A Radius Choice Algorithm for MIMO Sphere Decoding Based on the Noise Statistics

Although sphere decoding (SD) can significantly reduce the complexity of MIMO maximum likelihood decoding, its complexity is still too high to apply it into practical systems. Because the radius determines the volume of the hyper sphere, choosing a proper radius can be very helpful in further reducing the complexity of SD. In this paper, we propose a new algorithm to determine the radius for SD based on the noise statistics. We first get the radii of the spheres in which the expected numbers of points are some predefined values and then propose our algorithm based on those radii. Through analysis and simulations, we can show that the complexity is reduced significantly without additional computations and performance degradation.

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