Abstract
Abstract in Undetermined
Signal detection algorithms providing likelihood information
for coded spatial-multiplexing multiple-input multipleoutput
(MIMO) wireless communication system pose a critical
design challenge due to their prohibitively high computational
complexity. In this paper, we present a low-complexity soft-output
detection algorithm by adopting four implementation-friendly
algorithm-level improvements to the fixed-complexity sphere
decoder (FSD). More specifically, we introduce a reliabilitydependent
tree expansion approach and an on-demand listsize
reduction scheme for low-cost candidate list generation.
In terms of performance improvement, we apply an early bitflipping
strategy and utilize the l1-norm distance representation.
The algorithm is evaluated by computer simulations performed
over Rayleigh flat fading channels and computational complexity
analysis. Compared to the soft-output K-Best algorithm, the
proposed algorithm saves at least 60% of the computations for
detecting 4 x 4 64-QAM MIMO signal, and at the same time,
provides better detection performance, making it a promising
detection scheme for real-life hardware implementation.
Signal detection algorithms providing likelihood information
for coded spatial-multiplexing multiple-input multipleoutput
(MIMO) wireless communication system pose a critical
design challenge due to their prohibitively high computational
complexity. In this paper, we present a low-complexity soft-output
detection algorithm by adopting four implementation-friendly
algorithm-level improvements to the fixed-complexity sphere
decoder (FSD). More specifically, we introduce a reliabilitydependent
tree expansion approach and an on-demand listsize
reduction scheme for low-cost candidate list generation.
In terms of performance improvement, we apply an early bitflipping
strategy and utilize the l1-norm distance representation.
The algorithm is evaluated by computer simulations performed
over Rayleigh flat fading channels and computational complexity
analysis. Compared to the soft-output K-Best algorithm, the
proposed algorithm saves at least 60% of the computations for
detecting 4 x 4 64-QAM MIMO signal, and at the same time,
provides better detection performance, making it a promising
detection scheme for real-life hardware implementation.
| Original language | English |
|---|---|
| Pages (from-to) | 607-617 |
| Journal | IEEE Transactions on Vehicular Technology |
| Volume | 61 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2012 |
Subject classification (UKÄ)
- Electrical Engineering, Electronic Engineering, Information Engineering
Free keywords
- soft-output
- Terms—Multiple-input multiple-output (MIMO) detection
- spatial-multiplexing (SM)
- log likelihood ratio (LLR)
- fixed-complexity sphere decoder (FSD).