Add to ORKGAbstract – In this paper, a best channel matrix selection scheme (BCMS) is proposed to approximate maximum likelihood (ML) detection for a multiple-input multiple-output system. For a one stage BCMS scheme, one of the transmitted symbols is selected to perform ML detection and the other symbols are detected by zero forcing (ZF). To increase the diversity of the symbols that are detected by ZF, multi-stage BCMS detection scheme is used to further improve the system performance. Simulation results show that the performance of the proposed BCMS scheme can approach that of ML detection with a significant reduction in complexity
Large-scale multiple-input multiple-output (LS-MIMO) technology constitutes a foundation for next ge...
Abstract — This paper proposes a suboptimal maximum like-lihood detection (MLD) algorithm for multip...
Abstract—In this paper, we propose a multiple-input mul-tiple-output (MIMO) receiver algorithm that ...
In this paper, a best channel matrix selection scheme (BCMS) is proposed to approximate maximum like...
In this paper, we propose a simplified Maximum Likelihood (ML) detection scheme for Multiple-Input M...
Abstract — For multiple-input multiple-output (MIMO) sys-tems, the optimum maximum likelihood (ML) d...
The Maximum Likelihood Detector (MLD) offers an optimal bit-error-ratio for an un-coded multiple-inp...
Abstract—Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel...
This paper proposes an improved QR decomposition associated M algorithm for maximum-likelihood detec...
Abstract: Maximum likelihood (ML) detection is an optimal signal detection scheme, which is often di...
In this paper, we propose a low complexity detection scheme for MIMO systems incorporating spatial m...
We propose a new approach to reach a near maximum likelihood (ML) MIMO detection performance with a ...
Abstract—The maximum likelihood (ML) detection for multiple-input multiple-output (MIMO) system achi...
Multiple-input multiple-output (MIMO) has been considered as a promising technique due to the fact t...
Semi-blind joint maximum likelihood (ML) channel estimation and data detection is proposed for multi...
Large-scale multiple-input multiple-output (LS-MIMO) technology constitutes a foundation for next ge...
Abstract — This paper proposes a suboptimal maximum like-lihood detection (MLD) algorithm for multip...
Abstract—In this paper, we propose a multiple-input mul-tiple-output (MIMO) receiver algorithm that ...
In this paper, a best channel matrix selection scheme (BCMS) is proposed to approximate maximum like...
In this paper, we propose a simplified Maximum Likelihood (ML) detection scheme for Multiple-Input M...
Abstract — For multiple-input multiple-output (MIMO) sys-tems, the optimum maximum likelihood (ML) d...
The Maximum Likelihood Detector (MLD) offers an optimal bit-error-ratio for an un-coded multiple-inp...
Abstract—Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel...
This paper proposes an improved QR decomposition associated M algorithm for maximum-likelihood detec...
Abstract: Maximum likelihood (ML) detection is an optimal signal detection scheme, which is often di...
In this paper, we propose a low complexity detection scheme for MIMO systems incorporating spatial m...
We propose a new approach to reach a near maximum likelihood (ML) MIMO detection performance with a ...
Abstract—The maximum likelihood (ML) detection for multiple-input multiple-output (MIMO) system achi...
Multiple-input multiple-output (MIMO) has been considered as a promising technique due to the fact t...
Semi-blind joint maximum likelihood (ML) channel estimation and data detection is proposed for multi...
Large-scale multiple-input multiple-output (LS-MIMO) technology constitutes a foundation for next ge...
Abstract — This paper proposes a suboptimal maximum like-lihood detection (MLD) algorithm for multip...
Abstract—In this paper, we propose a multiple-input mul-tiple-output (MIMO) receiver algorithm that ...