Raptor-Coded Free-Space Optical Communications Experiment

Min Lu; Linyan Liu; Steve Hranilovic

doi:10.1364/JOCN.8.000398

Journal of Optical Communications and Networking
Vol. 8,
Issue 6,
pp. 398-407
(2016)
•https://doi.org/10.1364/JOCN.8.000398

Raptor-Coded Free-Space Optical Communications Experiment

Min Lu, Linyan Liu, and Steve Hranilovic

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Min Lu, Linyan Liu, and Steve Hranilovic, "Raptor-Coded Free-Space Optical Communications Experiment," J. Opt. Commun. Netw. 8, 398-407 (2016)

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Abstract

While free-space optical (FSO) links have many inherent advantages, such as high data rates and license-free operation, they are sensitive to atmospheric conditions. A promising solution to improve the reliability of such communication links is to combine FSO and radio frequency (RF) channels using Raptor codes. This paper presents a first in-field demonstration of real-time Raptor-coded FSO communication over a 1.87 km urban link. This work serves as an important initial step toward field-programmable gate array (FPGA)-based implementation of Raptor-coded hybrid FSO/RF links. The hardware architecture of a Raptor 10 decoder based on a novel resource- and time-efficient matrix inversion algorithm is presented and implemented in an FPGA platform. The receiver is implemented in a pipelined architecture to maximize link utilization. The throughput of the Raptor-coded FSO link is measured both experimentally and numerically under real-life weather conditions for a continuous period of 8 h. Experimental results demonstrate that Raptor-coded FSO links are capable of tracking changes in the channel state to maximize link utilization.

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Implementation^a	# of Slices Versus Matrix Dimensions				# of Clock Cycles
Implementation^a	$5 \times 5$	$10 \times 10$	$20 \times 20$	$50 \times 50$	# of Clock Cycles
Direct [16]	282	1,278	4,729	30,640	$N$ (exactly)
Jasinski et al. [16]	126	385	1,862	11,065	$N$ (exactly)
Bogdanov et al. [15]	54	187	656	4,004	2 $N$ (average) $\sim N^{2}$ (w.c.)^b
This work	52	227	992	6,090	$N$ (b.c.) $\sim 2 N$ (w.c.)^b

Parameter^a	Algorithm	Matrix Dimensions ( $N \times N$ )
Parameter^a	Algorithm	$5 \times 5$	$10 \times 10$	$20 \times 20$	$50 \times 50$
$f_{\max}$ [MHz]	Direct [16]	201.1	136.5	99.5	71.7
	Jasinski et al. [16]	438.0	337.7	186.3	142.9
	Bogdanov et al. [15]^b	n.r.	n.r.	n.r.	n.r.
	This work	771.0	465.1	297.7	135.6
	Direct [16]	24.9	73.3	201.0	697.4
$T_{i}$ [ns]	Jasinski et al. [16]	11.4	29.6	107.4	350.0
	Bogdanov et al. [15]^b	n.r.	n.r.	n.r.	n.r.
Time to invert	This work^c	6.5 (b.c.)	21.5 (b.c.)	67.2 (b.c.)	368.7 (b.c.)
		13.0 (w.c.)	43.0 (w.c.)	134.4 (w.c.)	737.5 (w.c.)

Parameter	Symbol	Value
Number of source symbols	$k$	64
Column size of matrix $A$	$l$	86
Row size of matrix $A$	$m$	102
Symbols size	$T$	32 bits
UDP clock frequency	N/A	31.25 MHz
Decoding clock frequency	CLK	62.5 MHz
Encoding symbol ID	ESI	32 bits
Payload in UDP datagram	N/A	68 bytes

Implementation^a	# of Slices Versus Matrix Dimensions				# of Clock Cycles
Implementation^a	$5 \times 5$	$10 \times 10$	$20 \times 20$	$50 \times 50$	# of Clock Cycles
Direct [16]	282	1,278	4,729	30,640	$N$ (exactly)
Jasinski et al. [16]	126	385	1,862	11,065	$N$ (exactly)
Bogdanov et al. [15]	54	187	656	4,004	2 $N$ (average) $\sim N^{2}$ (w.c.)^b
This work	52	227	992	6,090	$N$ (b.c.) $\sim 2 N$ (w.c.)^b

Parameter^a	Algorithm	Matrix Dimensions ( $N \times N$ )
Parameter^a	Algorithm	$5 \times 5$	$10 \times 10$	$20 \times 20$	$50 \times 50$
$f_{\max}$ [MHz]	Direct [16]	201.1	136.5	99.5	71.7
	Jasinski et al. [16]	438.0	337.7	186.3	142.9
	Bogdanov et al. [15]^b	n.r.	n.r.	n.r.	n.r.
	This work	771.0	465.1	297.7	135.6
	Direct [16]	24.9	73.3	201.0	697.4
$T_{i}$ [ns]	Jasinski et al. [16]	11.4	29.6	107.4	350.0
	Bogdanov et al. [15]^b	n.r.	n.r.	n.r.	n.r.
Time to invert	This work^c	6.5 (b.c.)	21.5 (b.c.)	67.2 (b.c.)	368.7 (b.c.)
		13.0 (w.c.)	43.0 (w.c.)	134.4 (w.c.)	737.5 (w.c.)

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Journal of Optical Communications and Networking