Computationally efficient near-optimal combined antenna selection algorithms for V-BLAST systems

2013 ◽  
Vol 23 (1) ◽  
pp. 375-381 ◽  
Author(s):  
Chiao-En Chen ◽  
Wei-Ho Chung
Keyword(s):  
Antenna Selection ◽  
Computationally Efficient ◽  
Selection Algorithms

Antenna Selection Algorithms in Correlated Fading MIMO Channels

2006 ◽  
Author(s):  
M. I. As-Saafani ◽  
Sultan J. Sadi ◽  
Ehab F. Badran ◽  
Darwish A. E. Mohamed ◽  
Shawki Shaaban
Keyword(s):  
Antenna Selection ◽  
Mimo Channels ◽  
Correlated Fading ◽  
Selection Algorithms

A THEORETICAL ANALYSIS OF THE SELECTION OF DIFFERENTIALLY EXPRESSED GENES

2005 ◽  
Vol 03 (03) ◽  
pp. 627-643 ◽  
Author(s):  
SACH MUKHERJEE ◽  
STEPHEN J. ROBERTS
Keyword(s):  
Theoretical Analysis ◽  
Differentially Expressed Genes ◽  
Gene Selection ◽  
Small Sample ◽  
Ranking Function ◽  
Differentially Expressed ◽  
Computationally Efficient ◽  
Small Sample Sizes ◽  
Selection Algorithms ◽  
Selection Of

A great deal of recent research has focused on the challenging task of selecting differentially expressed genes from microarray data ("gene selection"). Numerous gene selection algorithms have been proposed in the literature, but it is often unclear exactly how these algorithms respond to conditions like small sample sizes or differing variances. Choosing an appropriate algorithm can therefore be difficult in many cases. In this paper we propose a theoretical analysis of gene selection, in which the probability of successfully selecting differentially expressed genes, using a given ranking function, is explicitly calculated in terms of population parameters. The theory developed is applicable to any ranking function which has a known sampling distribution, or one which can be approximated analytically. In contrast to methods based on simulation, the approach presented here is computationally efficient and can be used to examine the behavior of gene selection algorithms under a wide variety of conditions, even when the number of genes involved runs into the tens of thousands. The utility of our approach is illustrated by comparing three widely-used gene selection methods.

scholarly journals A Novel Transmit Antenna Selection Algorithms to Improve Energy and Spectral Efficiency

2019 ◽  
Vol 9 (2S3) ◽  
pp. 298-301
Keyword(s):  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Transmit Antenna Selection ◽  
Noise Interference ◽  
Efficiency Performance ◽  
Selection Algorithms ◽  
Mimo Technology ◽  
Selection Of

In massive MIMO systems, the selection of optimal transmits antennas remains as a major constraint. As the number of antennas is increased, the power or energy consumption also increases. Selection of optimal transmit antennas is considered as a multi objective problem, where the energy has to be minimizedand the spectral efficiency (bandwidth) has to be increased. In fact, for attaining higher bandwidth, more transmit antennas have to be selected, which leads to increase in power consumption, In this proposal various papers are reviewed for Energy and Spectral Efficiency performance in Massive MIMO Technology through different algorithms and parameter comparisons are made to identify the better algorithms in terms of EE and SE to achieve the higher data transmission rates, BER, mitigating the inter Noise interference.

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