scholarly journals Iterative Intercell Interference Cancellation in MIMO Multicell Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhengzhen Zhang ◽  
Chao Dong ◽  
Qian Wan
Keyword(s):  
Interference Cancellation ◽  
Mean Squared Error ◽  
Base Station ◽  
Intercell Interference ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Pilot Allocation ◽  
Receiver Performance ◽  
Multicell Networks

An iterative intercell interference cancellation algorithm is introduced to improve the receiver performance of uplink transmission in multicell networks. At first, the uplink signal detection is performed independently in each cell according to minimum mean squared error (MMSE) criterion. Subsequently, the detection results are applied to reconstruct the transmit signals of different users and cancel their interference to neighboring cells. With the help of reconstruction results, the MMSE detection matrix of each cell is updated. The channel responses of both efficient and interference links are estimated with the help of pilots. The pilot allocation parameter is introduced to indicate the quality of channel estimation. The simulation results indicate that intercell interference can be greatly mitigated by the proposed algorithm with a moderate number of receiver antennas at the base station.

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.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

scholarly journals Attack-resilient minimum mean-squared error estimation

2014 ◽  
Author(s):  
James Weimer ◽  
Nicola Bezzo ◽  
Miroslav Pajic ◽  
Oleg Sokolsky ◽  
Insup Lee
Keyword(s):  
Error Estimation ◽  
Mean Squared Error ◽  
Minimum Mean Squared Error ◽  
Squared Error

scholarly journals Target and Equalizer Design for High-Density Bit-Patterned Media Recording

1970 ◽  
Vol 6 (2) ◽  
pp. 128-135
Author(s):  
Santi Koonkarnkhai ◽  
Phongsak Keeratiwintakorn ◽  
Piya Kovintavewat
Keyword(s):  
Partial Response ◽  
Mean Squared Error ◽  
Bit Patterned Media ◽  
Patterned Media ◽  
Media Noise ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Cross Track ◽  
Partial Response Maximum Likelihood ◽  
Better Than

In bit-patterned media recording (BPMR) channels, the inter-track interference (ITI) is extremely severe at ultra high areal densities, which significantly degrades the system performance. The partial-response maximum-likelihood (PRML) technique that uses an one-dimensional (1D) partial response target might not be able to cope with this severe ITI, especially in the presence of media noise and track mis-registration (TMR). This paper describes the target and equalizer design for highdensity BPMR channels. Specifically, we proposes a two-dimensional (2D) cross-track asymmetric target, based on a minimum mean-squared error (MMSE) approach, to combat media noise and TMR. Results indicate that the proposed 2D target performs better than the previously proposed 2D targets, especially when media noise and TMR is severe.

scholarly journals New robust iterative minimum mean squared error-based interference alignment algorithm

2014 ◽  
Vol 2014 (2) ◽  
pp. 49-50 ◽  
Author(s):  
Sara Teodoro ◽  
Adão Silva ◽  
Rui Dinis ◽  
Daniel Castanheira ◽  
Atílio Gameiro
Keyword(s):  
Mean Squared Error ◽  
Interference Alignment ◽  
Alignment Algorithm ◽  
Minimum Mean Squared Error ◽  
Squared Error
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