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Unitary signal constellations for differential space-time modulation with two transmit antennas: parametric codes, optimal designs, and bounds

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2 Author(s)
Xue-Bin Liang ; Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA ; Xiang-Gen Xia

We focus on the design of unitary signal constellations for differential space-time modulation with double transmit antennas. By using the parametric form of a two-by-two unitary matrix, we present a class of unitary space-time codes called parametric codes and show that this class of unitary space-time codes leads to a five-signal constellation with the largest possible diversity product and a 16-signal constellation with the largest known diversity product. Although the parametric code of size 16 is not a group by itself, we show that it is a subset of a group of order 32. Furthermore, the unitary signal constellations of sizes 32, 64, 128, and 256 obtained by taking the subsets of the parametric codes of sizes 37, 75, 135, and 273, respectively, have the largest known diversity products. We also use large diversity sum of unitary space-time signal constellations as another significant property for the signal constellations to have good performance in low-SNR scenarios. The newly introduced unitary space-time codes can lead to signal constellations with sizes of 5 and 9 through 16 that have the largest possible diversity sums. Subsequently, we construct a few sporadic unitary signal constellations with the largest possible diversity product or diversity sum. A four-signal constellation which has both the largest possible diversity product and the largest possible diversity sum and three unitary signal constellations with the largest possible diversity sums for sizes of 6, 7, and 8 are constructed, respectively. Furthermore, by making use of the existing results in sphere packing and spherical codes, we provide several upper and lower bounds on the largest possible diversity product and the largest possible diversity sum that unitary signal constellations of any size can achieve.

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Information Theory, IEEE Transactions on  (Volume:48 ,  Issue: 8 )