Power-Efficient Tomlinson-Harashima Precoding for the Downlink of Multi-User MISO Systems

We propose a power-efficient Tomlinson-Harashima precoder (THP) in the downlink of multi-user multiple-input single-output (MU-MISO) systems, where a transmit power reduction is achieved by means of interference optimization. The adopted approach is based on adaptively scaling the symbols of a number of users whose received signal-to-noise ratio (SNR) thresholds are known to the transmitter. By doing this, the interference can be better aligned to the symbols of interest, thus reducing the power required to cancel it. The scaling is performed by forming a constrained optimization problem, solved with existing well-known techniques, which entails an increase in the computational complexity at the base station. To quantify this trade-off in performance and complexity, a study of the impact in the signal processing load is carried out by means of a power efficiency analysis. The presented analytical and simulation results in this paper confirm that the proposed technique increases the power efficiency up to 100% with respect to previous THP-based approaches while, at the same time, maintaining the same average performance.

[1]  Mathini Sellathurai,et al.  Vector Perturbation Based on Symbol Scaling for Limited Feedback MISO Downlinks , 2014, IEEE Transactions on Signal Processing.

[2]  Ying-Chang Liang,et al.  Power and modulo loss tradeoff with expanded soft demapper for LDPC coded GMD-THP MIMO systems , 2009, IEEE Transactions on Wireless Communications.

[3]  M Arakawa,et al.  Computational Workloads for Commonly Used Signal Processing Kernels , 2006 .

[4]  Piet Demeester,et al.  Comparison of power consumption of mobile WiMAX, HSPA and LTE access networks , 2010, 2010 9th Conference of Telecommunication, Media and Internet.

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

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

[7]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization , 2005, IEEE Transactions on Wireless Communications.

[8]  Cheng Wang,et al.  Adaptive downlink multi-user MIMO wireless systems for correlated channels with imperfect CSI , 2006, IEEE Transactions on Wireless Communications.

[9]  Chau Yuen,et al.  Achieving near-capacity at low SNR on a multiple-antenna multiple-user channel , 2009, IEEE Transactions on Communications.

[10]  Derek Curd,et al.  Power Consumption in 65 nm FPGAs , 2007 .

[11]  Thomas F. Coleman,et al.  An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds , 1993, SIAM J. Optim..

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

[13]  Tharmalingam Ratnarajah,et al.  Maximizing Energy Efficiency in the Vector Precoded MU-MISO Downlink by Selective Perturbation , 2014, IEEE Transactions on Wireless Communications.

[14]  Chungyong Lee,et al.  Performance Optimization of Tomlinson-Harashima Precoder with Tilted Constellation , 2010, IEEE Communications Letters.

[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.

[17]  D. G. Watts,et al.  Nonlinear Regression: Iterative Estimation and Linear Approximations , 2008 .

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

[19]  Mandy Eberhart,et al.  Digital Communication Over Fading Channels , 2016 .

[20]  Reinaldo A. Valenzuela,et al.  V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channel , 1998, 1998 URSI International Symposium on Signals, Systems, and Electronics. Conference Proceedings (Cat. No.98EX167).

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

[22]  Wei Yu,et al.  Trellis and convolutional precoding for transmitter-based interference presubtraction , 2005, IEEE Transactions on Communications.

[23]  Chungyong Lee,et al.  Tomlinson-harashima precoder with tilted constellation for reducing transmission power , 2009, IEEE Transactions on Wireless Communications.

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

[25]  Giuseppe Caire,et al.  Lattice coding and decoding achieve the optimal diversity-multiplexing tradeoff of MIMO channels , 2004, IEEE Transactions on Information Theory.

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

[27]  Thomas H. Lee.  The Design of CMOS Radio-Frequency Integrated Circuits , 1998 .

[28]  Tiejun Lv,et al.  Approximate Minimum BER Power Allocation for MIMO-THP System , 2008, 2008 International Wireless Communications and Mobile Computing Conference.

[29]  Jean-Yves Le Boudec,et al.  Predicting User-Cell Association in Cellular Networks from Tracked Data , 2009, MELT.

[30]  Babak Hassibi,et al.  On the expected complexity of integer least-squares problems , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[31]  Tharmalingam Ratnarajah,et al.  A Low-Complexity Sequential Encoder for Threshold Vector Perturbation , 2013, IEEE Communications Letters.

[32]  Tharmalingam Ratnarajah,et al.  Transmit-Power Efficient Linear Precoding Utilizing Known Interference for the Multiantenna Downlink , 2014, IEEE Transactions on Vehicular Technology.

[33]  Narayan Prasad,et al.  Analysis of decision feedback detection for MIMO Rayleigh-fading channels and the optimization of power and rate allocations , 2004, IEEE Transactions on Information Theory.

[34]  Jorge J. Moré,et al.  The Levenberg-Marquardt algo-rithm: Implementation and theory , 1977 .

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

[36]  Martin Haardt,et al.  An introduction to the multi-user MIMO downlink , 2004, IEEE Communications Magazine.