A tabular parsing algorithm with error recovery

1995 ◽  
Author(s):  
Frank Hadlock
Keyword(s):  
Error Recovery ◽  
Parsing Algorithm

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.

Programmed error recovery for APLSV

1976 ◽  
Vol 7 (3) ◽  
pp. 7-11 ◽  
Author(s):  
Richard Grossman
Keyword(s):  
Error Recovery

scholarly journals PHY, MAC, and RLC Layer Based Estimation of Optimal Cyclic Prefix Length

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4796
Author(s):  
Adriana Lipovac ◽  
Vlatko Lipovac ◽  
Borivoj Modlic
Keyword(s):  
Error Recovery ◽  
Cyclic Prefix ◽  
Closed Form Expression ◽  
Delay Spread ◽  
Radio Link ◽  
Medium Access ◽  
Power Delay Profile ◽  
Rms Delay Spread ◽  
Industry Standard ◽  
New Radio

This work is motivated by growing evidence that the standard Cyclic Prefix (CP) length, adopted in the Long Term Evolution (LTE) physical layer (PHY) specifications, is oversized in propagation environments ranging from indoor to typical urban. Although this ostensibly seems to be addressed by 5G New Radio (NR) numerology, its scalable CP length reduction is proportionally tracked by the OFDM symbol length, which preserves the relative CP overhead of LTE. Furthermore, some simple means to optimize fixed or introduce adaptive CP length arose from either simulations or models taking into account only the bit-oriented PHY transmission performance. On the contrary, in the novel crosslayer analytical model proposed here, the closed-form expression for the optimal CP length is derived such as to minimize the effective average codeblock length, by also considering the error recovery retransmissions through the layers above PHY—the Medium Access Control (MAC) and the Radio Link Control (RLC), in particular. It turns out that, for given protective coding, the optimal CP length is determined by the appropriate rms delay spread of the channel power delay profile part remaining outside the CP span. The optimal CP length values are found to be significantly lower than the corresponding industry-standard ones, which unveils the potential for improving the net throughput.

An exception-based mechanism for syntactic error recovery

1984 ◽  
Vol 19 (11) ◽  
pp. 42-51
Author(s):  
Thomas N. Turba
Keyword(s):  
Error Recovery
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