Title
A Geometrical Approach for Highly Efficient Soft Demodulation of Rotated Constellations
Abstract
Rotated constellations have shown promising potentials for harsh channel conditions and it becomes an crucial feature of DVB-T2. Several other standards, such as new generations of ATSC and DTMB, are also considering it. How-ever, the superiority of performance comes at the cost of orders of magnitudes higher complexity for demodulation, which is a crucial part of the receiver. Constellations of conventional QAM modulations stay on completely regular integer points, so that the demodulation can be as simple as quantization and table lookup. However, the rotation and independent transmissions of I/Q branches break the above properties, so that soft demodulation becomes much more complex. Previous efficient solutions are mostly based on reduced search instead of performing a full search. We take a totally different approach that derives closest constellation points with geometrical transformations. Search is completely avoided. This results in orders of magnitudes of complexity reduction.
Year
DOI
Venue
2012
10.1109/SiPS.2012.63
SiPS
Keywords
Field
DocType
qam modulation,demodulation,rotated constellations,diversity reception,atsc,dtmb,geometrical transformation,full search,closest constellation point,rotated constellation,geometrical approach,q branch,soft demodulation,quadrature amplitude modulation,digital video broadcasting,dvb-t2,highly efficient soft demodulation,crucial part,magnitudes higher complexity,crucial feature,reduced search,complexity reduction
Quadrature modulation,Demodulation,Telecommunications,Quadrature amplitude modulation,Computer science,Parallel computing,QAM,Algorithm,Reduction (complexity),Digital Video Broadcasting,Quantization (signal processing),Modulation (music)
Conference
ISSN
ISBN
Citations 
2162-3562
978-1-4673-2986-6
2
PageRank 
References 
Authors
0.50
3
4
Name
Order
Citations
PageRank
Min Li116023.21
Andre Bourdoux2121.89
Antoine Dejonghe330930.25
Liesbet Van Der Perre41013108.24