Improving the DMT Performance for MIMO Communication With Linear Receivers

Multiple-input-multiple-output (MIMO) linear receivers are often of more practical interest than maximum-likelihood (ML) receivers due to their low decoding complexity but at the cost of worse diversity gain performance. Such a statement on performance loss is due to the assumption of using an independent identically distributed complex Gaussian vector as channel input. By removing this assumption, we find that the diversity performance of MIMO linear receivers can be significantly improved. In an extreme case, it can be the same as that of ML receivers. Specifically, in this paper, we investigate the diversity-multiplexing tradeoff (DMT) performance of MIMO linear receivers with colored and possibly degenerate Gaussian channel inputs. By varying the rank of the covariance matrix of the channel input vector and by allowing temporal coding across multiple channel uses, we show that the MIMO linear receiver can achieve a much better DMT performance than the currently known one. Explicit optimal code constructions are provided, along with simulation results, to justify the above findings. For the case of (2 × 2) and (3 × 3) MIMO linear receivers, simulation results show that the newly proposed codes provide significant gains of 10 and 12.08 dB in Eb/N0 at bit error rate 10-4 compared to the conventional schemes, respectively.

[1]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[2]  Xiaoli Ma,et al.  Performance analysis for MIMO systems with lattice-reduction aided linear equalization , 2008, IEEE Transactions on Communications.

[3]  Kai-Kit Wong,et al.  On the decoding order of MIMO maximum-likelihood sphere decoder: linear and non-linear receivers , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[4]  Eduard Axel Jorswieck,et al.  Lattice-reduction aided detection: spatial multiplexing versus quasi-orthogonal STBC , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[5]  John M. Cioffi,et al.  Spatio-temporal coding for wireless communication , 1998, IEEE Trans. Commun..

[6]  P. Elia,et al.  Explicit Space–Time Codes Achieving the Diversity–Multiplexing Gain Tradeoff , 2006, IEEE Transactions on Information Theory.

[7]  Eko N. Onggosanusi,et al.  Capacity analysis of frequency-selective MIMO channels with sub-optimal detectors , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[8]  Alexandra Duel-Hallen,et al.  A family of multiuser decision-feedback detectors for asynchronous code-division multiple-access channels , 1995, IEEE Trans. Commun..

[9]  Nam Ik Cho,et al.  Low-Complexity Decoding via Reduced Dimension Maximum-Likelihood Search , 2010, IEEE Transactions on Signal Processing.

[10]  Dirk Wübben,et al.  Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[11]  Jian Yang,et al.  On joint transmitter and receiver optimization for multiple-input-multiple-output (MIMO) transmission systems , 1994, IEEE Trans. Commun..

[12]  Pramod Viswanath,et al.  Approximately universal codes over slow-fading channels , 2005, IEEE Transactions on Information Theory.

[13]  Li Hong,et al.  Bit Error Rate Performance of MIMO MMSE Receivers in Correlated Rayleigh Flat-Fading Channels , 2011, IEEE Transactions on Vehicular Technology.

[14]  Sergio Verdu,et al.  Multiuser Detection , 1998 .

[15]  A. Dembo,et al.  Large Deviation Techniques and Applications. , 1994 .

[16]  Xiaodong Wang,et al.  MIMO antenna selection with lattice-reduction-aided linear receivers , 2004, IEEE Transactions on Vehicular Technology.

[17]  Joakim Jaldén,et al.  DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models , 2009, IEEE Transactions on Information Theory.

[18]  Jinkang Zhu,et al.  Transmit Antenna Selection for Linear Dispersion Codes Based on Linear Receiver , 2006, 2006 IEEE 63rd Vehicular Technology Conference.

[19]  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).

[20]  J. Yang,et al.  Joint transmitter-receiver optimization for multi-input multi-output systems with decision feedback , 1994, IEEE Trans. Inf. Theory.

[21]  P. Vijay Kumar,et al.  Explicit Space–Time Codes Achieving the Diversity–Multiplexing Gain Tradeoff , 2006, IEEE Transactions on Information Theory.

[22]  Jaekwon Kim,et al.  Fixed-Complexity LLL-Based Signal Detection for MIMO Systems , 2013, IEEE Trans. Veh. Technol..

[23]  Babak Hassibi,et al.  High-rate codes that are linear in space and time , 2002, IEEE Trans. Inf. Theory.

[24]  A. Chkeif,et al.  Sphere decoding of space-time codes , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[25]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[26]  M. O. Damen,et al.  A unified framework for tree search decoding: rediscovering the sequential decoder , 2005, SPAWC 2005.

[27]  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).

[28]  Gregory W. Wornell,et al.  Lattice-reduction-aided detectors for MIMO communication systems , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[29]  Amir K. Khandani,et al.  LLLl lattice-basis reduction achieves the maximum diversity in MIMO systems , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[30]  Abu B. Sesay,et al.  Capacity of MIMO OFDM systems in spatially correlated indoor fading channels , 2004 .

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

[32]  J. Akhtar Diversity and spatial-multiplexing tradeoff under linear decoding , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[33]  J. Speidel,et al.  Analytical performance of MIMO MMSE receivers in correlated Rayleigh fading environments , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[34]  Giuseppe Caire,et al.  Asymptotic Performance of Linear Receivers in MIMO Fading Channels , 2008, IEEE Transactions on Information Theory.

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

[36]  Giuseppe Caire,et al.  On maximum-likelihood detection and the search for the closest lattice point , 2003, IEEE Trans. Inf. Theory.

[37]  Giuseppe Caire,et al.  Performance of MMSE MIMO Receivers: A Large N Analysis for Correlated Channels , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

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

[39]  Alexandra Duel-Hallen,et al.  Equalizers for Multiple Input/Multiple Output Channels and PAM Systems with Cyclostationary Input Sequences , 1992, IEEE J. Sel. Areas Commun..

[40]  Don Coppersmith,et al.  Matrix multiplication via arithmetic progressions , 1987, STOC.

[41]  Abu B. Sesay,et al.  Capacity of MIMO OFDM systems in spatially correlated indoor fading channels , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[42]  A. K. Lenstra,et al.  Factoring polynomials with rational coefficients , 1982 .

[43]  Giuseppe Caire,et al.  On Outage Analysis and Code Design for Correlated MIMO Fading Channels , 2007, 2007 IEEE International Symposium on Information Theory.

[44]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[45]  Walaa Hamouda,et al.  BER Performance of MIMO-SM with Zero-Forcing in Spatially Correlated Ricean Fading , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.