Selective vector perturbation for low-power small cell MISO downlinks

A selective vector perturbation technique is introduced for low-power Small Cell downlink. In contrast to conventional vector perturbation (VP) where the search for perturbation vectors involves all users' symbols, here the perturbation is applied to a subset of the transmitted symbols. This therefore introduces a performance-complexity tradeoff, where the complexity is greatly reduced compared to VP by limiting the dimensions of the sphere search, at the expense of a performance penalty compared to VP. By changing the size of the subset of perturbed users, the above tradeoff can be controlled. We further propose three distinct criteria for selecting which users' symbols to perturb, each of which yields a different performance-complexity tradeoff. The presented analytical and simulation results show that the proposed is most useful in the low-power small cell scenarios where power efficiency levels improved by up to 300% compared to VP are demonstrated.

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

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

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

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

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

[6]  Claus-Peter Schnorr,et al.  Lattice Basis Reduction: Improved Practical Algorithms and Solving Subset Sum Problems , 1991, FCT.

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

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

[9]  M Kobayashi,et al.  Green Small-Cell Networks , 2011, IEEE Vehicular Technology Magazine.

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

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

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

[13]  Filippo Tosato,et al.  Joint Linear and Nonlinear Precoding in MIMO Systems , 2011, IEEE Communications Letters.

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

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

[16]  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.