Iterative Tomographic Solution of Integer Least Squares Problems With Applications to MIMO Detection

Convergence and Density Evolution of a MIMO Detector Based on a Forward–Backward Recursion Over a Ring

“…The translation function given by Gaussian density function in (9) assumes data symbols other than x j and x i are all Gaussian. This assumption, however, is only for pruning edges and to simplify the graphical model as shown in Fig.…”

“…Leaving only two variables, one can construct pair-wise graphical model resulting in a low complexity detection algorithm. As a matter of fact, the edge pruning in [8], [9] and [12], [13] are special case of the channel truncation approach in [18], either in zero-forcing sense or in MMSE sense. Similar to sphere decoding, these detectors are a two stage detector, where the channel is first truncated (pruning edges) to simplify the graph and, then, post-joint detection is performed as a BP over the simplified graphical model.…”

“…This result is consistent with the results in [20] and [21], where it was shown that BP over a graphical model with a single cycle always converges. According to [5] and [6], as well as more recent simulation results in [9] and [13], however, limiting edge degree and keeping graphical model sparse seems to be a must for successful convergence of BP based detection, especially for use of higher order modulation.…”