Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels

Details Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels

2008-02-13

arxiv.org/abs/0802.1785v1

Proceedings of 2008 IEEE International Symposium on Information Theory, pp. 2022-2025, 2008

Computer Science

Information Theory

8 pages, two column, 14 figures, LaTeX2e

Scientific paper

10.1109/ISIT.2008.4595344

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.

Affiliated with

Also associated with

No associations

Rating

Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-676557