Block Diagonalized Vector Perturbation for Multiuser MIMO Systems

Precoding with block diagonalization (BD) is an attractive technique for approaching the sum capacity in the multiuser multiple-input multiple-output (MIMO) broadcast channel. Unfortunately, BD requires either global channel state information at every receiver or an additional training phase, which demands additional control overhead and additional system planning. In this paper we propose a new multiuser MIMO algorithm that combines BD with vector perturbation (VP). The proposed algorithm avoids the second training phase, reduces each user is receiver complexity thanks to pre-equalization with VP at the transmitter, and has comparable diversity performance to BD with maximum likelihood decoding algorithm. A bound on the achievable sum rate for the proposed technique is derived and used to show that BD with VP approaches the achievable sum rate of BD with water-filling. Numerical simulations confirm that the proposed technique provides better bit error rate and diversity performance than BD with a zero-forcing receiver as well as BD with zero-forcing precoding.

[1]  Tung-Sang Ng,et al.  Generalized multiuser orthogonal space-division multiplexing , 2004, IEEE Transactions on Wireless Communications.

[2]  Rohit U. Nabar,et al.  Introduction to Space-Time Wireless Communications , 2003 .

[3]  Robert W. Heath,et al.  WLC06-4: A Lattice-Based MIMO Broadcast Precoder with Block Diagonalization for Multi-Stream Transmission , 2006, IEEE Globecom 2006.

[4]  Martin Haardt,et al.  Successive optimization Tomlinson-Harashima precoding (SO THP) for multi-user MIMO systems , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[5]  A. Lee Swindlehurst,et al.  A vector-perturbation technique for near-capacity multiantenna multiuser communication-part II: perturbation , 2005, IEEE Transactions on Communications.

[6]  Robert W. Heath,et al.  Coordinated Beamforming for the Multiuser MIMO Broadcast Channel With Limited Feedforward , 2008, IEEE Transactions on Signal Processing.

[7]  Shlomo Shamai,et al.  On the achievable throughput of a multiantenna Gaussian broadcast channel , 2003, IEEE Transactions on Information Theory.

[8]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[9]  Shlomo Shamai,et al.  The capacity region of the Gaussian MIMO broadcast channel , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

[10]  Martin Haardt,et al.  Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels , 2004, IEEE Transactions on Signal Processing.

[11]  Robert W. Heath,et al.  Shifting the MIMO Paradigm , 2007, IEEE Signal Processing Magazine.

[12]  A. Lee Swindlehurst,et al.  A vector-perturbation technique for near-capacity multiantenna multiuser communication-part I: channel inversion and regularization , 2005, IEEE Transactions on Communications.

[13]  A. Goldsmith,et al.  Sum power iterative water-filling for multi-antenna Gaussian broadcast channels , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[14]  Ross D. Murch,et al.  A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach , 2004, IEEE Transactions on Wireless Communications.

[15]  Robert F. H. Fischer,et al.  Precoding and Signal Shaping for Digital Transmission , 2002 .

[16]  Shlomo Shamai,et al.  The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel , 2006, IEEE Transactions on Information Theory.

[17]  B.L. Evans,et al.  Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization , 2005, IEEE Transactions on Signal Processing.

[18]  Huan Yao,et al.  Efficient signal, code, and receiver designs for MIMO communication systems , 2003 .

[19]  Jeffrey G. Andrews,et al.  Transmit Selection Diversity for Unitary Precoded Multiuser Spatial Multiplexing Systems With Linear Receivers , 2007, IEEE Transactions on Signal Processing.