In the area of communication systems, it has recently been discovered that by exploiting the linearity of a communication channel and the lattice structure of a modulation scheme, many signal detection problems can be formulated as a problem of finding a nearest lattice point. Examples of such signal detection problems include multiple-input multiple-output (MIMO) detection and decoding of various classes of space-time codes. Further, it has been shown that the relative degree of freedom provided by such lattice-based approaches in choosing a lattice basis can be a significant factor affecting the quality and efficiency of such approaches. For example, conventional low-complexity and highly sub-optimal MIMO detectors can be modified to provide detection that achieves full diversity without a significant sacrifice in complexity by employing lattice reduction of associated MIMO channel matrices.
However, the process of finding a good lattice basis reduction can be significantly complicated in many conventional lattice-based signal detection approaches as compared to other components of such approaches, such that the lattice reduction complexity of conventional lattice-based signal detection techniques often dominates the overall detection complexity. Moreover, this disparity in complexity generally becomes more significant as the dimension of the associated communication system increases. As a result, difficulties arise in applying conventional signal detection techniques in many communication systems, such as those where an associated channel matrix or related lattice basis undergo frequent changes. Accordingly, there exists a need in the art for lattice-based signal detection techniques that simplify the process of lattice reduction without significantly degrading detection performance.