From Sphere to Sequential Decoding

摘要

A general framework for sphere and sequential decoding is given and analyzed. We restrict ourselves to the transmission of lattice codes over linear Gaussian channels and formulate the joint detection and decoding problem as a closest lattice point search (CLPS) where a tree search framework for solving the CLPS is adopted. The CLPS algorithm is decomposed into the preprocessing and tree search stages. The role of the preprocessing stage is to expose the tree structure in a form matched to the search stage. We argue that the minimum mean square error decision feedback (MMSE-DFE) frontend is instrumental for solving the joint detection and decoding problem in a single search stage. It is further shown that MMSE-DFE filtering allows for using lattice reduction methods to reduce complexity, at the expense of a marginal performance loss, and solving under-determined linear systems. For the search stage, we present a generic method, based on the branch and bound (BB) algorithm, and show that it encompasses all existing sphere decoders as special cases.