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







Admin & Author: Salim

profile

  Website: www.salimwireless.com
  Interests: Signal Processing, Telecommunication, 5G Technology, Present & Future Wireless Technologies, Digital Signal Processing, Computer Networks, Millimeter Wave Band Channel, Web Development
  Seeking an opportunity in the Teaching or Electronics & Telecommunication domains.
  Possess M.Tech in Electronic Communication Systems.


Contact Us

Name

Email *

Message *

Popular Posts

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

Modulation Constellation Diagrams BER vs. SNR BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ... 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. It is defined as,  In mathematics, BER = (number of bits received in error / total number of transmitted bits)  On the other hand, SNR refers to the signal-to-noise power ratio. For ease of calculation, we commonly convert it to dB or decibels.   What is Signal the signal-to-noise ratio (SNR)? SNR = signal power/noise power (SNR is a ratio of signal power to noise power) SNR (in dB) = 10*log(signal power / noise power) [base 10] For instance, the SNR for a given communication system is 3dB. So, SNR (in ratio) = 10^{SNR (in dB) / 10} = 2 Therefore, in this instance, the s...

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

Modulation Constellation Diagrams BER vs. SNR MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...   MATLAB Script for  BER vs. SNR for M-QAM, M-PSK, QPSk, BPSK %Written by Salim Wireless %Visit www.salimwireless.com for study materials on wireless communication %or, if you want to learn how to code in MATLAB clc; clear; close all; % Parameters num_symbols = 1e5; % Number of symbols snr_db = -20:2:20; % Range of SNR values in dB % PSK and QAM orders to be tested psk_orders = [2, 4, 8, 16, 32]; qam_orders = [4, 16, 64, 256]; % Initialize BER arrays ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); % BER calculation for each PSK order and SNR value for i = 1:length(psk_orders) psk_order = psk_orders(i); for j = 1:length(snr_db) % Generate random symbols data_symbols = randi([0, psk_order-1], 1, num_symb...

Theoretical BER vs SNR for BPSK

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 Rate (BER) The probability of error (BER) for BPSK is given by a function called the Q-function. The Q-function Q(x) measures the tail probability of the normal distribution, i.e., the probability that a Gaussian random variable exceeds a certain value x.  Formula for BER: BER=Q(...

Constellation Diagrams of ASK, PSK, and FSK

Modulation ASK, FSK & PSK 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 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: +√Eb​ or -√Eb (they differ by 180 degree phase shift), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  This article will primarily discuss constellation diagrams, as well as what constellation diagrams tell us and the significance of constellation diagrams. Constellation diagrams can often demonstrate how the amplitude and phase of signals or symbols differ. These two characteristics lessen the interference between t...

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

  BER vs. SNR denotes how many bits in error are received in a communication process for a particular Signal-to-noise (SNR) ratio. In most cases, SNR is measured in decibel (dB). For a typical communication system, a signal is often affected by two types of noises 1. Additive White Gaussian Noise (AWGN) 2. Rayleigh Fading In the case of additive white Gaussian noise (AWGN), random magnitude is added to the transmitted signal. On the other hand, Rayleigh fading (due to multipath) attenuates the different frequency components of a signal differently. A good signal-to-noise ratio tries to mitigate the effect of noise.  Calculate BER for Binary ASK Modulation The theoretical BER for binary ASK (BASK) in an AWGN channel is given by: BER  = (1/2) * erfc(0.5 * sqrt(SNR_ask));   Enter SNR (dB): Calculate BER BER vs. SNR curves for ASK, FSK, and PSK Calculate BER for Binary FSK Modulation The theoretical BER for binary FSK (BFSK) in a...

OFDM in MATLAB

  MATLAB Script % The code is written by SalimWireless.Com 1. Initialization clc; clear all; close all; 2. Generate Random Bits % Generate random bits numBits = 100; bits = randi([0, 1], 1, numBits); 3. Define Parameters % Define parameters numSubcarriers = 4; % Number of subcarriers numPilotSymbols = 3; % Number of pilot symbols cpLength = ceil(numBits / 4); % Length of cyclic prefix (one-fourth of the data length) 4. Add Cyclic Prefix % Add cyclic prefix dataWithCP = [bits(end - cpLength + 1:end), bits]; 5. Insert Pilot Symbols % Insert pilot symbols pilotSymbols = ones(1, numPilotSymbols); % Example pilot symbols (could be any pattern) dataWithPilots = [pilotSymbols, dataWithCP];   6. Perform OFDM Modulation (IFFT) % Perform OFDM modulation (IFFT) dataMatrix = reshape(dataWithPilots, numSubcarriers, []); ofdmSignal = ifft(dataMatrix, numSubcarriers); ofdmSignal = reshape(ofdmSignal, 1, []); 7. Display the Generated Data % Display the generated data disp("Original Bits:"); ...

Why is Time-bandwidth Product Important?

Time-Bandwidth Product (TBP) The time-bandwidth product (TBP) is defined as: TBP = Δ f ⋅ Δ t Δf (Bandwidth) : The frequency bandwidth of the signal, representing the range of frequencies over which the signal is spread. Δt (Time duration) : The duration for which the signal is significant, i.e., the time interval during which the signal is non-zero. The TBP is a measure of the "spread" of the signal in both time and frequency domains. A higher TBP means the signal is both spread over a larger time period and occupies a wider frequency range.     To calculate the period of a signal with finite bandwidth, Heisenberg’s uncertainty principle plays a vital role where the time-bandwidth product indicates the processing gain of the signal. We apply spread spectrum techniques in wireless communication for various reasons, such as interference resili...