Network Slicing for 5G Networks

HOME
NEWSLETTER
CONTACT

Wireless Communication Modulation MATLAB Beamforming Project Ideas MIMO Computer Networks

Network Slicing for 5G Networks

5G

Network Slicing

We all know that 5G will completely transform our lives. We have only had cellular data from telecom data providers up to this point (up to 4G LTE). However, 5G will alter the game. 5G networks will provide us with mobile broadband data. In comparison to the 4G network, 5G will provide significantly more bandwidth. Although 5G is still being used in many countries at frequencies ranging from 3.5 to 4.5 GHz, it will soon be used in the millimeter wave band. In a few countries, 5G is already using carrier frequency bands of 28 GHz and 39 GHz.

5G will have extremely low latency due to its extremely high frequency band or high bandwidth. You are aware that latency is an important factor in any network communication. A network with lower latency transmits data more quickly. It is anticipated that 5G will provide 1 ms (on the air) latency, which will be sufficient for real-time monitoring. With the help of 5G, industrial automation, self-driving cars, virtual reality (VR), augmented reality, telemedicine, and other technologies will become a part of our daily lives.

Now we'll discuss network slicing in 5G networks. We already know that 5G will provide massive bandwidth, enough to connect thousands of devices per square kilometre. Some bandwidth may now be set aside for extremely useful and emergency services. For example, some bandwidth may be set aside for vehicular networks or telemedicine, among other things. Because, after allocating some fixed bandwidth to emergency services, 5G will have adequate bandwidth.

Parent Topics

People are good at skipping over material they already know!

View Related Topics to

Admin & Author: Salim

  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 *

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...

Antenna Gain-Combining Methods - EGC, MRC, SC, and RMSGC

There are different antenna gain-combining methods. They are as follows. 1. Equal gain combining (EGC) 2. Maximum ratio combining (MRC) 3. Selective combining (SC) 4. Root mean square gain combining (RMSGC) 1. Equal gain combining method We add the correlated data streams from different antennas in the equal gain combining method. Then we multiply the resultant data with (1/(number of antennas)) For example, for two antenna gain-combining If the received symbols are y1 and y2, then Equal combing gain, y_egc = 0.5 * (y1 + y2) 2. Maximum ratio combining method We multiply the individual data streams with weights in the maximum ratio combining method. More weightage is multiplied by those data streams with maximum {|h|^2}, where h denotes the channel impulse response. And less weightage is multiplied by those data streams with corresponding small value of {|h|^2}. Then we sum the data streams to improve SNR. In the case of Maximum Ratio Combining, if y1 an...

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

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 Performance Comparison: 1. Noise Sensitivity: - ASK is the most sensitive to noise due to its reliance on amplitude variations. - PSK is less sensitive to noise compared to ASK. - FSK is relatively more robust against noise, making it suitable for noisy environments. 2. Bandwidth Efficiency: - PSK is the most bandwidth-efficient, requiring less bandwidth than FSK for the same data rate. - FSK requires wider bandwidth compared to PSK. - ASK's bandwidth efficiency lies between FSK and PSK. Bandwidth Calculator for ASK, FSK, and PSK The baud rate represents the number of symbols transmitted per second Select Modulation Type: ASK...

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 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...

MATLAB Code for Pulse Amplitude Modulation (PAM) and Demodulation

Pulse Amplitude Modulation (PAM) & Demodulation MATLAB Script clc; clear all; close all; fm= 10; % frequency of the message signal fc= 100; % frequency of the carrier signal fs=1000*fm; % (=100KHz) sampling frequency (where 1000 is the upsampling factor) t=0:1/fs:1; % sampling rate of (1/fs = 100 kHz) m=1*cos(2*pi*fm*t); % Message signal with period 2*pi*fm (sinusoidal wave signal) c=0.5*square(2*pi*fc*t)+0.5; % square wave with period 2*pi*fc s=m.*c; % modulated signal (multiplication of element by element) subplot(4,1,1); plot(t,m); title('Message signal'); xlabel ('Time'); ylabel('Amplitude'); subplot(4,1,2); plot(t,c); title('Carrier signal'); xlabel('Time'); ylabel('Amplitude'); subplot(4,1,3); plot(t,s); title('Modulated signal'); xlabel('Time'); ylabel('Amplitude'); %demdulated d=s.*c; % At receiver, received signal is multiplied by carrier signal filter=fir1(200,fm/fs,'low'); % low-pass FIR fi...

Constellation Diagrams of ASK, PSK, and FSK

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. Key Points For Binary Amplitude Shift Keying (BASK), binary bit '0' can be represented as lower level voltage or no signal and bit '1' as higher level voltage. For Binary Frequency Shift Keying (BFSK), you can map binary bit '0' to 'j' and bit '1' to '1'. So, signals are in phase. A phase shift of 0 degrees could represent a binary '1...

MATLAB code for GMSK

Copy the MATLAB code from here % The code is developed by SalimWireless.com clc; clear; close all; % Parameters samples_per_bit = 36; bit_duration = 1; num_bits = 20; sample_interval = bit_duration / samples_per_bit; time_vector = 0:sample_interval:(num_bits * bit_duration); time_vector(end) = []; % Generate and modulate binary data binary_data = randi([0, 1], 1, num_bits); modulated_bits = 2 * binary_data - 1; upsampled_signal = kron(modulated_bits, ones(1, samples_per_bit)); figure; plot(time_vector, upsampled_signal); title('Message Signal'); % Apply Gaussian filter filtered_signal = conv(GMSK_gaussian_filter1(bit_duration, samples_per_bit), upsampled_signal); filtered_signal = [filtered_signal, filtered_signal(end)]; figure; plot(filtered_signal); title('Filtered Signal'); % Integration & GMSK modulation integrated_signal = cumsum(filtered_signal); gmsk_signal = exp(1i * integrated_signal); % Plotting the real and imaginary parts of the GMSK signal ...

Search This Blog