Engineering topics

Schlensinger, Adam

Publications and source records attributed to Schlensinger, Adam.

2 records

NASA NTRS2013

Soft Decision Analyzer

The Soft Decision Analyzer (SDA) is an instrument that combines hardware, firmware, and software to perform realtime closed-loop end-to-end statistical analysis of single- or dual- channel serial digital RF communications systems operating in very low signal-to-noise conditions. As an innovation, the unique SDA capabilities allow it to perform analysis of situations where the receiving communication system slips bits due to low signal-to-noise conditions or experiences constellation rotations resulting in channel polarity in versions or channel assignment swaps. SDA s closed-loop detection allows it to instrument a live system and correlate observations with frame, codeword, and packet losses, as well as Quality of Service (QoS) and Quality of Experience (QoE) events. The SDA s abilities are not confined to performing analysis in low signal-to-noise conditions. Its analysis provides in-depth insight of a communication system s receiver performance in a variety of operating conditions. The SDA incorporates two techniques for identifying slips. The first is an examination of content of the received data stream s relation to the transmitted data content and the second is a direct examination of the receiver s recovered clock signals relative to a reference. Both techniques provide benefits in different ways and allow the communication engineer evaluating test results increased confidence and understanding of receiver performance. Direct examination of data contents is performed by two different data techniques, power correlation or a modified Massey correlation, and can be applied to soft decision data widths 1 to 12 bits wide over a correlation depth ranging from 16 to 512 samples. The SDA detects receiver bit slips within a 4 bits window and can handle systems with up to four quadrants (QPSK, SQPSK, and BPSK systems). The SDA continuously monitors correlation results to characterize slips and quadrant change and is capable of performing analysis even when the receiver under test is subjected to conditions where its performance degrades to high error rates (30 percent or beyond). The design incorporates a number of features, such as watchdog triggers that permit the SDA system to recover from large receiver upsets automatically and continue accumulating performance analysis unaided by operator intervention. This accommodates tests that can last in the order of days in order to gain statistical confidence in results and is also useful for capturing snapshots of rare events.

Steele, Glen↗

NASA NTRS2011

Jitter Controller Software

Sinusoidal jitter is produced by simply modulating a clock frequency sinusoidally with a given frequency and amplitude. But this can be expressed as phase jitter, frequency jitter, or cycle-to-cycle jitter, rms or peak, absolute units, or normalized to the base clock frequency. Jitter using other waveforms requires calculating and downloading these waveforms to an arbitrary waveform generator, and helping the user manage relationships among phase jitter crest factor, frequency jitter crest factor, and cycle-to-cycle jitter (CCJ) crest factor. Software was developed for managing these relationships, automatically configuring the generator, and saving test results documentation. Tighter management of clock jitter and jitter sensitivity is required by new codes that further extend the already high performance of space communication links, completely correcting symbol error rates higher than 10 percent, and therefore typically requiring demodulation and symbol synchronization hardware to operating at signal-to-noise ratios of less than one. To accomplish this, greater demands are also made on transmitter performance, and measurement techniques are needed to confirm performance. It was discovered early that sinusoidal jitter can be stepped on a grid such that one can connect points by constant phase jitter, constant frequency jitter, or constant cycle-cycle jitter. The tool automates adherence to a grid while also allowing adjustments off-grid. Also, the jitter can be set by the user on any dimension and the others are calculated. The calculations are all recorded, allowing the data to be rapidly plotted or re-plotted against different interpretations just by changing pointers to columns. A key advantage is taking data on a carefully controlled grid, which allowed a single data set to be post-analyzed many different ways. Another innovation was building a software tool to provide very tight coupling between the generator and the recorded data product, and the operator's worksheet. Together, these allowed the operator to sweep the jitter stimulus quickly along any of three dimensions and focus on the response of the system under test (response was jitter transfer ratio, or performance degradation to the symbol or codeword error rate). Additionally, managing multi-tone and noise waveforms automated a tedious manual process, and provided almost instantaneous decision- making control over test flow. The code was written in LabVIEW, and calls Agilent instrument drivers to write to the generator hardware.

Lansdowne, Chatwin↗