Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels
Atsushi Okawado, Ryutaroh Matsumoto, Tomohiko Uyematsu
2008
2008 IEEE International Symposium on Information Theory
We propose Dijkstra's algorithm with bounded list size after QR decomposition for decreasing the computational complexity of near maximum-likelihood (ML) detection of signals over multiple-input-multiple-output (MIMO) channels. After that, we compare the performances of proposed algorithm, QR decomposition M-algorithm (QRD-MLD), and its improvement. When the list size is set to achieve the almost same symbol error rate (SER) as the QRD-MLD, the proposed algorithm has smaller average computational complexity.
doi:10.1109/isit.2008.4595344
dblp:conf/isit/OkawadoMU08
fatcat:6x37lkbhrfgannwi6bv3chtk3e