  In the conventional tabu search (TS) detection algorithm for multiple-input
multiple-output (MIMO) systems, the metrics of all neighboring vectors are
computed to determine the best one to move to. This strategy requires high
computational complexity, especially in large MIMO systems with high-order
modulation schemes such as 16- and 64-QAM signaling. This paper proposes a
novel reduced-complexity TS detection algorithm called neighbor-grouped TS
(NG-TS), which divides the neighbors into groups and finds the best neighbor by
using a simplified cost function. Furthermore, based on the complexity analysis
of NG-TS, we propose a channel ordering scheme that further reduces its
complexity. Simulation results show that the proposed NG-TS with channel
ordering can achieve up to 85% complexity reduction with respect to the
conventional TS algorithm with no performance loss in both low- and
higher-order modulation schemes.
