scholarly journals An Alternative Method to Compute the Bit Error Probability of Modulation Schemes Subject to Nakagami- Fading

2010 ◽  
Vol 2010 (1) ◽  
Author(s):  
Wamberto J. L. Queiroz ◽  
Waslon T. A. Lopes ◽  
Francisco Madeiro ◽  
Marcelo S. Alencar
Keyword(s):  
Error Probability ◽  
Nakagami Fading ◽  
Bit Error Probability ◽  
Alternative Method ◽  
Modulation Schemes

scholarly journals Closed-Form Expression for the Bit Error Probability of the M-QAM for a Channel Subjected to Impulsive Noise and Nakagami Fading

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Hugerles S. Silva ◽  
Marcelo S. Alencar ◽  
Wamberto J. L. Queiroz ◽  
Danilo B. T. Almeida ◽  
Francisco Madeiro
Keyword(s):  
Density Function ◽  
Error Probability ◽  
Channel Model ◽  
Impulsive Noise ◽  
Additive White Gaussian Noise ◽  
Closed Form Expression ◽  
Modulation Scheme ◽  
Nakagami Fading ◽  
Bit Error Probability ◽  
Noise Ratio

In this paper, new exact expressions for evaluating the bit error probability (BEP) of the M-ary quadrature amplitude modulation scheme (M-QAM) for a channel model characterized by double gated additive white Gaussian noise (G2AWGN) and Nakagami fading are presented. The derivation of the BEP is performed considering a method in which the multiplicative fading is transformed in an additive noise R obtained by dividing the received signal by the estimated fading envelope. In addition, the probability density function (PDF) and cumulative density function (CDF) of the random variable R that represents the aforementioned noise are obtained for the G2AWGN. The BEP curves as a function of the signal to permanent noise ratio for several values of the signal to impulsive noise ratio, modulation order, and fading parameters are also presented.

scholarly journals Bit Error Probability for Large Intelligent Surfaces Under Double-Nakagami Fading Channels

2020 ◽  
Vol 1 ◽  
pp. 750-759 ◽  
Author(s):  
Ricardo Coelho Ferreira ◽  
Michelle S. P. Facina ◽  
Felipe A. P. De Figueiredo ◽  
Gustavo Fraidenraich ◽  
Eduardo Rodrigues De Lima
Keyword(s):  
Fading Channels ◽  
Error Probability ◽  
Nakagami Fading ◽  
Bit Error Probability ◽  
Nakagami Fading Channels

Error Probability of MRC in Frequency Selective Nakagami Fading in the Presence of CCI and ACI

2009 ◽  
Vol E92-A (11) ◽  
pp. 2679-2687
Author(s):  
Mohammad Azizur RAHMAN ◽  
Chin-Sean SUM ◽  
Ryuhei FUNADA ◽  
Shigenobu SASAKI ◽  
Tuncer BAYKAS ◽  
...  
Keyword(s):  
Error Probability ◽  
Nakagami Fading ◽  
Frequency Selective

scholarly journals Ratio-based multi-level resistive memory cells

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Miguel Angel Lastras-Montaño ◽  
Osvaldo Del Pozo-Zamudio ◽  
Lev Glebsky ◽  
Meiran Zhao ◽  
Huaqiang Wu ◽  
...  
Keyword(s):  
Error Probability ◽  
Resistance Switching ◽  
Closed Form Expression ◽  
Memory Cells ◽  
Resistive Memory ◽  
Worst Case ◽  
Information Encoding ◽  
Bit Error Probability ◽  
Multi Level ◽  
Switching Devices

AbstractRatio-based encoding has recently been proposed for single-level resistive memory cells, in which the resistance ratio of a pair of resistance-switching devices, rather than the resistance of a single device (i.e. resistance-based encoding), is used for encoding single-bit information, which significantly reduces the bit error probability. Generalizing this concept for multi-level cells, we propose a ratio-based information encoding mechanism and demonstrate its advantages over the resistance-based encoding for designing multi-level memory systems. We derive a closed-form expression for the bit error probability of ratio-based and resistance-based encodings as a function of the number of levels of the memory cell, the variance of the distribution of the resistive states, and the ON/OFF ratio of the resistive device, from which we prove that for a multi-level memory system using resistance-based encoding with bit error probability x, its corresponding bit error probability using ratio-based encoding will be reduced to $$x^2$$ x 2 at the best case and $$x^{\sqrt{2}}$$ x 2 at the worst case. We experimentally validated these findings on multiple resistance-switching devices and show that, compared to the resistance-based encoding on the same resistive devices, our approach achieves up to 3 orders of magnitude lower bit error probability, or alternatively it could reduce the cell’s programming time and programming energy by up 5–10$$\times$$ × , while achieving the same bit error probability.

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