JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD B.Tech III Year DIGITAL COMMUNICATIONS Previous Question Paper (November/December - 2018 - R16)

Digital communication systems offer significant technical advantages over analog systems, primarily due to the discrete nature of the signals and the robustness of digital processing. The key advantages are:

• Regeneration of signals: Digital signals can be reconstructed at intermediate repeater stations using regenerative repeaters. This prevents the cumulative buildup of noise and distortion that occurs in analog systems, where amplification also amplifies the noise.
• Error detection and correction: Through the use of channel coding techniques, digital systems can detect and correct errors introduced by the transmission medium, ensuring high fidelity and reliability.
• Ease of multiplexing: Digital data is inherently compatible with Time Division Multiplexing (TDM), allowing for efficient integration of various types of traffic such as voice, video, and data over a single communication link.
• Security and privacy: Digital signals can be easily encrypted using sophisticated algorithms, providing a high level of security and privacy that is difficult to achieve with analog signals.
• Hardware flexibility: Digital communication systems rely heavily on integrated circuits and software-defined processing, which are more compact, reliable, and cost-effective to manufacture compared to complex analog circuitry.
• Storage and processing: Digital information can be stored easily on various media and processed using powerful digital signal processing (DSP) techniques, enabling advanced compression and filtering.

Aliasing is an artifact that occurs during the sampling of a continuous-time signal when the sampling frequency f_s is less than the Nyquist rate (twice the highest frequency component f_m of the signal). This causes high-frequency components to overlap with lower-frequency components in the frequency spectrum, making the original signal impossible to reconstruct accurately. To eliminate aliasing, an anti-aliasing filter (a low-pass filter) must be applied to the signal before sampling to remove all frequency components above f_s/2, and the sampling rate must satisfy the condition:

Aperture effect occurs in practical sampling systems where the sampling pulse has a finite duration τ rather than being an ideal impulse. This results in the signal being averaged over the duration of the pulse, which acts as a low-pass filter on the sampled signal, causing attenuation of higher-frequency components and distortion in the amplitude of the reconstructed signal. To eliminate or minimize the aperture effect, the following methods are used:

• Use narrower sampling pulses: Reducing the pulse width τ relative to the sampling interval T_s minimizes the averaging effect.
• Use aperture correction filters: Implement an equalizer or a post-reconstruction filter with a frequency response that compensates for the sinc-shaped attenuation caused by the finite pulse width.