Optimized Simple Bounds for Diversity Systems

• Main Authors: Conti, Andrea (Contributor), Gifford, Wesley Michael (Contributor), Win, Moe Z. (Contributor), Chiani, Marco (Author)
• Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers, 2010-03-18T18:49:38Z.
• Subjects: Article
• Online Access: Get fulltext

Diversity techniques play a key role in modern wireless systems, whose design benefits from a clear understanding of how these techniques affect system performance. To this aim we propose a simple class of bounds, whose parameters are optimized, on the symbol error probability (SEP) for detection of arbitrary two-dimensional signaling constellations with diversity in the presence of non-ideal channel estimation. Unlike known bounds, the optimized simple bounds are tight for all signal-to-noise ratios (SNRs) of interest. In addition, these bounds are easily invertible, which enables us to obtain bounds on the symbol error outage (SEO) and SNR penalty. As example applications for digital mobile radio, we consider the SEO in log-normal shadowing and the SNR penalty for both maximal ratio diversity, in the case of unequal branch power profile, and subset diversity, in the case of equal branch power profile, with non-ideal channel estimation. The reported lower and upper bounds are extremely tight, that is, within a fraction of a dB from each other.
United States. Office of Naval Research (Presidential Early Career Award for Scientists and Engineers [PECASE] N00014-09-1-0435)
National Science Foundation (Grants ECCS- 0636519 and ECCS-0901034)
Institute of Advanced Study Natural Science & Technology Fellowship
Startup'08 project funded by the University of Ferrara
FP7 European project OPTIMIX (Grant Agreement 214625)