Skip to main content

Analog Beamforming vs Digital beamforming



1. Analog Beamforming:

Beamforming is a method of focusing a signal in a certain direction to provide sufficient signal strength at the receiver end of the communication process. We normally require more than one closely located antenna to form a beam in a specific direction and focus the resultant signal from antennas to use beam forming. We can also use a phase shifter or PSs to control the phases of a signal. We employ MIMO (multiple input multiple output antenna) [↗] to provide beam forming. In a MIMO system, antennas are normally positioned in a half-wavelength interval of the operating frequency.


We commonly employ beam forming when we need to send a signal over a great distance (e.g., for radar communication) and omnidirectional transmission isn't feasible. On the other hand, we can use beam forming to extend the range of our signal without boosting TX power.


Similarly, 5G communication [Read More] makes advantage of an incredibly high frequency [↗]. As a result, it suffers from severe path loss [↗], and its short wavelength is easily absorbed by air gases, vapor, and other particles. With sufficient power, such an extremely high-frequency band can only go a short distance. As a result, we use beam forming to cover greater distances. We get a stronger and narrower beam by increasing the number of antennas without raising the TX power. It is an important advantage of beamforming.

There are several methods of beam formation, but they are usually divided into three categories: 1. Analog beam forming 2. Digital Beamforming 3. Hybrid Beamforming. In analog beam formation, the beam is steered at both the transmitter and receiver end, and the best beam pairs are selected for communication. More simply, we aim to send signals at varying angles of arrival range, or AOA, from the transmitter side. We do the same thing on the receiver side, then only connect the best beams from both the transmitter and receiver sides. We can only change the phases (or, to put it another way, the direction of signal transmission) of a signal in analog beam forming, and there is only one data stream between the transmitter and receiver.
 
analog beamforming
Get MATLAB Code for Analog and Digital Beamforming


The number of antennas on both the transmitter and receiving sides may be seen in the diagram above. To form a beam, more than one neighboring antenna is required, as previously stated. The fact that there is just one RF Chain on both the transmitter and receiver sides is a crucial aspect of analog beam formation. The number of RF chains equals the number of simultaneous data streams accessible between the transmitter and receiver. In the diagram above, we steer the beam at the transmitter to find the optimal beam between the transmitter and the receiver, while the receiver transmits in an omnidirectional manner. The same thing happens at the receiver's end, or the receiver tries directional beams while the transmitter radiates in an omnidirectional manner. Then, using adequate feedback, the best beam pairs from both sides are connected. RF chains contain mixers, power amplifiers, etc.

In the following chapters, we'll look into digital beam forming, which allows multiple data streams to be sent and received simultaneously. We'll also talk about canceling interference between many devices and canceling interference between simultaneous data streams.



2. Digital Beamforming:

Unlike analog pre-coding, we can send signals with a variety of phases and amplitudes. Different phases signify different things, such as the ability to steer the beam in different directions, which is also accessible for analog beam formation. On the other side, we can also regulate the transmitted signal's amplitude. If we need to reduce the signal's amplitude in a specific antenna element, we can easily do it.

The signal that was received is denoted by

y=√pHDs + n
where, p=average received power
H=channel matrix
D= digital or baseband pre-coder
s= symbol vector
n = additive white Gaussian noise

Each antenna is connected to a distinct transmit and receive (TR) module or RF chain in the system diagram below.


analog beamforming

Fig: Digital Beamforming


We know that point-to-point communication between MIMO is conceivable, such as h11, h12, h22, and so on. For example, 'h22' denotes channel gain or the link between the second antenna on the transmitter and the second antenna on the receiver. 


Also Read about

[1] What is the process of beamforming in MIMO or massive MIMO systems?

[2] Hybrid Beamforming 

[3] Mathematical aspects of beamforming in MIMO 

[4] Equations related to spectral efficiency in digital beamforming

[5] Equations related to spectral efficiency in hybrid beamforming   

[6]  MATLAB Codes for various types of beamforming

[7] Spatially Sparse Hybrid Precoding / beamforming

[8] What are the Precoding and Combining Weights / Matrices in a MIMO Beamforming System 

[9]  Beamforming in Wi-Fi

[10] Beamforming in Audio Signal Processing

[11] MIMO, massive MIMO, and Beamforming

more ...

# analog beamforming

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...

Constellation Diagrams of ASK, PSK, and FSK

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM 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 of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals...

Theoretical vs. simulated BER vs. SNR for ASK, FSK, and PSK

📘 Overview 🧮 Simulator for calculating BER 🧮 MATLAB Codes for calculating theoretical BER 🧮 MATLAB Codes for calculating simulated BER 📚 Further Reading BER vs. SNR denotes how many bits in error are received for a given signal-to-noise ratio, typically measured in dB. Common noise types in wireless systems: 1. Additive White Gaussian Noise (AWGN) 2. Rayleigh Fading AWGN adds random noise; Rayleigh fading attenuates the signal variably. A good SNR helps reduce these effects. Simulator for calculating BER vs SNR for binary ASK, FSK, and PSK Calculate BER for Binary ASK Modulation Enter SNR (dB): Calculate BER Calculate BER for Binary FSK Modulation Enter SNR (dB): Calculate BER Calculate BER for Binary PSK Modulation Enter SNR (dB): Calculate BER BER vs. SNR Curves MATLAB Code for Theoretical BER % The code is written by SalimWireless.Com clc; clear; close all; % SNR va...

MATLAB Code for ASK, FSK, and PSK

📘 Overview & Theory 🧮 MATLAB Code for ASK 🧮 MATLAB Code for FSK 🧮 MATLAB Code for PSK 🧮 Simulator for binary ASK, FSK, and PSK Modulations 📚 Further Reading ASK, FSK & PSK HomePage MATLAB Code MATLAB Code for ASK Modulation and Demodulation % The code is written by SalimWireless.Com % Clear previous data and plots clc; clear all; close all; % Parameters Tb = 1; % Bit duration (s) fc = 10; % Carrier frequency (Hz) N_bits = 10; % Number of bits Fs = 100 * fc; % Sampling frequency (ensure at least 2*fc, more for better representation) Ts = 1/Fs; % Sampling interval samples_per_bit = Fs * Tb; % Number of samples per bit duration % Generate random binary data rng(10); % Set random seed for reproducibility binary_data = randi([0, 1], 1, N_bits); % Generate random binary data (0 or 1) % Initialize arrays for continuous signals t_overall = 0:Ts:(N_bits...

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...

🧮 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; num_symbols = 1e5; snr_db = -20:2:20; 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) psk_order = psk_orders(i); for j = 1:length(snr_db) data_symbols = randi([0, psk_order-1], 1, num_symbols); modulated_signal = pskmod(data_symbols, psk_order, pi/psk_order); received_signal = awgn(modulated_signal, snr_db(j), 'measured'); demodulated_symbols = pskdemod(received_signal, psk_order, pi/psk_order); ber_psk_results(i, j) = sum(data_symbols ~= demodulated_symbols) / num_symbols; end end for i...

Comparisons among ASK, PSK, and FSK | And the definitions of each

📘 Comparisons among ASK, FSK, and PSK 🧮 Online Simulator for calculating Bandwidth of ASK, FSK, and PSK 🧮 MATLAB Code for BER vs. SNR Analysis of ASK, FSK, and PSK 📚 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 Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK    Comparisons among ASK, PSK, and FSK Comparison among ASK, FSK, and PSK Parameters ASK FSK PSK Variable Characteristics Amplitude Frequency ...

Calculation of SNR from FFT bins in MATLAB

📘 Overview 🧮 MATLAB Code for Estimation of SNR from FFT bins of a Noisy Signal 🧮 MATLAB Code for Estimation of Signal-to-Noise Ratio from Power Spectral Density Using FFT and Kaiser Window Periodogram from real signal data 📚 Further Reading   Here, you can find the SNR of a received signal from periodogram / FFT bins using the Kaiser operator. The beta (β) parameter characterizes the Kaiser window, which controls the trade-off between the main lobe width and the side lobe level in the frequency domain. For that you should know the sampling rate of the signal.  The Kaiser window is a type of window function commonly used in signal processing, particularly for designing finite impulse response (FIR) filters and performing spectral analysis. It is a general-purpose window that allows for control over the trade-off between the main lobe width (frequency resolution) and side lobe levels (suppression of spectral leakage). The Kaiser window is defined...

Theoretical BER vs SNR for BPSK

Theoretical Bit Error Rate (BER) vs Signal-to-Noise Ratio (SNR) for BPSK in AWGN Channel Let’s simplify the explanation for the theoretical Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) for Binary Phase Shift Keying (BPSK) in an Additive White Gaussian Noise (AWGN) channel. Key Points Fig. 1: Constellation Diagrams of BASK, BFSK, and BPSK [↗] BPSK Modulation Transmits one of two signals: +√Eb or −√Eb , where Eb is the energy per bit. These signals represent binary 0 and 1 . AWGN Channel The channel adds Gaussian noise with zero mean and variance N₀/2 (where N₀ is the noise power spectral density). Receiver Decision The receiver decides if the received signal is closer to +√Eb (for bit 0) or −√Eb (for bit 1) . Bit Error Rat...