Reduced-Complexity Lattice Spherical Decoding

Lattice sequential decoders based on a spherical search region, such as the Sphere Decoder and the SB-Stack decoder, implement a tree-search strategy to find the ML solution while visiting only the lattice points that belong to a sphere of a predefined radius. Their computational complexity depends then critically on the choice of the initial sphere radius. We propose in this work novel initial sphere radius selection methods for spherical-region based sequential lattice decoders and show through simulations the complexity reduction allowed by such methods when the Sphere Decoder is used while maintaining ML performance.