Skip to main content

Beamforming in 5G, Wi-Fi, and Others | Implementation



Implementation of Beamforming Technique in Wireless Communication and  Future work


Beamforming is a technique for sending a signal further away from the receiver without raising the transmitter's transmission power. Beamforming is employed everywhere that we want to transmit our signal to a long-distance receiver, from radar communication to deep-space communication. In the instance of deep space communication, we use a laser beam to send our signal millions of miles away.

An omnidirectional antenna radiates its power uniformly around the antenna. 0 dBi is the gain of an omnidirectional isotropic antenna. However, we acquire better gain with directional antennas than with omnidirectional antennas. It also can send a signal in a specific direction with greater power and across a greater distance.

If we achieve the directional antenna gain of 6dB for a standard directional antenna system, the signal will travel twice the distance covered without beamforming.



Applications of Beamforming in Wireless Communication


In WLAN Applications

Beamforming is a technique used in Wi-Fi technology, particularly in routers. MIMO technology is also used to provide users with numerous communication channels or to allow several users to connect to the internet from the same router.

In Ground Stations

Beamforming is important in satellite communication, deep space communication, and other applications. We can't fathom delivering a radio signal thousands of miles away from a ground station on Earth without sending a powerful narrow beam. The direction of the beam is also crucial in this case. For example, big parabolic antennas capable of producing a stronger, narrower beam are used in ground stations to connect with satellites or aircraft.


In Modern Cellular 5G Networks  

We use incredibly high-frequency hands in 5G, as you know. Signal power loss in free space communication is inversely proportional to the operational frequency band. In the case of 5G path loss, the atmospheric loss is also included. Oxygen, vapor, and other molecules in the atmosphere easily absorb extremely high-frequency bands. As a result, beamforming is required to focus signal at a 5G user's device so that data packets can be received with good signal strength. Due to inadequate signal strength, we will be unable to connect devices to cell towers or access points if beamforming is not used in 5G communication. Beamforming, on the other hand, is well suited to energy harvesting. When communication is required, it only focuses beams toward the desired user's device.

Beamforming is a critical technique for enabling 5G. As a result, various studies on beamforming in 5G have been conducted, particularly on massive MIMO, which is capable of producing narrower beams. Massive MIMO provides a narrower or finer beam immediately adjacent to the antenna elements. Because beamforming is nothing more than the result of several antennas transmitting the same signal. Where the signal amplitude is also a resultant value and the beam is focused in the resultant phase direction of all signals.



Contact Us

Name

Email *

Message *

Popular Posts

Online Simulator for ASK, FSK, and PSK

Interactive Digital Signal Processing (DSP) Tutorial and Simulator for ASK, FSK, and BPSK modulation techniques. Try our new Digital Signal Processing Simulator!   •   Interactive ASK, FSK, and BPSK tools updated for 2025. Start Now Digital Modulation Visualizer: ASK, FSK, & BPSK Simulator Learn and visualize binary modulation techniques (ASK, FSK, BPSK) in real-time with adjustable carrier and sampling parameters. Perfect for DSP students and engineers. 📡 ASK Simulator 📶 FSK Simulator 🎚️ BPSK Simulator 📚 More Topics ASK Modulator FSK Modulator BPSK Modulator More Topics 1. ASK (Amplitude Shift Keying) Simulato...

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...(with Online Simulator)

🧮 MATLAB Code for BPSK, M-ary PSK, and M-ary QAM Together 🧮 MATLAB Code for M-ary QAM 🧮 MATLAB Code for M-ary PSK 📚 Further Reading MATLAB Script for BER vs. SNR for M-QAM, M-PSK, QPSK, BPSK % Written by Salim Wireless clc; clear; close all; snr_db = -5:2:25; psk_orders = [2, 4, 8, 16, 32]; qam_orders = [4, 16, 64, 256]; ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); for i = 1:length(psk_orders) ber_psk_results(i, :) = berawgn(snr_db, 'psk', psk_orders(i), 'nondiff'); end for i = 1:length(qam_orders) ber_qam_results(i, :) = berawgn(snr_db, 'qam', qam_orders(i)); end figure; semilogy(snr_db, ber_psk_results(1, :), 'o-', 'LineWidth', 1.5, 'DisplayName', 'BPSK'); hold on; for i = 2:length(psk_orders) semilogy(snr_db, ber_psk_results(i, :), 'o-', 'DisplayName', sprintf('%d-PSK', psk_or...

UGC NET Electronic Science Previous Year Question Papers

Home / Engineering & Other Exams / UGC NET 2022 PYQ 📥 Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading UGC-NET (Electronics Science, Subject code: 88) Subject_Code : 88; Department : Electronic Science; 📂 View All Question Papers Q. UGC Net Electronic Science Question Paper [June 2025] A. UGC Net Electronic Science Question Paper With Answer Key Download Pdf [June 2025] with full explanation Q. UGC Net Electronic Science Question Paper [December 2024] A. UGC Net Electronic Science Question Paper With Answer Key Download Pdf [December 2024] Q. UGC Net Electronic Science Question Paper [Aug 2024] A. UGC Net Electronic Scien...

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 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 figure of merit for a...

Constellation Diagrams of ASK, PSK, and FSK (with MATLAB Code + Simulator)

Constellation Diagrams: ASK, FSK, and PSK Comprehensive guide to signal space representation, including interactive simulators and MATLAB implementations. 📘 Overview 🧮 Simulator ⚖️ Theory 📚 Resources Definitions Constellation Tool Key Points MATLAB Code 📂 Other Topics: M-ary PSK & QAM Diagrams ▼ 🧮 Simulator for M-ary PSK Constellation 🧮 Simulator for M-ary QAM Constellation BASK (Binary ASK) Modulation Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1. BFSK (Binary FSK) Modulation Transmits one...

DFTs-OFDM vs OFDM: Why DFT-Spread OFDM Reduces PAPR Effectively (with MATLAB Code)

Understanding PAPR in DFT-spread OFDM vs. Standard OFDM In modern wireless communications like 4G LTE and 5G NR, managing the Peak-to-Average Power Ratio (PAPR) is critical for hardware efficiency. While OFDM is the gold standard for high-speed data, its high PAPR poses significant challenges for mobile devices. This is where DFTs-OFDM (also known as SC-FDMA) comes in. DFT-spread OFDM (DFTs-OFDM) has lower Peak-to-Average Power Ratio (PAPR) because it "spreads" the data in the frequency domain before applying IFFT, making the time-domain signal behave more like a single-carrier signal rather than a multi-carrier one like OFDM. Deeper Explanation: Aspect OFDM DFTs-OFDM Signal Type Multi-carrier Single-carrier-like Process IFFT of QAM directly QAM → DFT → IFFT PAPR Level High (due to many...

MATLAB Code for Zero-Forcing (ZF) Beamforming in 4×4 MIMO Systems

MATLAB Code for Zero-Forcing (ZF) Beamforming in 4×4 MIMO Systems clc; clear; close all; %% Parameters Nt = 4; % Transmit antennas Nr = 4; % Receive antennas (must be >= Nt for ZFBF) numBits = 1e4; % Number of bits per stream SNRdB = 0; % SNR in dB numRuns = 100; % Number of independent runs for averaging %% Precompute noise standard deviation noiseSigma = 10^(-SNRdB / 20); %% Accumulator for total errors totalErrors = 0; for run = 1:numRuns % Generate random bits: [4 x 10000] bits = randi([0 1], Nt, numBits); % BPSK modulation: 0 → +1, 1 → -1 txSymbols = 1 - 2 * bits; % Rayleigh channel matrix: [4 x 4] H = (randn(Nr, Nt) + 1j * randn(Nr, Nt)) / sqrt(2); %% === Zero Forcing Beamforming at Transmitter === W_zf = pinv(H); % Precoding matrix: [Nt x Nr] txPrecoded = W_zf * txSymbols; % Apply ZF precoding % Normalize transmit power (optional but useful) txPrecoded = txPrecoded / sqrt(mean(abs(txPrecoded(:)).^2)); %% Channel transmission with AWGN noise = noiseSigma * (randn(...

MIMO, massive MIMO, and Beamforming

Introduction to MIMO Systems The term Multiple Input Multiple Output (MIMO) refers to wireless communication systems that use multiple antennas at both the transmitter (Tx) and receiver (Rx). MIMO is a core technology in modern standards such as Wi-Fi 4/5/6, LTE, and 5G . The main purpose of MIMO is to increase channel capacity and improve link reliability by transmitting multiple independent data streams over the same frequency band. These simultaneous data streams are spatially multiplexed and transmitted through distinct propagation paths. When properly decoded, this orthogonal multiplexing minimizes interference among data streams and enhances throughput. In Massive MIMO —a key concept in 5G systems—hundreds of antennas are used at the base station to achieve very high capacity and to enable beamforming or directional transmission. 1. Essential Characteristics of a MIMO System 1.1 Spatial Division Multiple Access (SD...