Skip to main content

5G : Channel modelling for millimeter wave


Channel modelling for millimeter wave 5G communication:

In general, we employ 1. analytical channel modelling; 2. map based channel modelling; and 3. sinusoidal channel modelling for wireless communication channel modelling. Analytical modelling is based on measurements such as pathloss, rms delay spread, and so on. Map-based channel modelling, on the other hand, is focused on the geographical architecture of a specific location. When we derive a channel model for a specific frequency band, we use these two models. We'll focus on channel modelling for millimetre wave communication, which is a promising contender for enabling 5G communications.

When interacting with metal, glass, and other surfaces, mm Wave signals have a higher reflectivity and are more easily absorbed by air, rain, and other elements than signals in lower frequency bands. Furthermore, its diffraction ability is reduced. As we aforementioned channel modelling approaches fall into one of three categories: analytical modelling, map-based modelling, and stochastic modelling. Analytical modelling uses a set of established parameters, whereas ray-tracing-based modelling focuses on locating signal paths in the environment. For applications such as massive MIMO and enhanced beam formation, the map-based model delivers precise and realistic spatial channel features.


Analytical Channel Modelling:

The appropriate statistical parameters such as number of pathways, root-mean-square (RMS) delay spread, path loss, and shadowing of the propagation channel can be produced using the analytical modelling approach, which is based on the data of measurements or statistical characteristics of the scenario. Without taking into account the specifics of the environment, this method can be represented using a given set of parameters. As a result, in an anisotropic radio environment, the analysis result may be inaccurate.


Map-based Channel Modelling:

For applications such as massive MIMO and sophisticated beamforming, the map-based model delivers precise and realistic spatial channel features. It automatically generates spatially consistent modelling for difficult instances like D2D and V2V links with dual-end mobility. Ray tracing is used in conjunction with a reduced 3D geometric description of the propagation environment to create the model. Diffraction, specular reflection, diffuse scattering, and blocking are all considered important propagation mechanisms. The electromagnetic material properties of building walls are modelled as rectangular surfaces. There is no explicit path loss model in the map-based model. Instead, path loss, shadowing, and other propagation features are defined by the map layout and, optionally, a random distribution of objects that account for people, automobiles, and trees, among other things.


General description:

A geometrical representation of the environment – such as a map or a building layout expressed in a three-dimensional (3D) Cartesian coordinate system – is required for any ray-tracing-based model. It is not necessary to have a high level of map detail. Building walls and potentially other fixed structures are the only things that need to be defined.

Here in the above figure signal reaches to cell phone via MPCs where paths are either reflected or reflected. The probability of LOS path decreases as operating frequency increases.


Creation of the environment:

When walls are modelled as rectangular surfaces, a 3D map comprising coordinate points of wall corners is constructed. Both outside and indoor maps, as well as the position of indoor walls within a building block, are defined in the outdoor-to-indoor instance. The map is then strewn with random scattering/shadowing objects that depict persons, automobiles, and other items. The item positions can then be defined either based on a known regular pattern, such as the spectator seats in a stadium, or randomly selected from a uniform distribution with a set situation dependent density.


Determination of propagation pathways:

Direct, diffraction, specular reflection, and diffuse scattering must all be represented for this purpose, as seen in Figure above. The diffuse scattering caused by rough surfaces is compensated for by placing point scatterers on the external walls' surface.

Here in millimeter wave channel modelling map-based channel modeling is very important because here types of obstacle's surfaces, constructional architecture of a area, angle of arrival and departure (AoA and AoD) matters a lot.


Stochastic Channel Modelling:

The stochastic model is based on the Geometry-based Stochastic Channel Models (GSCMs) family, which includes 3GPP 3D Channel Models. It concentrates on path loss, the sum-of-sinusoids approach for calculating large-scale parameters, and so on.

#beamforming

Next Page>>



Contact Us

Name

Email *

Message *

Popular Posts

Design of CMOS Flip-Flops (SR, D, JK)

Design of CMOS Flip-Flops (SR, D, JK) A flip-flop or latch is a circuit with two stable states, used to store state information. It is the basic storage element in sequential logic and a fundamental building block in digital electronics systems, including computers and communication devices. Flip-flops and latches act as data storage elements for states, pulse counting, and synchronization of variably-timed input signals to a reference clock. Flip-flops can be transparent/opaque (latches) or clocked (synchronous, edge-triggered). Latches are level-sensitive, while flip-flops are edge-sensitive. In sequential logic, the output depends on current inputs and previous states. Fig.1 shows a sequential circuit combining a combinational block and a memory element. ...

Q-function in BER vs SNR Calculation (with Simulation)

Q-function in BER vs. SNR Calculation In digital communications and signal processing, the Q-function plays a significant role in predicting system reliability. It allows engineers to quantify the probability that Gaussian noise will exceed a specific threshold, causing a bit error. What is the Q-function? The Q-function is a mathematical function representing the tail probability of the standard normal (Gaussian) distribution. It is the complementary cumulative distribution function (CCDF) of a standard Gaussian distribution. Q(x) = (1 / √(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt The Role of the Q-function in BER vs. SNR The Q-function is the standard tool for calculating BER in systems like BPSK or QPSK over AWGN (Additive White Gaussian Noise) channels. For BPSK: In BPSK, we transmit +√E b (bit 1) and -√E b (bit 0). The decision boundary is set at 0 . If -√E b was sent, an error occurs if noise r > √...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...(MATLAB Code + Simulator)

Bit Error Rate (BER) & SNR Guide Analyze communication system performance with our interactive simulators and MATLAB tools. 📘 Theory 🧮 Simulators 💻 MATLAB Code 📚 Resources BER Definition SNR Formula BER Calculator MATLAB Comparison 📂 Explore M-ary QAM, PSK, and QPSK Topics ▼ 🧮 Constellation Simulator: M-ary QAM 🧮 Constellation Simulator: M-ary PSK 🧮 BER calculation for ASK, FSK, and PSK 🧮 Approaches to BER vs SNR Calculation What is Bit Error Rate (BER)? The BER indicates how many corrupted bits are received compared to the total number of bits sent. It is the primary figur...

Channel Impulse Response (CIR) (with MATLAB + Simulator)

📘 Overview & Theory 📘 How CIR Affects the Signal 🧮 Online Channel Impulse Response Simulator 🧮 MATLAB Codes 📚 Further Reading What is the Channel Impulse Response (CIR)? The Channel Impulse Response (CIR) is a concept primarily used in the field of telecommunications and signal processing. It provides information about how a communication channel responds to an impulse signal. It describes the behavior of a communication channel in response to an impulse signal. In signal processing, an impulse signal has zero amplitude at all other times and amplitude ∞ at time 0 for the signal. Using a Dirac Delta function, we can approximate this. Fig: Dirac Delta Function The result of this calculation is that all frequencies are responded to equally by δ(t) . This is crucial since we never know which frequenci...

FFT Butterfly Method Explained (with Simulations)

4-Point FFT Using Butterfly Method Given: x[n] = {0, 1, 2, 3} Step 1: Split into Even & Odd Even indices: x e = {x[0], x[2]} = {0, 2} Odd indices: x o = {x[1], x[3]} = {1, 3} Step 2: 2-point DFT For any {a, b}: DFT = {a + b, a - b} Even Part (E): {0+2, 0-2} = {2, -2} Odd Part (O): {1+3, 1-3} = {4, -2} Step 3: Combine Using Butterfly X[k] = E[k] + W 4 k O[k] X[k + 2] = E[k] - W 4 k O[k] Twiddle Factors (N=4): W 4 0 = 1, W 4 1 = -j Final Calculations: X[0] = E[0] + W 4 0 O[0] = 2 + (1)(4) = 6 X[2] = E[0] - W 4 0 O[0] = 2 - (1)(4) = -2 X[1] = E[1] + W 4 1 O[1] = -2 + (-j)(-2) = -2 + 2j X[3] = E[1] - W 4 1 O[1] = -2 - (-j)(-2) = -2 - 2j Final Answer: X[k] = {6, -2 + 2j, -2, -2 - 2j} 8-Point FFT Using Butterfly Method Given: x[n] = {0,1,2,3,4,5,6,7} Step 1: Split into Bit-Reversed Order To perform DIT-FFT, split the 8 points into pairs of two: Group A: {x[0], x[4]} = {0, 4}...

Frequency Bands : EHF, SHF, UHF, VHF, HF, MF, LF, VLF and Their Uses

Frequency Bands >> EHF, SHF, UHF, VHF, HF, MF, LF... Frequency Bands and Their Uses 1. Extremely High Frequency (EHF) 30 - 300 GHz Uses 5G Networks 5G millimeter wave band 6G and beyond (Experimental) RADAR 2. Super High Frequency (SHF) 3 - 30 GHz Uses Ultra-wideband (UWB) Airborne RADAR Satellite Communication Microwave Link Communication or SATCOM 3. Ultra High Frequency (UHF) 300 - 3000 MHz Uses Satellite Communication Television Surveillance Navigation aids Also, read important wireless communication terms 4....

FM Bandwidth and FM Band Explained

FM radio uses the frequency band from 88 MHz to 108 MHz , which is a 20 MHz-wide spectrum . This is the range of carrier frequencies available to stations. 108 MHz − 88 MHz = 20 MHz However, a single FM station occupies only about 200 kHz . This is the bandwidth of the modulated FM signal. 1. Why One FM Station Needs ~200 kHz FM uses frequency modulation . The bandwidth depends on how far the carrier swings. Carson's Rule gives the approximate FM bandwidth: B = 2 ( Δf + f m ) ...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Home / Engineering & Other Exams / UGC NET 2026 PYQ ⬇️ Download Papers and Solutions 📋 Exam Pattern 💡 Preparation Tips ❓ FAQs 📊 Exam Highlights: Electronic Science (88) Feature Details Junior Research Fellowship (JRF) ₹37,000 + HRA per month Eligibility M.Sc/M.Tech in Electronics (55%) Validity of Certificate JRF (3 Years) | Lectureship (Lifetime) 📥 Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading 📂 View All Question Papers June 2025 - Question Paper Download PDF June 2025 - Solved Paper + Explanation ...