LR-Aided MIMO Detectors under Correlated and Imperfectly Estimated Channels

In this contribution, lattice reduction (LR) technique is applied to improve the multiple-input multiple-output (MIMO) detector performance under correlated channels and imperfect channel estimation constrains. Zero-forcing, minimum mean squared error, ordered successive interference cancellation and sphere decoding (SD) detectors are analysed taking into consideration (a) different correlated fading channel indexes, (b) increasing spectral efficiency, by combining number of transmit antennas and modulation formats, and (c) channel coefficient error estimations. Analysis of correlated channel effects over the MIMO system performance equipped with different LR-aided detectors are carried out, indicating the robustness of those detectors and the SD–MIMO detector deficiency to deal with such channel condition. Besides, computational complexities are compared aiming to determine the best LR–MIMO detection scheme under the perspective of performance-complexity tradeoff.

[1]  László Lovász,et al.  Factoring polynomials with rational coefficients , 1982 .

[2]  Erik G. Larsson,et al.  Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays , 2012, IEEE Signal Process. Mag..

[3]  Babak Hassibi,et al.  Maximum-likelihood decoding and integer least-squares: The expected complexity , 2003, Multiantenna Channels: Capacity, Coding and Signal Processing.

[4]  Markku J. Juntti,et al.  Lattice Reduction Based Detection Algorithms in High Correlated MIMO-OFDM System , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[5]  Yichuang Sun,et al.  The Capacity Performance of ASTC-MIMO-OFDM System in a Correlated Rayleigh Frequency-Selective Channel , 2013, Wirel. Pers. Commun..

[6]  Liang Liu,et al.  A Parallel Early-Pruned K-Best MIMO Signal Detector Up to 1.9Gb/s , 2011, Wirel. Pers. Commun..

[7]  C. Hermite Extraits de lettres de M. Ch. Hermite à M. Jacobi sur différents objects de la théorie des nombres. , 1850 .

[8]  Hermann Minkowski Ueber positive quadratische Formen. , 1886 .

[9]  Robert F. H. Fischer,et al.  Low-complexity near-maximum-likelihood detection and precoding for MIMO systems using lattice reduction , 2003, Proceedings 2003 IEEE Information Theory Workshop (Cat. No.03EX674).

[10]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[11]  F. Hlawatsch,et al.  Detection techniques for MIMO spatial multiplexing systems , 2005 .

[12]  H. Artes Reducing sphere decoder complexity by elliptical tree pruning , 2004, IEEE 5th Workshop on Signal Processing Advances in Wireless Communications, 2004..

[13]  Walid A. Al-Hussaibi,et al.  Fast Receive Antenna Selection for Spatial Multiplexing MIMO over Correlated Rayleigh Fading Channels , 2013, Wirel. Pers. Commun..

[14]  Gene H. Golub,et al.  Matrix computations , 1983 .

[15]  Rodney A. Kennedy,et al.  Effect of Signal and Noise Mutual Coupling on MIMO Channel Capacity , 2007, Wirel. Pers. Commun..

[16]  Kevin T. Kelly,et al.  The expected complexity of problem solving , 1987 .

[17]  H. Vincent Poor,et al.  Performance of Spatial Modulation in the Presence of Channel Estimation Errors , 2012, IEEE Communications Letters.

[18]  Carl Friedrich Gauß Carl Friedrich Gauss' Untersuchungen über höhere Arithmetik. (Disquisitiones arithmeticae. Theorematis arithmetici demonstratio nova. Summatio quarundam serierum singularium ó. ). Deutsch hrsg. von H. Mas , 1889 .

[19]  C. Hermite Extraits de lettres de M. Ch. Hermite à M. Jacobi sur différents objects de la théorie des nombres. (Continuation). , .

[20]  Wai Ho Mow,et al.  Variants of the LLL Algorithm in Digital Communications: Complexity Analysis and Fixed-Complexity Implementation , 2010, ArXiv.

[21]  Sergio Verdu,et al.  Multiantenna Channels: Capacity, Coding and Signal Processing , 2003 .

[22]  van A Allert Zelst,et al.  A single coefficient spatial correlation model for multiple-input multiple-output (MIMO) radio channels , 2002 .

[23]  M. Seysen,et al.  Simultaneous reduction of a lattice basis and its reciprocal basis , 1993, Comb..

[24]  Hui Xu,et al.  Research Progress of Lattice Bases Reduction Algorithms , 2012 .

[25]  Jiandong Li,et al.  Robust Uniform Channel Decomposition and Power Allocation for MIMO Systems with Imperfect CSI , 2012, Wirel. Pers. Commun..

[26]  Zohreh Andalibi,et al.  Precoder Design for BICM-MIMO Systems Under Channel Estimation Error , 2013, Wirel. Pers. Commun..

[27]  Björn E. Ottersten,et al.  On the complexity of sphere decoding in digital communications , 2005, IEEE Transactions on Signal Processing.

[28]  Zhou ShiXian,et al.  Research Progress of Lattice Bases Reduction Algorithms , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[29]  Dirk Wübben,et al.  Reduced complexity MMSE detection for BLAST architectures , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[30]  Dirk Wübben,et al.  Lattice Reduction , 2011, IEEE Signal Processing Magazine.

[31]  Taufik Abrão,et al.  S/MIMO MC-CDMA Heuristic Multiuser Detectors Based on Single-Objective Optimization , 2010, Wirel. Pers. Commun..

[32]  K.-D. Kammeyer,et al.  MMSE extension of V-BLAST based on sorted QR decomposition , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[33]  Dirk Wübben,et al.  MMSE-based lattice-reduction for near-ML detection of MIMO systems , 2004, ITG Workshop on Smart Antennas (IEEE Cat. No.04EX802).

[34]  John S. Thompson,et al.  Fixing the Complexity of the Sphere Decoder for MIMO Detection , 2008, IEEE Transactions on Wireless Communications.

[35]  Yi Zhang,et al.  Effect of Channel Estimation Error on the Mutual Information of MIMO Fading Channels , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[36]  E.G. Larsson,et al.  MIMO Detection Methods: How They Work [Lecture Notes] , 2009, IEEE Signal Processing Magazine.

[37]  M. Sandell,et al.  Simplified Quantisation in a Reduced-Lattice MIMO Decoder , 2011, IEEE Communications Letters.

[38]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .

[39]  Björn E. Ottersten,et al.  The Error Probability of the Fixed-Complexity Sphere Decoder , 2009, IEEE Transactions on Signal Processing.