Equations related to Spectral Efficiency in Hybrid Beamforming

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Equations related to Spectral Efficiency in Hybrid Beamforming

📘 Overview of Beamforming in MIMO
🧮 Hybrid Beaforming
🧮 Spectral Efficiency in Hybrid Beamforming
📚 Further Reading

Fig 1: Hybrid Beamforming

In digital beamforming, each antenna element has its own radio frequency (RF) chain, consisting of analog components (such as amplifiers, filters, and mixers) and digital components (such as analog-to-digital converters (ADCs) and digital signal processors (DSPs)). On the other hand, Only a subset of antennas (or antenna elements) has their own RF chains, while the remaining antennas share a common RF chain.

In hybrid beamforming, the beamforming process is divided into analog (say, A) and digital (say, D) beamforming domains.

The goal is to optimise the overall throughput or sum rate R (A, D) obtained over Gaussian signalling on MMwave channels by designing (A, D).

The related sum rate optimization problem looks like this:

Here, set F consists all possible analog beamformers with constant-magnitude entries.
Now for hybrid architecture we will find singular value decomposition (SVD) of channel matrix to find the stronger eigen values and we will only allocate power accordingly to these paths to achieve low overhead in hybrid architecture.

📘 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...

BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc (MATLAB + Simulator)

📘 Overview 📚 QPSK vs BPSK and QAM: A Comparison of Modulation Schemes in Wireless Communication 📚 Real-World Example 🧮 MATLAB Code 📚 Further Reading QPSK provides twice the data rate compared to BPSK. However, the bit error rate (BER) is approximately the same as BPSK at low SNR values when gray coding is used. On the other hand, QPSK exhibits similar spectral efficiency to 4-QAM and 16-QAM under low SNR conditions. In very noisy channels, QPSK can sometimes achieve better spectral efficiency than 4-QAM or 16-QAM. In practical wireless communication scenarios, QPSK is commonly used along with QAM techniques, especially where adaptive modulation is applied. Modulation Bits/Symbol Points in Constellation Usage Notes BPSK 1 2 Very robust, used in weak signals QPSK 2 4 Balanced speed & reliability 4-QAM ...

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; 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...

Theoretical BER vs SNR for binary ASK, FSK, and PSK with MATLAB Code + Simulator

📘 Overview & Theory 🧮 MATLAB Codes 📚 Further Reading Theoretical BER vs SNR for Amplitude Shift Keying (ASK) The theoretical Bit Error Rate (BER) for binary ASK depends on how binary bits are mapped to signal amplitudes. For typical cases: If bits are mapped to 1 and -1, the BER is: BER = Q(√(2 × SNR)) If bits are mapped to 0 and 1, the BER becomes: BER = Q(√(SNR / 2)) Where: Q(x) is the Q-function: Q(x) = 0.5 × erfc(x / √2) SNR : Signal-to-Noise Ratio N₀ : Noise Power Spectral Density Understanding the Q-Function and BER for ASK Bit '0' transmits noise only Bit '1' transmits signal (1 + noise) Receiver decision threshold is 0.5 BER is given by: P b = Q(0.5 / σ) , where σ = √(N₀ / 2) Using SNR = (0.5)² / N₀, we get: BER = Q(√(SNR / 2)) Theoretical BER vs ...

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator! Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...

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 ...

MATLAB Code for QPSK Modulation and Demodulation

📘 Overview 🧮 MATLAB Codes 🧮 Theory 🧮 BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc 📚 Further Reading Quadrature Phase Shift Keying (QPSK) is a digital modulation scheme that conveys two bits per symbol by changing the phase of the carrier signal. Each pair of bits is mapped to one of four possible phase shifts: 0°, 90°, 180°, or 270° 00 ===> 0 degree phase shift of carrier signal 01 ===> 90 degree 11 ===> 180 degree 10 ===> 270 degree MATLAB Script clc; clear all; close all; clc; M = 4; data = randi([0 (M-1)], 1000, 1); Phase = 0; modData=pskmod(data,M,Phase); figure(1); scatterplot(modData); channelAWGN = 15; rxData2 = awgn(modData, channelAWGN); figure(2); scatterplot(rxData2); demodData = pskdemod(rxData2,M,Phase); Result data 1 0 2 2 0 2 1 . . . modData -1.00000000000000 + 1.22464679914735e-16i -1.83697019872103e-16 - 1.000000000000...

MATLAB Code for ASK, FSK, and PSK (with Online Simulator)

📘 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...

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