Computer Science – Information Theory
Scientific paper
2008-05-16
Computer Science
Information Theory
45 pages, 3 figures, partially appeared in the International Symp. on Information Theory (ISIT), Toronto, Canada, July 6-11, 2
Scientific paper
In this paper, we propose a partial interference cancellation (PIC) group decoding for linear dispersive space-time block codes (STBC) and a design criterion for the codes to achieve full diversity when the PIC group decoding is used at the receiver. A PIC group decoding decodes the symbols embedded in an STBC by dividing them into several groups and decoding each group separately after a linear PIC operation is implemented. It can be viewed as an intermediate decoding between the maximum likelihood (ML) receiver that decodes all the embedded symbols together, i.e., all the embedded symbols are in a single group, and the zero-forcing (ZF) receiver that decodes all the embedded symbols separately and independently, i.e., each group has and only has one embedded symbol, after the ZF operation is implemented. Our proposed design criterion for the PIC group decoding to achieve full diversity is an intermediate condition between the loosest ML full rank criterion of codewords and the strongest ZF linear independence condition of the column vectors in the equivalent channel matrix. We also propose asymptotically optimal (AO) group decoding algorithm, which is an intermediate decoding between the MMSE decoding algorithm and the ML decoding algorithm. The design criterion for the PIC group decoding applies to the AO group decoding algorithm. It is well-known that the symbol rate for a full rank linear STBC can be full, i.e., n_t for n_t transmit antennas. It has been recently shown that its rate is upper bounded by 1 if a code achieves full diversity with a linear receiver. The intermediate criterion proposed in this paper provides the possibility for codes of rates between n_t and 1 that achieve full diversity with a PIC group decoding. This therefore provides a complexity-performance-rate tradeoff.
Guo Xiaoyong
Xia Xiang-Gen
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