Communication Systems

Communication systems are engineered to move information reliably from a source to a destination across a physical medium. That medium might be copper, fiber, or free space, and the information might be audio, video, telemetry, or packetized data. Regardless of application, most systems share the same high-level structure: a transmitter that encodes information into a signal, a channel that distorts and adds noise, and a receiver that recovers the original message as accurately and efficiently as possible.

What differentiates modern communication systems is not the basic block diagram but the tradeoffs they make: bandwidth versus power, robustness versus spectral efficiency, complexity versus cost, and latency versus reliability. Those tradeoffs show up most clearly in modulation choices, channel capacity limits, wireless standards, and the practical accounting of gains and losses in a link budget.

Core building blocks of a communication system

At a minimum, a communication system includes:

• Source and source coding: the original information and optional compression to reduce redundancy.
• Channel coding: redundancy added intentionally for error detection and correction.
• Modulation: mapping bits or analog waveforms to changes in a carrier’s amplitude, frequency, or phase.
• Channel: the path between transmitter and receiver, including attenuation, interference, and noise.
• Demodulation and decoding: signal processing that estimates transmitted symbols and reconstructs the message.

In practice, systems also include synchronization, multiplexing (sharing resources among users), security layers, and networking protocols. But modulation and coding remain the physical core because they determine how well a system survives noise and interference for a given bandwidth and power.

Analog modulation: AM and FM in context

Analog modulation predates digital networking but remains a useful lens for understanding how signals behave.

Amplitude Modulation (AM)

AM encodes information by varying the carrier amplitude. In standard broadcast AM, the transmitted spectrum includes a carrier plus two sidebands. Its main advantages are simplicity and compatibility with straightforward receivers. Its disadvantages are susceptibility to amplitude noise and relatively inefficient use of transmit power because the carrier itself may carry little or no information.

AM also illustrates a general rule: if noise or interference couples primarily as amplitude variation, AM is vulnerable unless additional techniques are used.

Frequency Modulation (FM)

FM encodes information by varying the instantaneous frequency of the carrier. Because the receiver can limit amplitude variations, FM is inherently more resistant to certain noise sources than AM, which historically enabled higher-fidelity audio broadcasting. The tradeoff is bandwidth: FM typically occupies more spectrum than AM for comparable message quality.

AM and FM are not just “old” techniques. They represent two different ways to embed information in a carrier, a theme that continues in digital modulation.

Digital modulation: ASK, FSK, PSK, and QAM

Digital modulation maps discrete symbols (bits or groups of bits) onto a carrier. Compared with analog methods, digital techniques pair naturally with error-correcting codes and allow clearer design targets such as bit error rate (BER) and throughput.

Amplitude Shift Keying (ASK)

ASK varies the carrier amplitude to represent digital symbols. The simplest form is On-Off Keying, where one symbol is a carrier present and the other is absent.

• Strengths: simple transmitter and receiver architectures.
• Weaknesses: sensitive to amplitude noise and fading, which are common in wireless channels.

ASK is more comfortable in channels with stable amplitudes (certain wired or optical intensity-modulated links) than in mobile radio environments.

Frequency Shift Keying (FSK)

FSK represents symbols by shifting the carrier among discrete frequencies. Because information is carried in frequency rather than amplitude, FSK can be more robust in the presence of amplitude variations.

• Strengths: resilience to amplitude noise; can be implemented with noncoherent receivers.
• Weaknesses: can require more bandwidth for a given data rate compared with phase-based schemes.

Many low-power and legacy wireless systems have used FSK variants because of their implementation simplicity and robustness.

Phase Shift Keying (PSK)

PSK encodes symbols in the carrier phase. Common forms include BPSK (2 phases) and QPSK (4 phases). Phase-based modulation is power-efficient in many channels, but it requires good carrier synchronization at the receiver.

• Strengths: good power efficiency; widely used in wireless.
• Weaknesses: more sensitive to phase noise and oscillator impairments; needs accurate synchronization.

Quadrature Amplitude Modulation (QAM)

QAM combines amplitude and phase changes by using two orthogonal components (in-phase and quadrature). Higher-order QAM (such as 16-QAM, 64-QAM, 256-QAM) transmits more bits per symbol, increasing spectral efficiency.

• Strengths: high throughput per unit bandwidth.
• Weaknesses: requires higher signal-to-noise ratio (SNR) to maintain low error rates; more sensitive to nonlinearities and distortion.

A useful intuition is that higher-order QAM packs constellation points closer together. Noise that nudges a received point across a decision boundary causes symbol errors, so the system must compensate with higher SNR, better coding, or both.

Channel capacity and the Shannon limit

A central question in communication engineering is: what is the maximum reliable data rate a channel can support? Shannon’s channel capacity provides a theoretical upper bound for reliable communication in the presence of noise.

For an additive white Gaussian noise (AWGN) channel, the capacity is:

$$C=B{\log }_2(1+\text{SNR})$$

where:

• $C$ is capacity in bits per second,
• $B$ is bandwidth in hertz,
• SNR is the signal-to-noise power ratio (linear, not in dB).

This relationship highlights two levers:

• Increase bandwidth to raise $C$ linearly.
• Increase SNR to raise $C$ logarithmically.

That logarithmic behavior matters in practice. Doubling transmit power does not double capacity; it yields diminishing returns. This is one reason modern wireless systems aggressively use bandwidth (wider channels, carrier aggregation) and advanced signal processing (coding, MIMO) rather than relying solely on higher transmit power.

Shannon capacity is not a design recipe, but it anchors expectations. If a proposed modulation and coding scheme claims performance beyond the Shannon limit for a given $B$ and SNR, the claim is physically inconsistent.

Wireless systems and standards: how theory becomes deployed networks

Wireless standards translate modulation and coding theory into interoperable systems. Although standards differ, most modern ones adapt transmission parameters to channel conditions.

Common design elements include:

• Adaptive modulation and coding (AMC): selecting QPSK versus higher-order QAM and varying coding rates based on measured SNR and error statistics.
• OFDM-based waveforms: dividing bandwidth into many narrow subcarriers to manage multipath and enable flexible resource allocation. (Specific implementations vary by standard.)
• Multiple access and scheduling: allocating time, frequency, and sometimes spatial streams among users.
• Link adaptation feedback: receivers estimate channel quality and report it so the transmitter can choose a sustainable rate.

In a real network, the “best” modulation is situational. A handset at the cell edge may use a robust, lower-order modulation with strong coding, while a device near the base station may use 256-QAM to exploit high SNR and achieve high throughput.

Link budgets: the practical accounting of a communication link

A link budget is an engineering balance sheet that predicts received power and margin. It helps answer whether a link will close at a target data rate and reliability, and it identifies where improvements matter most.

A typical link budget considers:

• Transmit power
• Transmit and receive antenna gains
• Path loss (free-space and additional losses)
• Cable and connector losses
• Receiver noise figure
• Bandwidth-dependent noise power
• Implementation losses (modulator, filters, phase noise, quantization)
• Fade margin for variability due to shadowing and multipath

Noise power is often approximated as $N=kTB$ (with additional receiver noise contributions), meaning wider bandwidth increases noise power linearly. This interacts with Shannon’s formula and with modulation choices: higher bandwidth can increase capacity, but it also raises noise, so the net benefit depends on SNR and receiver design.

A well-built link budget does more than check feasibility. It guides decisions such as whether to add antenna gain, change frequency bands, reduce bandwidth, improve receiver noise figure, or select a more robust modulation and coding mode.

Bringing it together: selecting modulation under real constraints

Communication systems succeed when their physical-layer choices align with channel realities and product constraints:

• If bandwidth is scarce, higher-order QAM can improve spectral efficiency, but only if SNR and linearity support it.
• If power is limited, PSK with strong coding may outperform amplitude-heavy schemes.
• If channels fade and vary quickly, robustness and adaptation matter as much as peak rates.
• If hardware is constrained, simpler modulations (FSK, lower-order PSK) can reduce cost and power consumption, even if they sacrifice throughput.

Ultimately, modern communication systems are an exercise in disciplined compromise. Modulation provides the signaling alphabet, Shannon capacity defines the ceiling, standards define the interoperable rules, and link budgets keep designs honest against the physics of real channels.