Elements of a Communication System

Every communication system consists of several fundamental building blocks that work in coordination to transfer information from source to destination. Understanding each element's role and characteristics is crucial for designing efficient communication systems.

Complete System Architecture

1. Information Source

The information source generates the message to be communicated. Sources can be classified based on:

Analog Sources

• Human speech: bandwidth 300 Hz – 3.4 kHz
• Music: bandwidth 20 Hz – 20 kHz
• Video: bandwidth up to 6 MHz (standard TV)

Digital Sources

• Computer data: binary sequences
• Sensor readings: quantized measurements
• Text: encoded character sequences

Source Characteristics

2. Source Encoder

The source encoder removes redundancy from the source signal, representing it with fewer bits. This is also called data compression.

Key Functions:

• Removes statistical redundancy
• Reduces required transmission bandwidth
• Improves system efficiency

Mathematical Measure — Entropy:

H(X) = -Σ P(xᵢ) × log₂[P(xᵢ)]

Where P(xᵢ) is the probability of symbol xᵢ.

Examples of source coding:

• Huffman coding
• Lempel-Ziv-Welch (LZW) coding
• Run-length encoding (RLE)

3. Channel Encoder

The channel encoder adds controlled redundancy to combat transmission errors. This is the opposite of source encoding — it intentionally adds extra bits for error detection and correction.

Functions:

• Adds parity bits or check sequences
• Enables error detection at receiver
• Permits error correction without retransmission

Common Channel Codes:

4. Modulator

The modulator shifts the baseband signal to a higher frequency suitable for transmission through the channel.

Why Modulation is Required:

1. Practical antenna size: λ = c/f (lower f means impractically large antennas)
2. Frequency division multiplexing capability
3. Bandwidth management
4. Noise immunity improvement (FM/PM)

Modulation Expression:

s(t) = A_c[1 + m·m(t)] × cos(2πf_c·t) (for AM)

Where:

• A_c = carrier amplitude
• m = modulation index
• m(t) = normalized message signal
• f_c = carrier frequency

5. Transmitter

The transmitter prepares the modulated signal for transmission by:

• Amplifying the signal to required power level
• Filtering to limit bandwidth
• Coupling to antenna or transmission medium

Key Transmitter Parameters:

• Output power (watts/dBm)
• Frequency stability (ppm)
• Spectral purity (spurious emissions)
• Efficiency (DC to RF conversion)

6. Communication Channel

The channel is the physical medium connecting transmitter and receiver. Channels introduce three main impairments:

Channel Impairments

Channel Types

Guided Channels:

• Twisted pair: bandwidth ~100 MHz (Cat 6)
• Coaxial cable: bandwidth ~1 GHz
• Optical fiber: bandwidth ~50 THz

Unguided Channels:

• Radio waves: VLF to EHF bands
• Microwave links: 1–300 GHz
• Infrared: short-range, line of sight
• Free-space optical: point-to-point

7. Receiver

The receiver performs the inverse operations of the transmitter:

Key Receiver Parameters:

• Sensitivity (minimum detectable signal)
• Selectivity (ability to reject adjacent channels)
• Dynamic range (ratio of max to min signal levels)
• Noise figure (added noise by receiver)

8. Channel Decoder and Source Decoder

The channel decoder detects and corrects transmission errors using the redundancy added by the channel encoder. The source decoder then decompresses the signal back to its original form.

Solved Example

Problem: In a digital communication system, a source produces 4 symbols with probabilities P(A)=0.5, P(B)=0.25, P(C)=0.125, P(D)=0.125. Calculate the source entropy and the minimum average bits per symbol.

Solution:

H(X) = -Σ P(xᵢ) × log₂[P(xᵢ)]

H(X) = -(0.5×log₂0.5 + 0.25×log₂0.25 + 0.125×log₂0.125 + 0.125×log₂0.125)

H(X) = -(0.5×(-1) + 0.25×(-2) + 0.125×(-3) + 0.125×(-3))

H(X) = -(−0.5 − 0.5 − 0.375 − 0.375)

H(X) = 1.75 bits/symbol

This means we need at minimum 1.75 bits per symbol on average, compared to 2 bits with fixed-length coding (log₂4 = 2).

Interview Questions

Q1: Distinguish between source coding and channel coding.

Source coding removes redundancy to reduce data rate (compression), while channel coding adds controlled redundancy to enable error detection and correction. They serve opposite purposes but both improve overall system efficiency.

Q2: What is the role of a bandpass filter in a transmitter?

The bandpass filter limits the transmitted signal's bandwidth to prevent interference with adjacent channels, comply with regulatory requirements, and remove out-of-band noise and harmonics generated during modulation and amplification.

Q3: Why is the receiver more complex than the transmitter in most systems?

The receiver must deal with a very weak signal corrupted by noise, requiring high sensitivity and selectivity. It needs frequency conversion (mixing), precise filtering, automatic gain control, synchronization recovery, and error correction — all while maintaining low internal noise.

Q4: What happens if channel encoding is not used?

Without channel encoding, any bit errors introduced by channel noise cannot be detected or corrected. This leads to degraded performance, especially in noisy channels. The only alternative is retransmission (ARQ), which reduces throughput and increases latency.