Paper Info
Title
Near-Capacity Performance Soft Output Sphere Decoding Based On Short List Detection And Metrics Combining
Abstract
We introduce a low complexity iterative soft output sphere decoding algorithm for coded transmissions over multiple antenna channels. Before the iterative detection and decoding starts, a modified hard decision sphere decoder produces a short (base) list of vectors with maximum likelihood metrics. In subsequent iterative soft detections, two competing lists with a small number of vectors are further generated for each coded bit, by utilizing the base list vectors and a priori information from the channel decoder. The corresponding likelihood metrics of the vectors in each competing list are combined to produce soft detection output that approximates the optimal maximum a posteriori (MAP) solution. The performance improves as the base list size increases and a short list (hence a low number of competing vectors) can provide near-capacity performance after a few iterations. Compared with existing methods that adopt the max-log approximation and select only a single best competing vector, the proposed algorithm approaches the optimal performance better with significantly lower complexity requirements.
Year
DOI
Venue
2009
10.1109/CISS.2009.5054776
2009 43RD ANNUAL CONFERENCE ON INFORMATION SCIENCES AND SYSTEMS, VOLS 1 AND 2
Keywords
Field
DocType
sphere decoding, iterative detection
Approximation algorithm,Mathematical optimization,Algorithm design,Computer science,Turbo code,MIMO,Decoding methods,Maximum a posteriori estimation,Self-organizing list,Computational complexity theory
Conference
Citations 
PageRank 
References 
0
0.34
8
Authors
2
Name
Order
Citations
PageRank
Jinhong Wu182.55
Branimir R. Vojcic217014.48