scholarly journals MIMO Detectors Under Correlated Channels

2016 ◽  
Vol 37 (1) ◽  
pp. 3
Author(s):  
Bruno Felipe Costa ◽  
Alex Miyamoto Mussi ◽  
Taufik Abrão
Keyword(s):  
Maximum Likelihood ◽  
Interference Cancellation ◽  
Mean Squared Error ◽  
Multiple Input Multiple Output ◽  
Successive Interference Cancellation ◽  
Correlated Channels ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Multiple Input ◽  
Input Multiple Output

Este artigo analisa o desempenho de detectores com múltiplas antenas transmissoras e múltiplas antenas receptoras (MIMO – multiple-input multiple-output) em canais com desvanecimento correlacionados. Dois esquemas de detecção MIMO denominados erro quadrático médio mínimo (MMSE – minimum mean squared error) – com ou sem a etapa de cancelamento de interferência sucessiva ordenado (OSIC – ordered successive interference cancellation) – e técnica de redução treliça (LR – lattice reduction) são analisados e comparados com o limite de detecção de máxima verossimilhança (ML – maximum likelihood) em cenários específicos de interesse: (a) com incremento da eficiência espectral através do aumento do número de antenas. (b) quando há aumento nos índices de correlação de desvanecimento do canal. Neste contexto, o desempenho do detector ótimo ML-MIMO é utilizado como referência visando caracterizar o comportamento da taxa de erro de bit (BER) destes detectores MIMO e quão próximo esses estão do desempenho ML-MIMO.

scholarly journals Iterative successive MMSE multi-user MIMO transmit filtering

2007 ◽  
Vol 20 (1) ◽  
pp. 45-55
Author(s):  
Veljko Stankovic
Keyword(s):  
Interference Cancellation ◽  
Mean Squared Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mimo Channel ◽  
Practical Implementation ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output ◽  
Order Of Magnitude ◽  
Value Decomposition

In this paper we introduce a novel linear preceding technique. It was previously reported in the literature that when the user terminals are equipped with one antenna, minimum mean-squared-error (MMSE) in combination with successive interference cancellation is optimum on the uplink, while MMSE preceding in combination with Tomlinson-Harashima preceding (THP) is optimum on the downlink. The linear preceding technique introduced in this paper is based on the modified MSB criterion. It can serve the users that are equipped with arbitrary number of antennas with only limitation that the total number of users in the system has to be less than or equal to the rank of the combined multiple-input multiple-output (MIMO) channel matrix of all users. It was shown in the simulations that it extracts very high diversity gain and at low signal-to-noise ratios, when the total number of antennas at the user terminals is greater than the number of antennas at the base station, it approaches the maximum sum rate capacity of the broadcast channel. The technique introduced in this paper is favorable for practical implementation since it requires by an order of magnitude less operations than the techniques based on the singular value decomposition.

scholarly journals Location-Aided Uplink Transmission for User-Centric Cell-Free Massive MIMO Systems: A Fairness Priority Perspective

2022 ◽  
Author(s):  
Chen Wei ◽  
Kui Xu ◽  
Zhexian Shen ◽  
Xiaochen Xia ◽  
Wei Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Estimation Accuracy ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output ◽  
User Centric ◽  
Assignment Scheme

Abstract In this paper, we investigate the uplink transmission for user-centric cell-free massive multiple-input multiple-output (MIMO) systems. The largest-large-scale-fading-based access point (AP) selection method is adopted to achieve a user-centric operation. Under this user-centric framework, we propose a novel inter-cluster interference-based (IC-IB) pilot assignment scheme to alleviate pilot contamination. Considering the local characteristics of channel estimates and statistics, we propose a location-aided distributed uplink combining scheme based on a novel proposed metric representing inter-user interference to balance the relationship among the spectral efficiency (SE), user equipment (UE) fairness and complexity, in which the normalized local partial minimum mean-squared error (LP-MMSE) combining is adopted for some APs, while the normalized maximum ratio (MR) combining is adopted for the remaining APs. A new closed-form SE expression using the normalized MR combining is derived and a novel metric to indicate the UE fairness is also proposed. Moreover, the max-min fairness (MMF) power control algorithm is utilized to further ensure uniformly good service to the UEs. Simulation results demonstrate that the channel estimation accuracy of our proposed IC-IB pilot assignment scheme outperforms that of the conventional pilot assignment schemes. Furthermore, although the proposed location-aided uplink combining scheme is not always the best in terms of the per-UE SE, it can provide the more fairness among UEs and can achieve a good trade-off between the average SE and computational complexity.

scholarly journals Decentralized Limited-Feedback Multiuser MIMO for Temporally Correlated Channels

2010 ◽  
Vol 2010 ◽  
pp. 1-9
Author(s):  
Eduardo Zacarías B ◽  
Stefan Werner ◽  
Risto Wichman
Keyword(s):  
Multiple Input Multiple Output ◽  
Limited Feedback ◽  
Mimo Channels ◽  
Linear Filters ◽  
Correlated Channels ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Channel Information ◽  
Feedback Algorithm ◽  
Temporally Correlated

This paper proposes a novel multiuser (MU) multiplexing scheme for temporally correlated multiple-input, multiple-output (MIMO) channels, suitable for systems employing low-rate feedback links. A decentralized solution is obtained by the mobile receivers, which employ interference rejection combiner (IRC) linear filters and command the update of the corresponding per-user antenna transmit weights through compact feedback messages, thus avoiding explicit transmission of channel information. The proposed limited-feedback algorithm outperforms existing MU-MIMO solutions employing quantized matrices, operating at the same feedback overhead. A compensation mechanism is presented, which enables the proposed solution to operate under moderate probabilities of feedback errors, at the expense of a small downlink overhead.

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