Sphere decoding algorithms with improved radius search

This work first identifies the most efficient version of the sphere decoding algorithms (SDA) We then develop a novel SDA based on an improved increasing radius search (IIRS), which essentially achieves maximum likelihood (ML) error performance with considerable complexity reduction and provides both design intuition and analytical parameter specification. A probabilistic trimming approach, which exploits both channel realizations and the noise distribution is also introduced. Simulations confirm our claims on both the IIRS and the probabilistic trimming aspects.