This paper presents a low complexity detection technique with near Maximum Likelihood
(ML) performance for large multiple-input multiple-output (MIMO) systems. Large MIMO …

A recently reported result on large/massive multiple-input multiple-output (MIMO) detection
shows the utility of the branch and bound (BB)-based tree search approach for this problem …

Low-complexity near-optimal detection of large multiple-input multiple-output (MIMO) signals
has attracted recent research attention. Recently, it has been shown that certain algorithms …

Neighborhood search algorithms (NSAs) reduce the detection complexity in a multiple-input
multiple-output (MIMO) system equipped with a large number of antennas. These algorithms …

Neighborhood search algorithms such as likelihood ascent search (LAS) and reactive tabu
search (RTS) have been proposed for low complexity detection in multiple-input multiple …

Neighborhood search algorithms have been proposed for low complexity detection in
large/massive multipleinput multiple-output systems. They iteratively search for the vector …

Implementation of a best-first detection algorithm for multiple-input multiple-output (MIMO)
systems requires large amounts of memory especially in large systems with high-order …

Maximum likelihood detection for MIMO systems can be formulated as an integer quadratic
programming problem. In this paper, we introduce depth-first branch and bound algorithm …

In this paper, we investigate the performance of the low-complexity algorithms based on
Likelihood Ascent Search (LAS) and Tabu Search (TS) for detection in MIMO systems with …

The promising massive level MIMO (multipleinput-multiple-output) systems based on
extremely huge antenna collections have turned into a sizzling theme of wireless …