Estimating Downstream Performance And DOCSIS 3.1 Capacity In CAA and DAA Systems (2015)

By Michael Emmendorfer, Brent Arnold, Zoran Maricevic, Frank O'Keeffe, and Venk Mutalik, ARRIS

Recently the most often asked questions by cable operators around the world surround the expectations of their “future” network performance and capacity when using DOCSIS 3.1 technology in CAA (Centralized Access Architecture) and DAA (Distributed Access Architecture) systems. Answering these questions can be complicated because there are so many different factors that must be examined to predict the “future” end-ofline (EoL) performance and resulting DOCSIS 3.1 capacity. Since MSO-to-MSO network architectures can vary widely, and even within a cable operator’s own network architectures may vary, it is important that an understanding of performance impacting factors is identified to effectively predict EoL performance and DOCSIS 3.1 capacity.

            This paper and underlying model will be the first published analysis of its kind,

because it considers both current and future factors that determine end-of-line (EoL) performance, DOCSIS 3.1 capacity and/or CNR margin. The model is a comprehensive analysis based on real-world data of existing systems as well as predicting the performance of future DOCSIS 3.1 systems not yet created, all in an effort to estimate Downstream Performance and DOCSIS 3.1 Capacity in CAA and DAA Systems.

The model and paper identify four core areas impacting EoL performance: 1) Network Element and Configuration Settings, 2) Network Architecture and Topology, 3) Access Architecture (i.e. CAA & DAA), and 4) Network Condition and Performance.

These four areas influence EoL performance and ultimately D3.1 capacity and/or operator margin and will be examined, in detail in this paper. Specifically, the network element configuration settings such as transmitter MER, RF input levels, partial and full D3.1 spectrum loading, spectrum placement, and spectrum utilization of 750 MHz up to 1218 MHz. The network architecture and topology area examines parameters such as distance between facility and node, wavelength count, amplifiers cascade count, and CPE connection point. Access architectures such as CAA using amplitude modulated (AM) optics vs. future DAA using digital optics systems are examined. Network conditions that can degrade the performance and happen at any time and at any segment are also covered.

This paper will unveil for first time:

1) The results of a new model, created by the authors of this paper, that predicts future downstream end-of-line (EoL) performance and DOCSIS 3.1 capacity in CAA and DAA systems.

2) That “all of the following factors” matter in predicting EoL performance including: 1) Network Elements and Configuration Settings, 2) Network Architecture and Topology, 3) CAA and DAA, and 4) Network Condition and Performance.

3) The variance in the maximum downstream EoL amplifier performance and DOCSIS 3.1 modulation possible, when operating CAA using AM optics with different network architectures and configurations.

4) Where CAA and DAA performance are differentiated, as this will be an option available later this decade.

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