Error recovery properties of quasi-arithmetic codes and soft decoding with length constraint

2006 ◽  
Author(s):  
Simon Malinowski ◽  
Herve Jegou ◽  
Christine Guillemot
Keyword(s):  
Error Recovery ◽  
Soft Decoding ◽  
Length Constraint ◽  
Arithmetic Codes

scholarly journals Error Recovery Properties and Soft Decoding of Quasi-Arithmetic Codes

2007 ◽  
Vol 2008 (1) ◽  
Author(s):  
Simon Malinowski ◽  
Hervé Jégou ◽  
Christine Guillemot
Keyword(s):  
Error Recovery ◽  
Soft Decoding ◽  
Arithmetic Codes

scholarly journals Deleted DOI: Error Recovery Properties and Soft Decoding of Quasi-Arithmetic Codes

2008 ◽  
Vol 2008 ◽  
pp. 1-13 ◽  
Author(s):  
Simon Malinowski ◽  
Hervé Jégou ◽  
Christine Guillemot
Keyword(s):  
Error Recovery ◽  
Soft Decoding ◽  
Arithmetic Codes

Soft Decoding of Integer Codes and Their Application to Coded Modulation

2010 ◽  
Vol E93-A (7) ◽  
pp. 1363-1370 ◽  
Author(s):  
Hristo KOSTADINOV ◽  
Hiroyoshi MORITA ◽  
Noboru IIJIMA ◽  
A. J. HAN VINCK ◽  
Nikolai MANEV
Keyword(s):  
Coded Modulation ◽  
Soft Decoding ◽  
Integer Codes

scholarly journals Efficient Estimation of CFO-Affected OFDM BER Floor in Small Cells with Resource-Limited IoT End-Points

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3747
Author(s):  
Adriana Lipovac ◽  
Vlatko Lipovac ◽  
Borivoj Modlic
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Carrier Frequency Offset ◽  
Signal To Noise Ratio ◽  
Low Cost ◽  
Error Recovery ◽  
Efficient Estimation ◽  
Analytical Models ◽  
Small Cells ◽  
End Points ◽  
Power Delay Profile

Contemporary wireless networks dramatically enhance data rates and latency to become a key enabler of massive communication among various low-cost devices of limited computational power, standardized by the Long-Term Evolution (LTE) downscaled derivations LTE-M or narrowband Internet of Things (NB IoT), in particular. Specifically, assessment of the physical-layer transmission performance is important for higher-layer protocols determining the extent of the potential error recovery escalation upwards the protocol stack. Thereby, it is needed that the end-points of low processing capacity most efficiently estimate the residual bit error rate (BER) solely determined by the main orthogonal frequency-division multiplexing (OFDM) impairment–carrier frequency offset (CFO), specifically in small cells, where the signal-to-noise ratio is large enough, as well as the OFDM symbol cyclic prefix, preventing inter-symbol interference. However, in contrast to earlier analytical models with computationally demanding estimation of BER from the phase deviation caused by CFO, in this paper, after identifying the optimal sample instant in a power delay profile, we abstract the CFO by equivalent time dispersion (i.e., by additional spreading of the power delay profile that would produce the same BER degradation as the CFO). The proposed BER estimation is verified by means of the industry-standard LTE software simulator.

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