Low complexity vector precoding for fast fading MIMO downlinks

Vector precoding (VP) requires the feed-forwarding of the transmit scaling factor to the receiver for correct detection. This can be problematic in fast fading scenarios where the statistics of the scaling factor change frequently and in limited feedback scenarios where the feed-forwarding to the receiver is prone to quantization errors. In response to this, a new VP scheme is proposed for the downlink of multi-user multiple input multiple output (MU-MIMO) systems with limited feedback. The proposed VP circumvents the need for receive-scaling by constraining the search of perturbing vectors to the area in the symbol constellation which is constrictive to the information symbols, i.e. the area where the distances from the decision thresholds are increased with respect to a distance threshold. By doing this, the perturbation quantities need not be removed at the receiver and successful detection can be done without the use of the modulo operation and the scaling factor. In addition, instead of a computationally expensive sphere search used in conventional VP, the proposed scheme uses a MinMax Optimization to select the perturbation quantities. As illustrated by the analysis and results, the error floor encountered in conventional VP in limited feedback scenarios is avoided in the proposed scheme.

[1]  Robert F. H. Fischer,et al.  Precoding in multiantenna and multiuser communications , 2004, IEEE Transactions on Wireless Communications.

[2]  Christos Masouros,et al.  Two-stage transmitter precoding based on data-driven code-hopping and partial zero forcing beamforming for MC-CDMA communications , 2009, IEEE Transactions on Wireless Communications.

[3]  M. Sellathurai,et al.  Computationally Efficient Vector Perturbation Precoding Using Thresholded Optimization , 2013, IEEE Transactions on Communications.

[4]  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.

[5]  Shlomo Shamai,et al.  Capacity and lattice strategies for canceling known interference , 2005, IEEE Transactions on Information Theory.

[6]  Christos Masouros,et al.  Lattice-Reduction for Power Optimisation Using the Fast Least-Squares Solution-Seeker Algorithm , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[7]  Inkyu Lee,et al.  Modulo Loss Reduction for Vector Perturbation Systems , 2010, IEEE Transactions on Communications.

[8]  Tharmalingam Ratnarajah,et al.  Interference as a Source of Green Signal Power in Cognitive Relay Assisted Co-Existing MIMO Wireless Transmissions , 2012, IEEE Transactions on Communications.

[9]  Inkyu Lee,et al.  A Decoupling Approach for Low-Complexity Vector Perturbation in Multiuser Downlink Systems , 2011, IEEE Transactions on Wireless Communications.

[10]  Christos Masouros,et al.  Dynamic linear precoding for the exploitation of known interference in MIMO broadcast systems , 2009, IEEE Transactions on Wireless Communications.

[11]  Daesik Hong,et al.  Line Encoding for Multiuser MIMO Downlink , 2011, IEEE Transactions on Vehicular Technology.

[12]  Christos Masouros,et al.  A Fast Least-Squares Solution-Seeker Algorithm for Vector-Perturbation , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[13]  Tharmalingam Ratnarajah,et al.  Interference-Driven Linear Precoding in Multiuser MISO Downlink Cognitive Radio Network , 2012, IEEE Transactions on Vehicular Technology.

[14]  Gerald Matz,et al.  Vector Perturbation Precoding Revisited , 2011, IEEE Transactions on Signal Processing.

[15]  Christos Masouros,et al.  Correlation Rotation Linear Precoding for MIMO Broadcast Communications , 2011, IEEE Transactions on Signal Processing.

[16]  Tharmalingam Ratnarajah,et al.  Interference Optimization for Transmit Power Reduction in Tomlinson-Harashima Precoded MIMO Downlinks , 2012, IEEE Transactions on Signal Processing.

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

[18]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[19]  Christos Masouros,et al.  Soft Linear Precoding for the Downlink of DS/CDMA Communication Systems , 2010, IEEE Transactions on Vehicular Technology.