Parallel Sequence Spread Spectrum: Analytical and simulative approach for determination of bit error probability

2016 ◽  
Author(s):  
Lisa Underberg ◽  
Armin Wulf ◽  
Ramona Croonenbroeck ◽  
Wolfgang Endemann ◽  
Rudiger Kays
Keyword(s):  
Spread Spectrum ◽  
Error Probability ◽  
Bit Error Probability

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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