On the Rate Versus ML-Decoding Complexity Tradeoff of Square LDSTBCs with Unitary Weight Matrices
ABSTRACT The low decoding complexity structure of Linear Dispersion Space Time Block Codes (LDSTBCs) with unitary weight matrices is analyzed. It is shown that given n = 2alpha, the maximum number of groups in which the information symbols can be separated and decoded independently is (2a + 2), and as we lower the number of different groups to (2k + 2), 0 les k les alpha, we get higher rate codes. We also find the analytic expression for rates that such codes can achieve for any chosen group number, thus completely characterizing the rate-ML-decoding-complexity tradeoff for this class of codes. The proof of the result also includes a method for constructing such optimal rate achieving codes. Interestingly, this analysis produces some low decoding complexity codes with rate greater than one.
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ABSTRACT: We construct a class of linear space-time block codes for any number of transmit antennas that have controllable ML decoding complexity with a maximum rate of 1 symbol per channel use. The decoding complexity for M transmit antennas can be varied from ML decoding of 2<sup>[log2 M]-1</sup> symbols together to single symbol ML decoding. For ML decoding of 2<sup>[log2 M]-n</sup> (n = 1,2,...) symbols together, a diversity of min (M, 2<sup>[log2 M]-n+1</sup>) can be achieved. Numerical results show that the performance of the constructed code when 2<sup>[log2 M]-1</sup> symbols are decoded together is quite close to the performance of ideal rate-1 orthogonal codes (that are non-existent for more than 2 transmit antennas).Information Theory, 2007. ISIT 2007. IEEE International Symposium on; 07/2007
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ABSTRACT: Space-time block codes for providing transmit diversity in wireless communication systems are considered. Based on the principles of linearity and unitarity, a complete classification of linear codes is given in the case when the symbol constellations are complex, and the code is based on a square matrix or restriction of such by deleting columns (antennas). Maximal rate delay optimal codes are constructed within this category. The maximal rates allowed by linearity and unitarity fall off exponentially with the number of transmit antennasIEEE Transactions on Information Theory 03/2002; · 2.62 Impact Factor
- IEEE Transactions on Information Theory - TIT. 01/2006;