Dec 4, 2014 · The main idea of our algorithm is to successively boost the detection by leveraging the hidden sparsity in the residual error of received signal ...

Abstract—In this letter, we propose a novel low-complexity detector for large MIMO systems, which is capable of achieving near-ML performance for low order ...

A novel low-complexity detector for large MIMO systems, which is capable of achieving near-ML performance for low order constellation (such as BPSK, 4-QAM), ...

The main idea of our algorithm is to successively boost the detection by leveraging the hidden sparsity in the residual error of received signal. Specifically, ...

Abstract—Neighborhood search algorithms have been pro- posed for low complexity detection in large/massive multiple- input multiple-output systems.

Mar 18, 2021 · In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems.

In this paper, a Bayesian strategy is investigated for MIMO systems. The main idea of this algorithm is to improve the performance of a detector by finding the ...

Abstract—Sparsity based techniques have been found to be promising for detection in large/massive multiple-input multiple- output (MIMO) systems.

Aug 30, 2017 · We developed a novel blind detection scheme to efficiently exploit the channel sparsity inherent in massive MIMO systems. The proposed blind.

... In [137], a hidden sparsity resulting from the decision feedback equalization has been exploited to iteratively boost the detection with the computational ...