A low-complexity tree search detection algorithm for superposition modulation
Dapeng Hao, Peter Adam Hoeher · 2012
We present a novel soft-output detection algorithm for superposition modulation. Using a sequential tree search approach with Gaussian approximation (TS-GA) on the unknown layers, the most significant symbols can be identified and used to approximate the marginal posterior probabilities. The detector has low and fixed computational complexity. Simulation results demonstrate that the optimal a posteriori probability (APP) performance can be approached with a small number of symbol candidates.