) bit error rate (BER) performance of practical rate-adaptive block-by-block communication schemes, such as discrete multitone modulation (DMT) is proposed. Our strategies are inspired by some recent work which showed that for uniformly bit-loaded schemes, the transmission strategy which minimizes the BER for a linear receiver involves allocating power to the subchannels that are implicit in the block-by-block framework in a minimum mean square error (MMSE) fashion and linearly combining these subchannels using a normalized discrete Fourier transform (DFT) matrix. This combining equalizes the decision point signal-to-noise ratios (SNRs) of the subchannels. Given a nonuniformly bit-loaded scheme, our first design strategy simply performs a DFT-based linear combination within the groups of subchannels which share the same constellation. Our second strategy provides further reduction in the BER by reallocating power within these groups in a MMSE fashion prior to DFT combining. Our examples indicate that our design strategies can provide significant reductions in the BER, and give rise to substantial SNR gains (of the order of several decibels).

[1]  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.

[2]  Dongweon Yoon,et al.  On the general BER expression of one- and two-dimensional amplitude modulations , 2002, IEEE Trans. Commun..

[3]  John M. Cioffi,et al.  Understanding Digital Subscriber Line Technology , 1999 .

[4]  Dov Wulich,et al.  Minimum BER power loading for OFDM in fading channel , 2002, IEEE Trans. Commun..

[5]  Anna Scaglione,et al.  Optimal designs for space-time linear precoders and decoders , 2002, IEEE Trans. Signal Process..

[6]  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..

[7]  Anna Scaglione,et al.  Redundant filterbank precoders and equalizers-part I , 1998 .

[8]  Jian Yang,et al.  On joint transmitter and receiver optimization for multiple-input-multiple-output (MIMO) transmission systems , 1994, IEEE Trans. Commun..

[9]  J. Salz,et al.  Digital transmission over cross-coupled linear channels , 1985, AT&T Technical Journal.

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

[11]  Anna Scaglione,et al.  Filterbank Transceivers Optimizing Information Rate in Block Transmissions over Dispersive Channels , 1999, IEEE Trans. Inf. Theory.

[12]  John M. Cioffi,et al.  Optimum linear joint transmit-receive processing for MIMO channels with QoS constraints , 2004, IEEE Transactions on Signal Processing.

[13]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .