Orthotope sphere decoding and parallelotope decoding-reduced complexity optimum detection algorithms for MIMO channels

被引:5
作者
Sweatman, Catherine Z. W. Hassell [1 ]
Thompson, John S. [1 ]
机构
[1] Univ Edinburgh, Sch Engn & Elect, Inst Digital Commun, Edinburgh EH9 3JL, Midlothian, Scotland
关键词
wireless; multiple input multiple output (MIMO); receiver processing; sphere decoding;
D O I
10.1016/j.sigpro.2005.08.012
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The complexity of maximum likelihood detection (MLD) in multiple input multiple output (MIMO) systems with N transmit antennas typically grows exponentially with N. This makes MLD too complex to implement, particularly if higher order modulation schemes such as quadrature amplitude modulation are employed. Recently, generalised sphere decoding (GSD) was proposed, which provides the same performance as MLD, but complexity is only a polynomial function of N for small values of N. This is achieved by only considering lattice points that lie within a hypersphere centred at the received signal. Determining which lattice points lie within the sphere requires a complex distance calculation, so this paper investigates an different approach, called parallelotope decoding (PD) or alternatively the Karman strategy. This method fits a parallelotope around the sphere, and simplifies the distance calculation. It turns out that PD performs poorly under certain channel conditions, so a novel hybrid scheme called orthotope sphere decoding is also proposed. This decoder is a hybrid of PD and GSD and is usually the most cost effective of the four optimal algorithms under discussion. Simulation results are presented to compare the performance and complexity of the optimal detectors described in the paper and the sub-optimal V-BLAST algorithm. (C) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:1518 / 1537
页数:20
相关论文
共 47 条
[21]   Algorithm and implementation of the K-best sphere decoding for MIMO detection [J].
Guo, Z ;
Nilsson, P .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2006, 24 (03) :491-503
[22]   Approximate ML detection for MIMO systems using multistage sphere decoding [J].
Cui, T ;
Tellambura, C .
IEEE SIGNAL PROCESSING LETTERS, 2005, 12 (03) :222-225
[23]   Signal Detection for Large MIMO Systems Using Sphere Decoding on FPGAs [J].
Hassan, Mohamed W. ;
Dabah, Adel ;
Ltaief, Hatem ;
Fahmy, Suhaib A. .
2023 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM, IPDPS, 2023, :102-111
[24]   Deep Learning Aided Low Complex Sphere Decoding for MIMO Detection [J].
Liao, Jieyu ;
Zhao, Junhui ;
Gao, Feifei ;
Li, Geoffrey Ye .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2022, 70 (12) :8046-8059
[25]   Circular Sphere Decoding: A Low Complexity Detection for MIMO Systems With General Two-dimensional Signal Constellations [J].
Jang, Hwanchol ;
Nooshabadi, Saeid ;
Kim, Kiseon ;
Lee, Heung-No .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2017, 66 (03) :2085-2098
[26]   Low-Complexity Sphere Decoding of Polar Codes Based on Optimum Path Metric [J].
Niu, Kai ;
Chen, Kai ;
Lin, Jiaru .
IEEE COMMUNICATIONS LETTERS, 2014, 18 (02) :332-335
[27]   New List Sphere Decoding (LSD) and Iterative Synchronization Algorithms for MIMO-OFDM Detection With LDPC FEC [J].
Kora, Ahmed D. ;
Saemi, Amir ;
Cances, Jean Pierre ;
Meghdadi, Vahid .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2008, 57 (06) :3510-3524
[28]   EM algorithm with sphere decoding for joint channel estimation and detection in MIMO systems [J].
Tajalli, H ;
Hajiani, P ;
Shafiee, H .
2005 INTERNATIONAL CONFERENCE ON WIRELESS AND OPTICAL COMMUNICATIONS NETWORKS, 2005, :518-522
[29]   Approaching MIMO channel capacity with soft detection based on hard sphere decoding [J].
Wang, RQ ;
Giannakis, GB .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2006, 54 (04) :587-590
[30]   Reduced-complexity Sphere Decoding Algorithm Based on Adaptive Radius in Each Dimension [J].
Li, Jianping ;
Chen, Si .
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC), 2015, :309-313