Low Complexity Iterative Receiver Design for Sparse Code Multiple Access

Sparse code multiple access (SCMA) is one of the most promising methods among all the non-orthogonal multiple access techniques in the future 5G communication. Compared with some other non-orthogonal multiple access techniques, such as low density signature, SCMA can achieve better performance due to the shaping gain of the SCMA code words. However, despite the sparsity of the code words, the decoding complexity of the current message passing algorithm utilized by SCMA is still prohibitively high. In this paper, by exploring the lattice structure of SCMA code words, we propose a low-complexity decoding algorithm based on list sphere decoding (LSD). The LSD avoids the exhaustive search for all possible hypotheses and only considers signal within a hypersphere. As LSD can be viewed a depth-first tree search algorithm, we further propose several methods to prune the redundancy-visited nodes in order to reduce the size of the search tree. Simulation results show that the proposed algorithm can reduce the decoding complexity substantially while the performance loss compared with the existing algorithm is negligible.

[1]  Brendan J. Frey,et al.  Factor graphs and the sum-product algorithm , 2001, IEEE Trans. Inf. Theory.

[2]  Emanuele Viterbo,et al.  A universal lattice code decoder for fading channels , 1999, IEEE Trans. Inf. Theory.

[3]  Alireza Bayesteh,et al.  SCMA Codebook Design , 2014, 2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall).

[4]  Emanuele Viterbo,et al.  Signal Space Diversity: A Power- and Bandwidth-Efficient Diversity Technique for the Rayleigh Fading Channel , 1998, IEEE Trans. Inf. Theory.

[5]  U. Fincke,et al.  Improved methods for calculating vectors of short length in a lattice , 1985 .

[6]  Yan Chen,et al.  Iterative multiuser receiver in sparse code multiple access systems , 2015, 2015 IEEE International Conference on Communications (ICC).

[7]  Reza Hoshyar,et al.  LDS-OFDM an Efficient Multiple Access Technique , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[8]  Muhammad Ali Imran,et al.  Information Theoretic Analysis of LDS Scheme , 2011, IEEE Communications Letters.

[9]  X. Jin Factor graphs and the Sum-Product Algorithm , 2002 .

[10]  Jaap van de Beek,et al.  Multiple Access with Low-Density Signatures , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[11]  Louay M. A. Jalloul,et al.  Reduced Complexity Soft-Output MIMO Sphere Detectors—Part I: Algorithmic Optimizations , 2014, IEEE Transactions on Signal Processing.

[12]  C. Tellambura,et al.  An efficient generalized sphere decoder for rank-deficient MIMO systems , 2004 .

[13]  Alireza Bayesteh,et al.  Low Complexity Techniques for SCMA Detection , 2015, 2015 IEEE Globecom Workshops (GC Wkshps).

[14]  Wen Chen,et al.  Efficient Compute-and-Forward Network Codes Search for Two-Way Relay Channel , 2012, IEEE Communications Letters.

[15]  Alexander Vardy,et al.  Closest point search in lattices , 2002, IEEE Trans. Inf. Theory.

[16]  Hosein Nikopour,et al.  Sparse code multiple access , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[17]  Pierluigi Salvo Rossi,et al.  A Dominance-Based Soft-Input Soft-Output MIMO Detector With Near-Optimal Performance , 2014, IEEE Transactions on Communications.

[18]  Yan Chen,et al.  Joint codebook assignment and power allocation for SCMA based on capacity with Gaussian input , 2016, 2016 IEEE/CIC International Conference on Communications in China (ICCC).

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

[20]  Stephan ten Brink,et al.  Achieving near-capacity on a multiple-antenna channel , 2003, IEEE Trans. Commun..

[21]  Reza Hoshyar,et al.  Novel Low-Density Signature for Synchronous CDMA Systems Over AWGN Channel , 2008, IEEE Transactions on Signal Processing.

[22]  Babak Hassibi,et al.  On the sphere-decoding algorithm II. Generalizations, second-order statistics, and applications to communications , 2005, IEEE Transactions on Signal Processing.

[23]  Helmut Bölcskei,et al.  Soft–Input Soft–Output Single Tree-Search Sphere Decoding , 2009, IEEE Transactions on Information Theory.

[24]  Pingzhi Fan,et al.  A Fixed Low Complexity Message Pass Algorithm Detector for Up-Link SCMA System , 2015, IEEE Wireless Communications Letters.

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

[26]  Sihai Zhang,et al.  Weighted message passing algorithm for SCMA , 2015, 2015 International Conference on Wireless Communications & Signal Processing (WCSP).

[27]  Claus-Peter Schnorr,et al.  Lattice basis reduction: Improved practical algorithms and solving subset sum problems , 1991, FCT.

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

[29]  Yan Chen,et al.  Sparse code multiple access: An energy efficient uplink approach for 5G wireless systems , 2014, 2014 IEEE Global Communications Conference.

[30]  Brendan J. Frey,et al.  Iterative Decoding of Compound Codes by Probability Propagation in Graphical Models , 1998, IEEE J. Sel. Areas Commun..

[31]  Muhammad Ali Imran,et al.  On Receiver Design for Uplink Low Density Signature OFDM (LDS-OFDM) , 2012, IEEE Transactions on Communications.

[32]  Mohamed Oussama Damen,et al.  Lattice code decoder for space-time codes , 2000, IEEE Communications Letters.

[33]  Babak Hassibi,et al.  On the sphere-decoding algorithm I. Expected complexity , 2005, IEEE Transactions on Signal Processing.

[34]  James F. Blinn,et al.  Floating-point tricks , 1997 .

[35]  Michael E. Pohst,et al.  On the computation of lattice vectors of minimal length, successive minima and reduced bases with applications , 1981, SIGS.

[36]  Wen Chen,et al.  Compute-and-Forward Network Coding Design over Multi-Source Multi-Relay Channels , 2012, IEEE Transactions on Wireless Communications.

[37]  Wen Chen,et al.  A Low Complexity SCMA Decoder Based on List Sphere Decoding , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).