CCNA Voice 640-461- Part 3 historic voice-digital connectivity-part 1

1,865 views
1,780 views

Published on

Historic Voice: Digital Connectivity

Problems with analogue connections

Analog-to-Digital Signal Conversion

0 Comments
3 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
1,865
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
349
Comments
0
Likes
3
Embeds 0
No embeds

No notes for slide

CCNA Voice 640-461- Part 3 historic voice-digital connectivity-part 1

  1. 1. CCNA Voice 640-461Part 3 -Historic Voice: Digital Connectivity- Part 1 www.amir-jafari.com amirjafari17@gmail.com
  2. 2. Historic Voice: Digital Connectivity Problems with analogue connectivity Connecting analogue to digital signal
  3. 3. Problems with analogue connections 1- Distance limitation -An analog electrical signal experiences degradation (signal fading) over long distances. To increase the distance the analog signal could travel, the phone company had to install repeaters to regenerate the signal as it became weak. -Unfortunately, as the analog signal was regenerated, the repeater device was unable to differentiate between the voice traveling over the wire and line noise. Each time the repeater regenerated the voice, it also amplified the line noise. Thus, the more times a phone company regenerated a signal, the more distorted and difficult to understand the signal became.
  4. 4. Problems with analogue connections 2- Wiring requirements The second difficulty encountered with analog connections was the sheer number of wires the phone company had to run to support a large geographical area or a business with a large number of phones. -Because each phone required two wires, the bundles of wire became massive and difficult to maintain -A solution to send multiple calls over a single wire was needed. A digital connection is that solution.
  5. 5. Analog-to-Digital Signal Conversion The steps to convert an analog signal to a digital signal Step Procedure 1 Sample the analog signal regularly. 2 Quantize the sample. 3 Encode the value into an 8-bit digital form. 4 (Optional) Compress the samples to reduce bandwidth.
  6. 6. Analog-to-Digital Signal ConversionBasic Concepts:Frequency: The number of complete cycles of sinusoidal variation per unit time. Unit ofmeasurement of frequency used to be cycles per second and now the unit of measure ishertz (Hz).Amplitude Is the objective measurement of the degree of change (positive or negative)in atmospheric pressure caused by sound wave The amplitude of a sound wave is themaximum amount by which the instantaneous sound pressure differs from the ambientpressure.Wavelength :It is defined as the distance between successive peaks or troughs of asinusoidal wave which is measured in meters (m). Frequency is the number of times per second that a wave cycle (one peak and one trough) repeats at a given amplitude. A is the amplitude and is the wavelength.
  7. 7. Analog-to-Digital Signal ConversionBasic Concepts:Modulation process:- The purpose of a communication system is to deliver a message signal froman information source in recognizable form to a user destination.- To do this, the transmitter modifies the message signal into a form suitable fortransmission over the channel.-This modification is achieved by means of a process known as modulation,which involves varying some parameter of a carrier wave in accordance withthe message signal.- The receiver re-creates the original message signal from a degraded versionof the transmitted signal after propagation through the channel. This re-creationis accomplished by using a process known as demodulation which the reverseof the modulation process used in the transmitter.
  8. 8. Analog-to-Digital Signal Conversion 1- Sampling and the Nyquist Theorem Sampling process: - Through use of the sampling process, an analogue signal is converted into a corresponding sequence of samples that are usually spaced uniformly in time. - It is necessary that we choose the sampling rate properly, so that the sequence of the samples uniquely defines the original analogue signal. - Those samples are then digitized (that is, represented as a series of 1s and 0s). -Then, at the other end of the voice conversation, this digitized signal can be converted back into an analog wave, which the listener can understand.
  9. 9. Analog-to-Digital Signal Conversion -It is important to take appropriate samples per second which allow equipment to accurately reproduce the original signal, without consuming more bandwidth than necessary. -Digital signal technology is based on the premise stated in the Nyquist Theorem: When a signal is instantaneously sampled at the transmitter in regular intervals and has a rate of at least twice the highest channel frequency, then the samples will contain sufficient information to allow an accurate reconstruction of the signal at the receiver.
  10. 10. Analog-to-Digital Signal Conversion - While the human ear can sense sounds from 20 to 20,000 Hz -Speech encompasses sounds from about 200 to 9000 Hz, - The telephone channel was designed to operate at about 300 to 3400 Hz. This economical range carries enough fidelity to allow callers to identify the party at the far end and sense their mood. -Nyquist decided to extend the digitization to 4000 Hz, to capture higher-frequency sounds that the telephone channel may deliver. Therefore, the highest frequency for voice is 4000 Hz, or 8000 samples per second; that is, one sample every 125 microseconds.
  11. 11. Analog-to-Digital Signal Conversion - The telephone channel frequency range (300–3,400 Hz) gives you enough sound quality to identify the remote caller and sense their mood. - The telephone channel frequency range does not send the full spectrum of human voice inflection and lowers the actual quality of the audio. - For example, if you’ve ever listened to talk radio, you can always tell the difference in quality between the radio host and the telephone caller.
  12. 12. Analog-to-Digital Signal Conversion 2- Quantization - The result of the multiple sampling is a pulse amplitude modulation (PAM) wave. - Quantization: Match the PAM signal to a segmented scale. This scale measures the amplitude (height) of the PAM signal and assigns an integer number to define that amplitude which can then be transmitted in binary form.
  13. 13. Analog-to-Digital Signal Conversion The x-axis is time and the y-axis is the voltage value (PAM). The voltage range is divided into 16 segments (0 to 7 positive, and 0 to 7 negative). Each segment is divided into steps. Starting with segment 0, each segment has fewer steps than the previous segment.
  14. 14. Analog-to-Digital Signal Conversion 3- Encode the value into an 8-bit digital form -At this point, the spoken voice has been converted into a series of 1 and 0s. This process is called pulse code modulation(PCM). -There are two PCM methods(G.711 codec): a-law (use in USA, Japan, and Canada) and μ-law (use in countries outside of North America), they use two different ways of encoding - An 8-bit (that is, 1-byte) value represents each sample. - The first bit of the byte determines the polarity (that is, positive or negative) of the sample -The bytes next 3 bits identify the segment -The final 4 bits of the byte specify the step
  15. 15. Analog-to-Digital Signal Conversion - For communication between a μ-law country and an a-law country, the μ-law country must change its signaling to accommodate the a-law country - According to Mr. Nyquist, we need to take 8000 samples per second - Each sample uses 8 bits. - 8000 samples per second * 8 bits per sample = 64,000 bits per second - These calculations show us that we can transmit digitized voice using 64 kbps of bandwidth
  16. 16. Analog-to-Digital Signal Conversion 4- Compress the samples to reduce bandwidth Once our analog waveforms have been digitized, we might want to save WAN bandwidth by compressing these digitized waveforms by encoding them. Early on in the voice digitization years, the powers that be created a measurement system known as a Mean Opinion Score (MOS) to rate the quality of the various voice codecs on a scale of 1-5. The following three common voice compression techniques are standardized: -G.711: Doesnt actually compress the analog waveform. Rather, PCM samples and performs quantization without any compression. - G.729: The process G.729 uses to compress this audio is to send a sound sample once and simply tell the remote device to continue playing that sound for a certain time interval. This is often described as “building a codebook” of the human voice traveling between the two endpoints Using this process, G.729 is able to reduce bandwidth down to 8 kbps for each call; a fairly massive reduction in bandwidth.
  17. 17. Analog-to-Digital Signal Conversion 4- Compress the samples to reduce bandwidth Audio codec Bandwidth and MOS Values - Cisco designed all its IP phones with the ability to code in either G.711 or G.729. - G.711 is the “common ground” between all VoIP devices. For example, if a Cisco IP phone is attempting to communicate with an Avaya IP phone, they may support different compressed codecs, but can at least agree on G.711 when communicating.
  18. 18. Analog-to-Digital Signal Conversion - After the receiving terminal at the far end receives the digital PCM signal, it must convert the PCM signal back into an analog signal. The process of converting digital signals back into analog signals includes the following two processes: • Decoding The received 8-bit word is decoded to recover the number that defines the amplitude of that sample. This information is used to rebuild a PAM signal of the original amplitude. • Filtering: The PAM signal is passed through a filter to reconstruct the original analog wave from its digitally coded counterpart. - Network devices can easily transmit a numeric value any distance a cable can run without any degradation or line noise, which solves the signal degradation issues faced by analog phone connections
  19. 19. Analog-to-Digital Signal Conversion
  20. 20. References Cioara, J., Valentine, M. (2012). CCNA Voice 640-461 Official Cert Guide, Cisco Press, USA Davidson, J., Peters, J., Bhatia, M., Kalidindi, S., Mukherjee, S. (2006). Voice over IP Fundamentals, Second Edition, Cisco Press, USA Froehlich, A. (2010). CCNA Voice Study Guide, Wiley Publishing, Inc., Indianapolis, Indiana Kaza, R., Asadullah, S. (2005). Cisco IP Telephony: Planning, Design, Implementation, Operation, and Optimization, Cisco Press, USA Wallace, K. (2005). Voice over IP First-Step, Cisco Press, USA Wallace, K. (2006). Authorized Self-Study Guide Cisco Voice over IP (CVoice), Cisco Press, USA

×