Two-Stage List Sphere Decoding for Under-Determined Multiple-Input Multiple-Output Systems

A two-stage list sphere decoding (LSD) algorithm is proposed for under-determined multiple-input multiple-output (UD-MIMO) systems that employ N transmit antennas and M<;N receive antennas. The two-stage LSD algorithm exploits the unique structure of UD-MIMO systems by dividing the N detection la...

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Veröffentlicht in:IEEE transactions on wireless communications Jg. 12; H. 12; S. 6476 - 6487
Hauptverfasser: Chen Qian, Jingxian Wu, Zheng, Yahong Rosa, Zhaocheng Wang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.12.2013
Institute of Electrical and Electronics Engineers
Schlagworte:
Antennas
Applied sciences
Coding, codes
Complexity theory
Decoding
depth-first tree search
Exact sciences and technology
Information, signal and communications theory
list sphere decoding (LSD)
Matrix decomposition
Measurement
MIMO
Partitioning algorithms
Radiocommunications
Signal and communications theory
Telecommunications
Telecommunications and information theory
turbo detection
Two-stage LSD algorithm
under-determined multiple-input multiple-output (UD-MIMO)
Vectors
Performance evaluation
MIMO system
turbo detection
Multistage method
Tree algorithm
list sphere decoding (LSD)
Two-stage LSD algorithm
Bit error rate
depth-first tree search
Decoding
Adaptive method
Search algorithm
Degradation
under-determined multiple-input multiple-output (UD-MIMO)
Simulation
Transmitting antenna
Algorithm complexity
Search tree
Receiving antenna
Damaging
ISSN:1536-1276
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Beschreibung
Zusammenfassung:A two-stage list sphere decoding (LSD) algorithm is proposed for under-determined multiple-input multiple-output (UD-MIMO) systems that employ N transmit antennas and M<;N receive antennas. The two-stage LSD algorithm exploits the unique structure of UD-MIMO systems by dividing the N detection layers into two groups. Group 1 contains layers 1 to M that have similar structures as a symmetric MIMO system; while Group 2 contains layers M+1 to N that contribute to the rank deficiency of the channel Gram matrix. Tree search algorithms are used for both groups, but with different search radii. A new method is proposed to adaptively adjust the tree search radius of Group 2 based on the statistical properties of the received signals. The employment of the adaptive tree search can significantly reduce the computation complexity. We also propose a modified channel Gram matrix to combat the rank deficiency problem, and it provides better performance than the generalized Gram matrix used in the Generalized Sphere-Decoding (GSD) algorithm. Simulation results show that the proposed two-stage LSD algorithm can reduce the complexity by one to two orders of magnitude with less than 0.1 dB degradation in the Bit-Error-Rate (BER) performance.
ISSN:1536-1276
DOI:10.1109/TWC.2013.103013.130844