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Communication Systems

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Communication systems are engineering systems that enable the transmission of a message generated at a source to a receiver via an appropriate channel and its subsequent reconstruction at the destination. These systems consist of five fundamental components that control the flow of information: source, transmitter, channel, receiver, and destination. In practice, the most tightly controlled segment is the transmitter–channel–receiver trio, as this part directly determines both the physical form of the signal and the reliability of transmission. The message generated at the source is converted into an electrical format using a transducer; it is then subjected to encoding or modulation at the transmitter. As the signal passes through the channel, it is subjected to effects such as attenuation, distortion, and noise. The receiver attempts to recover the original information through demodulation, equalization, and error correction steps. This process is recognized as the information transmission chain, forming the foundation of modern communication.

Theoretical Framework: Shannon–Weaver Model and Systemic Approach

Shannon–Weaver Model

This model, developed by Claude E. Shannon and Warren Weaver, explains communication through five components: source, transmitter, channel, receiver, and destination. Shannon’s “mathematical theory of communication” assumes that a message is an element selected from a set of probabilities. In other words, the receiver reconstructs a corrupted message into its most probable correct form through probabilistic inference. In this sense, the model is a statistical system that examines not the “meaning of the message” but the “reliability of transmission.” Thanks to this theory, the concepts of “amount of information (entropy)” and “redundancy” were defined in communication, establishing a mathematical foundation for communication engineering.

Systemic Approach and the Concept of Observer

Systemic communication theories extend the boundaries drawn by Shannon. According to Dirk Baecker’s systemic theories, communication is not merely the transfer of a signal; it is an interactive process sustained by the system’s internal selections and observational relationships. In this approach, the “channel” represents more than a medium—it embodies the distinction between the system and its environment. Communication is not the transmission of a single message but the dynamic management of the balance between variety and redundancy. Thus, systems are not only oriented toward sending messages but also toward observing their own boundaries; in this sense, communication is a recursive process that continuously reproduces itself.

System Components and Functional Flow

Source

The source converts physical or abstract information into a measurable quantity. For example, speech is converted into an electrical signal via a microphone; an image is transformed into an electrical counterpart of light intensity by camera sensors. The quality of the source determines the signal’s initial SNR value. Weak sources increase the cost of noise correction. Therefore, modern systems employ high-sensitivity transducers such as MEMS microphones or CCD sensors.

Transmitter

The transmitter adapts the incoming message for transmission over the channel. This process includes stages such as amplification, filtering, modulation, and carrier signal generation. For instance, in an AM transmitter, the audio signal is multiplied by a high-frequency carrier to make it transmittable in the frequency domain. In FM systems, the information’s amplitude remains constant while its frequency varies. The transmitter also ensures impedance matching to guarantee maximum power transfer along the channel.

Channel

The channel is the physical medium through which the signal is transmitted: it may be a wire, fiber, atmosphere, or vacuum. Each channel has its own unique transmission losses, bandwidth limitations, and noise sources. For example, optical fiber offers low loss and high data rates but has high installation costs. Radio channels, while economical and wireless, are susceptible to atmospheric noise. Channel selection is determined by the application’s energy requirements, reliability targets, and coverage criteria.

Receiver

The receiver performs the inverse operations of the transmitter. It receives the signal, amplifies it, filters it, demodulates it, and reconstructs the original information. A simple crystal receiver produces only sound, whereas modern radar or satellite receivers employ advanced techniques such as digital signal processing (DSP), forward error correction (FEC), and frequency synthesis. The receiver also minimizes distortions through equalization and noise estimation processes.

Destination

The destination is the final point where the message acquires meaning. This is often a human, but in IoT networks, it may be a sensor, computer, or autonomous machine. For humans, the perception process is linked to auditory and visual systems; for devices, it involves digital analysis and processing logic. The correct operation of the destination is evaluated as the final performance metric of the system’s success.

Channel Characteristics, Distortions, and Performance

Channel distortions are analyzed in three main categories:

Attenuation: Signal power decreases with distance. These losses are measured in decibels (dB). In fiber optic cables, attenuation is approximately 0.2 dB/km, while in copper lines, it can reach 8–10 dB/km. Solutions include placing amplifiers or repeaters.
Distortion: The shape of the signal is altered due to differential attenuation of frequency or phase components. Linear distortions arise from amplitude/phase response irregularities; nonlinear distortions stem from nonlinear responses of circuit elements.
Noise: A random and uncontrolled energy component, it may originate from thermal, cosmic, or industrial sources. Communication quality is typically measured by SNR (Signal to Noise Ratio) or BER (Bit Error Rate).

To mitigate these effects, equalizer circuits, filters, and error correction codes (FEC) are employed.

Modulation, Demodulation, and Pulse Shaping

Baseband signals are not suitable for direct transmission because low-frequency signals attenuate more easily, require larger antennas, and are more prone to interference. Therefore, the signal is superimposed onto a high-frequency carrier. This process is called modulation. AM, FM, and PM are the most common analog modulation types. In digital systems, variations such as ASK, FSK, PSK, and QAM are used.

In digital transmission, data is sent as bit streams. However, to make these streams compatible with the channel’s bandwidth, pulse shaping is required. For example, a raised cosine filter reduces out-of-band spectral leakage and prevents intersymbol interference (ISI). At the receiver, demodulation and symbol decision algorithms recover the data. Adaptive equalizers optimize this process according to changing channel conditions.

Digital transmission steps typically involve converting the bit stream into m-bit symbols via symbol mapping, limiting bandwidth through pulse shaping, aligning spectral support with the channel’s passband, followed by modulation and demodulation at the receiver for recovery. The adaptive equalizer is the fundamental building block of the digital receiver, designed to estimate and compensate for channel distortions.

Data Communication: Line Coding and Transmission Modes

Data communication is the process of transmitting information in digital form. There are two primary transmission methods: serial transmission (sequential sending of bits) and parallel transmission (simultaneous transfer of multiple bits). In serial transmission, asynchronous mode uses start and stop bits; synchronous mode transmits continuous frames.

Line coding (NRZ, RZ, Manchester, etc.) enables the recovery of clock information and controls DC components. Transmission modes are classified as simplex (one-way), half-duplex (two-way but sequential), and full-duplex (simultaneous two-way). Each mode suits different applications: for example, radio communication typically operates in half-duplex mode, while fiber-based networks are full-duplex.

Example Systems and Technological Trends

Microwave Systems

Microwave communication systems operate in the wavelength range of 0.1 mm to 1 m (approximately 300 MHz to 300 GHz) and offer high data-carrying capacity. Although sensitive to atmospheric conditions, their high directivity and wide bandwidth provide advantages for long-distance data transmission. The fundamental operating principle relies on electromagnetic waves emitted from the transmitter station reaching the receiver station via a line-of-sight (LOS) path. Consequently, the LOS between two stations is typically established using antennas mounted on tall towers or mountain peaks.

Modern microwave systems employ parabolic reflector antennas, waveguides, modulators, and multiplexers. These systems play a critical role in backhaul connections between cellular base stations, satellite communications, military radar systems, and telemetry applications. However, disadvantages include complex circuitry, high installation cost, rain attenuation, and LOS dependency. In 5G and 6G infrastructure, microwave technology forms the backbone of “backhaul” networks operating in the E-band (70–80 GHz), enabling high-speed data transmission and low-latency connectivity.

Radio Waves and Broadcasting

Radio waves are the lowest-frequency electromagnetic waves, occupying the wavelength range of 1 mm to 100 km. These waves carry audio, music, or data signals using modulation techniques (AM, FM, PM). In AM (Amplitude Modulation) systems, information is transmitted by varying the amplitude of the carrier signal; in FM (Frequency Modulation) systems, it is transmitted by varying the frequency. FM is more resistant to interference and is therefore widely preferred in modern radio broadcasting.

Because radio waves can reflect off the ionosphere, intercontinental communication is possible, especially using the HF band (3–30 MHz). Today, traditional radio systems are integrated with digital technologies: DAB (Digital Audio Broadcasting), internet radio, satellite-based broadcasting systems, and VLC (Visible Light Communication) provide complementary solutions to classical radio broadcasting. In the future, radio systems are expected to integrate with 5G Broadcast and IP-based data broadcasting.

Wi-Fi (IEEE 802.11)

Wi-Fi is a communication technology based on the IEEE 802.11 standard family for wireless local area networks (WLAN). Operating in the 2.4 GHz and 5 GHz bands, it has evolved through versions such as 802.11n/ac/ax (Wi-Fi 4/5/6). The newer Wi-Fi 6E standard utilizes the 6 GHz band to provide lower latency, higher bandwidth, and support for more simultaneous users. Wi-Fi networks enable devices to connect wirelessly to the internet through multiple access points (APs).

During transmission, the OFDMA (Orthogonal Frequency Division Multiple Access) method ensures efficient use of the frequency spectrum. Additionally, the TWT (Target Wake Time) feature improves energy efficiency by allowing devices to activate only at specified intervals. With the Wi-Fi 7 (802.11be) standard, features such as 320 MHz channel bandwidth, multi-link operation (MLO), and 4096-QAM modulation aim to achieve theoretical speeds up to 40 Gbps. These advancements are making Wi-Fi indispensable in high-data-demand areas such as smart cities, IoT infrastructure, and industrial automation.

Bluetooth

Bluetooth is a short-range wireless communication standard operating over distances of 10–100 meters. It operates in the 2.4 GHz ISM band and uses the FHSS (Frequency Hopping Spread Spectrum) method to hop across 79 different frequency channels 1600 times per second, reducing interference. Classic Bluetooth (BR/EDR) is used for audio and data transfer, while Bluetooth Low Energy (BLE) has become widespread in smartwatches, sensor networks, health monitoring devices, and IoT applications due to its low power consumption. With Bluetooth 5.3, data rates have reached up to 2 Mbps, and range has extended to 200 meters under ideal conditions. With advanced network topologies, devices can form a mesh network to enable multi-hop communication. In the future, Bluetooth is expected to be integrated into 5G-based D2D (Device-to-Device) communication infrastructures to serve as a foundational technology for positioning, object tracking, and smart factory systems.

Infrared (IR)

Infrared systems are wireless communication systems operating in the wavelength range of 700 nm to 1 mm and typically requiring a line-of-sight. Because this technology transmits data using light waves, it is resistant to electromagnetic interference (e.g., Wi-Fi noise). However, since light propagates only along a straight path, transmission is interrupted by obstacles. Advantages of infrared systems include low cost, privacy (signal does not extend beyond boundaries), and high security. Therefore, they have been widely used in remote controls, short-range data transfer (e.g., between older PDAs or mobile phones), medical device communication, and optical sensors. In the modern era, infrared systems are regaining importance alongside VLC (Visible Light Communication) and Li-Fi technologies. Li-Fi enables gigabit-speed wireless data transfer using LED-based light sources, paving the way for future integration of optical communication with radio-based systems.

Radar

RADAR (Radio Detection and Ranging) systems determine a target’s distance, velocity, and direction using electromagnetic waves. The system fundamentally consists of a transmitter, an antenna, a receiver, and a display or processing unit. The transmitter emits electromagnetic waves at a specific frequency; these waves reflect off the target and return. The receiver detects these reflected signals to calculate the target’s distance (from time delay), velocity (from Doppler shift), and position (from antenna orientation). Radar technology is used in numerous fields including military surveillance, air traffic control, meteorology, autonomous vehicle systems, and space observation. New-generation 4D radar systems extract not only distance and velocity but also height (elevation) and intensity data, generating a 3D point cloud plus time dimension. These developments demonstrate that radar is no longer merely a “detection” tool but has become an “imaging and classification” instrument.

Device-to-Device (D2D) and Multi-Hop Relaying

Increasing data traffic, energy efficiency demands, and coverage requirements have necessitated moving beyond traditional base station-centric (cellular) communication structures. Device-to-Device (D2D) communication enables two user devices to communicate directly without passing through a base station. This method reduces latency and alleviates cellular network load. Multi-hop relaying is based on the principle of transmitting a signal through multiple intermediate nodes (repeaters or booster stations). For example, in Bluetooth or Wi-Fi networks, each device can act as a relay, forwarding data to the next device. This extends coverage, reduces energy consumption, and enables long-range communication through chains of short-range links. This technology holds significant potential in 5G and 6G network architectures for applications such as vehicle-to-vehicle (V2V) communication, smart transportation systems, and IoT device clusters. In the future, D2D systems are expected to dynamically reconfigure themselves based on connection density and channel quality using AI-assisted network optimization.

Filtering, Attenuators, and Noise Perspective

In communication chains, filters pass only desired frequency components and suppress interference. Low-pass filters (LPF) preserve low-frequency components, while band-pass filters (BPF) select specific frequency ranges. Attenuators ensure impedance matching and adjust signal levels. In noise management, metrics such as noise figure (NF) and equivalent noise temperature (Te) are used. Optimizing these values directly affects the system’s total gain and sensitivity. In multi-stage systems, total noise contribution is calculated using the Friis formula.

Friis Transmission Formula: Pr=PtGtGr(4πRλ)2
Friis Formula in dB: LFS(dB)=32.44+20log10(R)+20log10(f)
Friis Noise Figure Formula: Ftotal=F1+G1F2−1+G1G2F3−1+⋯+G1G2…Gn−1Fn−1
Noise Figure in dB: NF(dB)=10log10(F)

Multiplexing and Protocol Interaction

Multiplexing enables multiple users or signals to share the same channel. Common methods include time-division (TDM), frequency-division (FDM), and code-division (CDM). For example, in PCM systems, speech signals are sampled, quantized, and combined using interleaving. These physical layer processes operate in conjunction with upper-layer protocols (TCP/IP, ARQ, HDLC, etc.), ensuring data integrity, error control, and minimal packet loss.

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AuthorBeraat ÖztorunDecember 2, 2025 at 2:37 PM

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Theoretical Framework: Shannon–Weaver Model and Systemic Approach
- Shannon–Weaver Model
- Systemic Approach and the Concept of Observer
System Components and Functional Flow
- Source
- Transmitter
- Channel
- Receiver
- Destination
Channel Characteristics, Distortions, and Performance
Modulation, Demodulation, and Pulse Shaping
Data Communication: Line Coding and Transmission Modes
Example Systems and Technological Trends
- Microwave Systems
- Radio Waves and Broadcasting
- Wi-Fi (IEEE 802.11)
- Bluetooth
- Infrared (IR)
- Radar
- Device-to-Device (D2D) and Multi-Hop Relaying
Filtering, Attenuators, and Noise Perspective
Multiplexing and Protocol Interaction