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

CMOS Logic Gates: Inverter, NAND, and NOR

CMOS Logic Gates: Inverter, NAND, and NOR Complementary metal–oxide–semiconductor (CMOS) technology forms the backbone of modern digital IC design. Patented by Frank Wanlass in 1963 ( US patent 3,356,858 ), CMOS enables low-power, high-speed, and noise-immune logic circuits. CMOS gates, including inverters, NAND, and NOR, are widely used in both large-scale and small-scale integrated circuits due to their efficiency and versatility. CMOS Inverter A CMOS inverter consists of a complementary pair of PMOS and NMOS transistors. The PMOS transistor connects to the supply voltage V DD , while the NMOS connects to ground. The input voltage V IN controls both gates, and the output voltage V OUT is taken from the connected drains. CMOS inverters are highly energy-efficient and produce minimal heat due to their comple...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Download Papers and Solutions Exam Pattern Preparation Tips FAQs More Home / Engineering & Other Exams / UGC NET 2026 PYQ 📊 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 2026 - Question Paper Download PDF June 202...

Linear vs Circular Convolution

Linear vs Circular Convolution Linear convolution vs circular convolution Linear convolution (what nature does) If: x[n] = transmitted signal h[n] = channel impulse response (multipath) Then the received signal is: y[n] = x[n] * h[n] This means: Past symbols spill into future symbols Causes inter-symbol interference (ISI) DFT of y[n] is not a simple product Circular convolution (what DFT assumes) The DFT assumes periodic signals : y[n] = x[n] ⊛ h[n], where indices wrap around modulo N Only under circular convolution does the DFT satisfy: Y[k] = X[k] · H[k] This is what enables one-tap frequency-domain equalization . What happens in the real channel (linear convolution) The channel performs linear convolution: y[n] = Σ l=0 Lh−1 h[l] x[n-l] But because: CP absorbs the “spillover” Receiver discards CP before DFT The useful part of the received symbol becomes: y[n] = Σ l=0 Lh−1 h[l] x[(n-l) mod N] Modulo inde...

Online Simulator for ASK, FSK, and PSK Signal Generation

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 Demodulation More Topics 1. ASK (Ampli...

Flat vs Frequency Selective Online Simulator

Flat vs Frequency Selective Online Simulator Channel Type Without Fading Flat Fading Multipaths Nakagami m SNR(dB) Run Simulation Input Signal Signal After Fading Constellation Diagram BER vs SNR Explore Advanced Flat vs Frequency-Selective Fading Simulator Want to see these equations in action? Visualize it. Launch Simulator Tool Interactive Rayleigh Fading Simulator Want to see Rayleigh fading in action? Visualize it. Launch Simulator Tool Return to DSP Simulations Main Page →

Design of CMOS XOR/XNOR Gates

Design of CMOS XOR/XNOR Gates The semiconductor industry has experienced rapid integration of multimedia applications into mobile electronics, leading to very high integration density in CMOS VLSI. As operating frequencies increase, power consumption, speed, silicon area, and reliability become critical considerations. The XOR-XNOR circuits are fundamental building blocks in arithmetic circuits (Full Adders, Multipliers), compressors, comparators, parity checkers, code converters, error-detecting/correcting codes, and phase detectors. Their performance directly impacts the complex circuits they are used in. Design goals include full output voltage swing, low power consumption, reduced transistor count, minimal delay, and simultaneous non-skewed outputs. Static Logic (Static CMOS) Stat...

MUSIC Algorithm Explained (with MATLAB + Simulator)

Practical Implementation of the MUSIC Algorithm The focus is on how the algorithm works computationally , not just theory, and it explains the denominator (a H E n E n H a) mathematically and intuitively. 1. Introduction The MUSIC (Multiple Signal Classification) algorithm is a high-resolution method used in signal processing and array processing to estimate the Direction of Arrival (DOA) of signals received by a sensor array. Unlike classical beamforming methods, MUSIC uses eigenvector decomposition of the covariance matrix to separate the signal subspace and noise subspace , allowing it to achieve much higher angular resolution. In practical implementations, MUSIC works by: Simulating or collecting array signals Computing the covariance matrix Performing eigenvalue decomposition Separating signal and noise subspaces Scanning possible angles using a steering vector Constructing a pseudo-spectrum where peaks indicate signal directions 2. Signal Mo...