TY - GEN
T1 - Lattice reduction aided selective spanning with fast enumeration for soft-output MIMO detection
AU - Ahmad, Ubaid
AU - Li, Min
AU - Pollin, Sofie
AU - Desset, Claude
AU - Van Der Perre, Liesbet
AU - Lauwereins, Rudy
PY - 2012
Y1 - 2012
N2 - Lattice Reduction (LR) is a promising technique to improve the performance of linear MIMO detectors. However, LR-aided linear hard output MIMO detection is still far from optimal. Practical systems use soft output information to exploit gains from forward-error-correcting codes to achieve near-optimal performance. In this paper, LR-aided Selective Spanning with Fast Enumeration (LR-SSFE) is proposed as a candidate list generation method for soft output MIMO detection. The proposed algorithm uses heuristics based on simple arithmetic operations, which results in a completely deterministic and regular data flow. Hence, LR-SSFE can be efficiently implemented on a parallel programmable architecture. LR-SSFE is compared to the Fixed Candidates Algorithm (FCA) in terms of performance and complexity, which is another LR-aided candidate list generation method. Under the same performance constraints LR-SSFE has a significantly lower complexity than FCA.
AB - Lattice Reduction (LR) is a promising technique to improve the performance of linear MIMO detectors. However, LR-aided linear hard output MIMO detection is still far from optimal. Practical systems use soft output information to exploit gains from forward-error-correcting codes to achieve near-optimal performance. In this paper, LR-aided Selective Spanning with Fast Enumeration (LR-SSFE) is proposed as a candidate list generation method for soft output MIMO detection. The proposed algorithm uses heuristics based on simple arithmetic operations, which results in a completely deterministic and regular data flow. Hence, LR-SSFE can be efficiently implemented on a parallel programmable architecture. LR-SSFE is compared to the Fixed Candidates Algorithm (FCA) in terms of performance and complexity, which is another LR-aided candidate list generation method. Under the same performance constraints LR-SSFE has a significantly lower complexity than FCA.
UR - http://www.scopus.com/inward/record.url?scp=84869812839&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84869812839
SN - 9781467310680
T3 - European Signal Processing Conference
SP - 51
EP - 55
BT - Proceedings of the 20th European Signal Processing Conference, EUSIPCO 2012
T2 - 20th European Signal Processing Conference, EUSIPCO 2012
Y2 - 27 August 2012 through 31 August 2012
ER -