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Dolinar, S.

Publications and source records attributed to Dolinar, S..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Quantum Limits of Space-to-Ground Optical Communications

For a pure loss channel, the ultimate capacity can be achieved with classical coherent states (i.e., ideal laser light): (1) Capacity-achieving receiver (measurement) is yet to be determined. (2) Heterodyne detection approaches the ultimate capacity at high mean photon numbers. (3) Photon-counting approaches the ultimate capacity at low mean photon numbers. A number of current technology limits drive the achievable performance of free-space communication links. Approaching fundamental limits in the bandwidth-limited regime: (1) Heterodyne detection with high-order coherent-state modulation approaches ultimate limits. SOA improvements to laser phase noise, adaptive optics systems for atmospheric transmission would help. (2) High-order intensity modulation and photon-counting can approach heterodyne detection within approximately a factor of 2. This may have advantages over coherent detection in the presence of turbulence. Approaching fundamental limits in the photon-limited regime (1) Low-duty cycle binary coherent-state modulation (OOK, PPM) approaches ultimate limits. SOA improvements to laser extinction ratio, receiver dark noise, jitter, and blocking would help. (2) In some link geometries (near field links) number-state transmission could improve over coherent-state transmission

laser communications↗
NASA NTRS2012

Quantum Limits of Space-to-Ground Optical Communications

Quantum limiting factors contributed by the transmitter, the optical channel, and the receiver of a space-to-ground optical communications link are described. Approaches to move toward the ultimate quantum limit are discussed.

free space optical communications↗
NASA NTRS2004

Science-based Region-of-Interest Image Compression

As the number of currently active space missions increases, so does competition for Deep Space Network (DSN) resources. Even given unbounded DSN time, power and weight constraints onboard the spacecraft limit the maximum possible data transmission rate. These factors highlight a critical need for very effective data compression schemes. Images tend to be the most bandwidth-intensive data, so image compression methods are particularly valuable. In this paper, we describe a method for prioritizing regions in an image based on their scientific value. Using a wavelet compression method that can incorporate priority information, we ensure that the highest priority regions are transmitted with the highest fidelity.

Wagstaff, K. L.↗
NASA NTRS2003

Iterative demodulation and decoding of coded non-square QAM

Simulation results show that, with iterative demodulation and decoding, coded NS-8QAM performs 0.5 dB better than standard 8QAM and 0.7 dB better than 8PSK at BER= 10(sup -5), when the FEC code is the (15, 11) Hamming code concatenated with a rate-1 accumulator code, while coded NS-32QAM performs 0.25 dB better than standard 32QAM.

iterative decoding QAM bit error rate capacity↗
NASA NTRS2001

Improving turbo-like codes using iterative decoder analysis

The density evolution method is used to analyze the performance and optimize the structure of parallel and serial turbo codes, and generalized serial concatenations of mixtures of different outer and inner codes. Design examples are given for mixture codes.

turbo codes iterative decoding↗
NASA NTRS2001

Capacity and capacity sensitivity of soft output optical channels

In this paper, we derive the capacity of pulse position modulation (PPM) on a general soft output, memoryless channel, and evaluate the capacity formula for a variety of optical channel models, including AWGN, webb (1), and Webb plus Gaussian distributions.

capacity↗
NASA NTRS2000

Capacity of PPM on APD-Detected Optical Channels

This report defines the fundamental parameters affecting the capacity of a soft-decision optical channel, and relates them to corresponding parameters for the well-understood AWGN channel.

AWGN PPM APD-Detected Optical Channels↗
NASA NTRS2000

Low Complexity Turbo-like Codes

This paper addresses the iterative devoding analysis, design, and performance of low complexity turbo like codes.

turbo-like codes iterative decoding analysis conca↗
NASA NTRS2000

Capacity of Pulse-Position Modulation (PPM) on Gaussian and Webb Channels

This article computes the capacity of various idealized soft-decision channels modeling an optical channel using an avalanche photodiode detector (APD) and pulse-position modulation (PPM). The capacity of this optical channel depends in a complicated way on the physical parameters of the APD and the constraints imposed by the PPM orthogonal signaling set. This article attempts to identify and separate the effects of several fundamental parameters on the capacity of the APD-detected optical PPM channel. First, an overall signal-to-noise ratio (SNR) parameter is de ned such that the capacity as a function of a bit-normalized version of this SNR drops precipitously toward zero at quasi-brick-wall limits on bit SNR that are numerically the same as the well-understood brick-wall limits for the standard additive white Gaussian noise (AWGN) channel. A second parameter is used to quantify the effects on capacity of one unique facet of the optical PPM channel (as compared with the standard AWGN channel) that causes the noise variance to be higher in signal slots than in nonsignal slots. This nonuniform noise variance yields interesting capacity effects even when the channel model is AWGN. A third parameter is used to measure the effects on capacity of the difference between an AWGN model and a non-Gaussian model proposed by Webb (see reference in [2]) for approximating the statistics of the APD-detected optical channel. Finally, a fourth parameter is used to quantify the blending of a Webb model with a pure AWGN model to account for thermal noise. Numerical results show that the capacity of M-ary orthogonal signaling on the Webb channel exhibits the same brick-wall Shannon limit, (M ln 2)=(M 1), as on the AWGN channel ( 1:59 dB for large M). Results also compare the capacity obtained by hard- and soft-output channels and indicate that soft-output channels o er a 3-dB advantage.

Dolinar, S.↗
NASA NTRS2000

Capacity of PPM on Gaussian and Webb Channels

This paper computes and compares the capacities of M-ary PPM on various idealized channels that approximate the optical communication channel: (1) the standard additive white Gaussian noise (AWGN) channel;(2) a more general AWGN channel (AWGN2) allowing different variances in signal and noise slots;(3) a Webb-distributed channel (Webb2);(4) a Webb+Gaussian channel, modeling Gaussian thermal noise added to Webb-distributed channel outputs.

Capacity PPM Webb Optical↗