Skip to main content

Equations related to Spectral Efficiency in Digital Beamforming


 
 
Fig 1: Digital Beamforming 
 

The main working principle between the beamforming (or analog beamforming) is to maximize the signal strength in a particular direction towards the receiver. For example, you can steer the antenna manually towards the transmitter to maximize the signal strength, like dish antennas. However, the approach could be more practical for mobile communications. With the help of a phase shifter, we do it electronically. On the other hand, for example, a dish antenna has an aperture that adds some gain to the received signal.Similarly, placing many antennas at a particular space instant creates a beam in a specific direction, minimizing signal strength in the rest of the directions. Here, a combination of antennas creates virtual apertures. On the transmitter side, it transmits a more robust signal toward the receiver. Oppositely, it makes a virtual aperture at the receiver and captures the signal more efficiently.

The main advantage of beamforming is maximizing the signal strength by increasing the number of antenna elements, not the total power.

In the case of analog beamforming, there is only one transmitter and one receiver, and only a single data stream is possible between them.

In the case of digital beamforming, multiple data streams are possible between transmitter and receiver or receivers. The number of users may be one or many.

If there is only one number of users, then multiple data streams between the transmitter and receiver will increase data rates through spatial multiplexing. Similarly, if multiple users exist, each data stream may be allocated to a single user. The various users communicate with the transmitter by deploying spatial multiplexing.

 

For Single User Digital Beamforming

The received signal vector y at receiver side,

                                                                                 y= √ρHDs + n

                                               Here, D = digital beamforming matrix

                                                         ρ = average received power

                                                         H =channel matrix ( Nr X Nt)

                                                         n = additive white Gaussian noise vector

                                                     Nr and Nt are the number of antenna elements at the receiver and  transmitter side respectively.

 You may think this beamforming equation is the same as analog beamforming, but this is not. Here, the number of independent data streams between transmitter and receiver is min(Nr, Nt). If there are two transmitting antennas and three receiver antennas, then two independent data streams are possible between transmitter and receiver to communicate simultaneously.
 

For Multi-user Digital Beamforming

D= [D1, D2, …, DU], & Du denotes the u th user, a digital precoder (size of NBS X NMS)

NBS and NMS are the number of antenna elements at the transmitter and receiver side respectively 

Now cancel interference at uth user due to other users, we need to design the baseband precoder in such a way that HuDn for nǂ u should be zero at the u th MS. Therefore, HuDn =0 cancels interferences at uth MS.



Contact Us

Name

Email *

Message *

Popular Posts

Hybrid Beamforming | Page 1

Beamforming Techniques Hybrid Beamforming... Page 1 | Page 2 | Hybrid Beamforming: Hybrid beam formation was developed to address some of the limitations of digital pre-coding approaches. Every antenna element is connected to an RF chain in digital pre-coding (beam forming) method. We also know that each RF chain is in charge of providing a separate data stream between the transmitter and the receiver. We know that a larger number of independent data streams leads to higher data rates. It has a spatial multiplexing feature for MIMO. As a result, we may assume that switching from MIMO to massive MIMO will benefit us more in terms of spatial multiplexing in massive MIMO, where each antenna is coupled to a single RF chain. We'll proceed with a definition of hybrid beam forming. Overview of hybrid beam forming with example: Unlike digital beam forming, more than one antenna element is connected to a single RF chain in hybr...

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 ...

MATLAB Code for Rms Delay Spread

RMS delay spread is crucial when you need to know how much the signal is dispersed in time due to multipath propagation, the spread (variance) around the average. In high-data-rate systems like LTE, 5G, or Wi-Fi, even small time dispersions can cause ISI. RMS delay spread is directly related to the amount of ISI in such systems. RMS Delay Spread [↗] Delay Spread Calculator Enter delays (ns) separated by commas: Enter powers (dB) separated by commas: Calculate   The above calculator Converts Power to Linear Scale: It correctly converts the power values from decibels (dB) to a linear scale. Calculates Mean Delay: It accurately computes the mean excess delay, which is the first moment of the power delay profile. Calculates RMS Delay Spread: It correctly calculates the RMS delay spread, defined as the square root of the second central moment of the power delay profile.   MATLAB Code  clc...

Comparisons among ASK, PSK, and FSK (with MATLAB + Simulator)

Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK 📘 Comparisons among ASK, FSK, and PSK 🧮 Online Simulator Bandwidth 🧮 MATLAB Code BER Analysis 📚 Further Reading 📂 View Other Topics on Comparisons among ASK, PSK, and FSK ... 🧮 Comparisons of Noise Sensitivity, Bandwidth, Complexity, etc. 🧮 MATLAB Code for Constellation Diagrams of ASK, FSK, and PSK 🧮 Online Simulator for ASK, FSK, and PSK Generation 🧮 Online Simulator for ASK, FSK, and PSK Constellation 🧮 Some Questions and Answers Comparisons among ASK, PSK, and FSK Comparison among ASK, FSK, and PSK Parameters ASK FSK PSK Variable Characteristics Amplitude ...

How Windowing Affects Your Periodogram

The windowed periodogram is a widely used technique for estimating the Power Spectral Density (PSD) of a signal. It enhances the classical periodogram by mitigating spectral leakage through the application of a windowing function. This technique is essential in signal processing for accurate frequency-domain analysis.   Power Spectral Density (PSD) The PSD characterizes how the power of a signal is distributed across different frequency components. For a discrete-time signal, the PSD is defined as the Fourier Transform of the signal’s autocorrelation function: S x (f) = FT{R x (τ)} Here, R x (τ)}is the autocorrelation function. FT : Fourier Transform   Classical Periodogram The periodogram is a non-parametric PSD estimation method based on the Discrete Fourier Transform (DFT): P x (f) = \(\frac{1}{N}\) X(f) 2 Here: X(f): DFT of the signal x(n) N: Signal length However, the classical periodogram suffers from spectral leakage due to abrupt truncation of the ...

What is - 3dB Frequency Response? And applications

📘 Overview & Theory 📘 Application of -3dB Frequency Response 🧮 MATLAB Codes 🧮 Online Digital Filter Simulator 📚 Further Reading Filters What is -3dB Frequency Response?   Remember, for most passband filters, the magnitude response typically remains close to the peak value within the passband, varying by no more than 3 dB. This is a standard characteristic in filter design. The term '-3dB frequency response' indicates that power has decreased to 50% of its maximum or that signal voltage has reduced to 0.707 of its peak value. Specifically, The -3dB comes from either 10 Log (0.5) {in the case of power} or 20 Log (0.707) {in the case of amplitude} . Viewing the signal in the frequency domain is helpful. In electronic amplifiers, the -3 dB limit is commonly used to define the passband. It shows whether the signal remains approximately flat across the passband. For example, in pulse shapi...

Phase Shift Keying (PSK) Modulation & Demodulation (with Simulation)

Phase Shift Keying (PSK) Theoretical Framework: Phase Shift Keying (PSK) is a digital modulation paradigm where information is encoded by modulating the instantaneous phase of a continuous-wave carrier. In Binary PSK (BPSK), the most fundamental implementation, the bitstream is mapped onto two discrete phases separated by $\pi$ radians—typically representing binary '1' and '0'—resulting in an antipodal signaling scheme where each state change induces a phase reversal in the carrier. BPSK Transmitter Synthesis: The analytic representation of a BPSK signal $s(t)$ is defined as: \[ s(t) = \begin{cases} A_c \cos(2\pi f_c t), & \text{for symbol } m_1 \\ A_c \cos(2\pi f_c t + \pi) = -A_c \cos(2\pi f_c t), & \text{for symbol } m_0 \end{cases} \] NRZ-L m(t) × ...