Skip to main content

1G to 5G Technology - Evolution of Wireless Generations


Cellular wireless evolution
Generation Frequency band PHY features Data rate Spectral Eff. (bps/Hz)
1G 850 MHz FDMA, FM N/A N/A
2G 900 MHz, 1.8 GHz TDMA/CDMA, GMSK/QPSK, FEC, PC 10 Kbps < 1
3G 1.8–2.5 GHz CDMA, QAM 1–40 Mbps 1–8
4G 2–8 GHz OFDMA, SC-FDMA, QAM, MIMO-OFDM 100–600 Mbps 15
5G 1–6 GHz
mm wave (26–28 GHz)
< 1 GHz (massive IoT)
visible light?
massive MIMO, beamforming
D2D, Full duplex, NOMA
LDPC and Polar codes
OFDM & variants (adapted to extremes?)
multi-Gbps several tens

Waveform design is the major change between the generations


Mobile Wireless Generations Specifications
 1G  Voice, Analog traffic, FDMA
 2G  Voice, SMS, CS data transfer, TDMA
 3G  Voice, SMS, PS data transfer, CDMA
 4G  PS data, VOIP, OFDMA
5G OFDMA, NOMA, Beamforming

 

1G

We've all heard about the evolution of G's, or, to put it another way, the evolution of wireless cellular networks from 1G to 5G. 1G (the first generation of wireless networks) was introduced in 1981. Only voice communication (by analog signals) was supported in 1G. It was able to handle a data rate of 2.4 kbps). There was no data communication. AMPS (Advanced mobile phone system), NMTS (nordic mobile phone system), TACS (total access communication system), etc. were the most popular 1G-access technologies at that time. 

📖 Related Topic: FDMA (Frequency Division Multiple Access) was the primary multiple-access technique used in most 1G analog cellular systems.



2G

2G was launched in the mid-1990s, providing PSDN or data communication as well as voice communication. The predecessor technology, 1G, is also referred to as analog. However, on 2G, we were able to communicate via voice and data at 64 kbps. 2G was the first generation of telecommunications that provide internet browsing capabilities. However, the data rate was merely adequate for browsing. New variants of 2G were introduced, such as 2.5G, 2.75G, and so on. The issue with 2G was that it did not meet international standards. In the context of low data rate, higher handover latency, limited capacity of cells, data roaming, etc. - we see several issues in 2G. GSM (global system for mobile communication), CDMA (code division multiple access), IS-95, etc. were the popular 2G access technologies at that time.


2G Modulation Techniques:

Frequency division multiplexing (FDM) and time division multiplexing (FDM) modulation techniques were primarily used in 2G. 2G distributes the entire available frequency spectrum into multiple subbands using FDM. Then, to link many devices, TDM is used for each subband. read more ...


Frequency bands for 2G:

GSM stands for Global System for Mobile Communications. The operating frequency ranged from 900 to 1800 MHz. We've probably all heard about uplink and downlink in 2G or other networks. The frequency band utilized to transfer signals from a mobile station (MS) to a base station is referred to as the uplink frequency (BS). Downlink frequency refers to the frequency utilized to convey data or signals from the BS to the MS.


Bandwidth:

Each channel in 2G has a bandwidth of 200 kHz and is modulated using TDM. We know that we can connect multiple MSs to a single channel using this technique. Using TDM, 2G GSM can connect 8 users simultaneously over a single channel.


The cell coverage of 2G GSM:

Previously, there was the idea of a big cell tower that could transmit its signal over a large area. You can assume that a tall transmitter is located in the center of a city and that it covers the entire area. For example, in 1946, the wireless mobile signal was sent in this manner in New York City. Only 543 users could be added to the network. We couldn't reuse the frequency with that technology.  However, as time went on, the number of users grew rapidly. Then there was the cellular (cellular network) concept. In a cellular 2G GSM network, we can reuse frequencies in cell towers when they are not too close or when interference is minimal. This allowed us a lot of flexibility in terms of connecting multiple devices at once.


Doppler Shift:

In a 2G network, Doppler shift is an inevitable parameter. When MSs travel closer to the BS or cell tower, the received frequency increases. When MSs move away from cell towers, on the other hand, the frequency of received signals decreases. It can be stated mathematically as a Doppler shift, 

It can be stated mathematically as a Doppler shift, 

fD = (v/lambda) * cos(theta), 

where v is the user's velocity and lambda is the operating frequency's wavelength. And theta = angle between BS and MS (theta)

read more ...



3G

The 3G connection became accessible later in 2001. 3G was the first wireless upgrade to bring online multimedia, video conferencing, and other features to the market. A 3G connection proved sufficient for internet video streaming. The main motivation behind 3G technology was to overcome the bandwidth limitation of 2G. WCDMA, CDMA2000, UMTS, etc. were the most popular 3G access technologies at that time. Primarily, 3G was able to handle a data transfer rate of 3.5 Mbps. Later on, we see different extensions of the third-generation network, like, HSDPA, HSUPA, HSPA+, etc. 



4G

In 4G, we observe data speeds of 30-40 Mbps that are satisfactory. However, the number of internet-connected devices is growing every day. 4G was designed to handle a data transfer rate of 300Mbps along with QoS (quality of service). According to Cisco, there will be 50 billion gadgets linked to the internet worldwide by 2020.

As a result, more bandwidth is required to connect more devices to the BS at the same time, and the need for high data rates is increasing. We are now accustomed to learning from video rather than text, such as high-definition video streaming, video conferencing, and so on. These applications necessitate a high data transfer rate.

4G is currently experiencing bandwidth congestion. The amount of data traffic generated by various wireless devices is increasing every day. So, either modern 4G is incapable of managing it, or the bandwidth of recent 4G LTE is insufficient to connect all devices to the internet at the same time. More bandwidth is required. 5G can help us with this.

📡 Core 4G Technologies:



5G

5G will, as we well know, operate at incredibly high frequencies ranging from sub 6 GHz band to millimeter wave band (26 to 100 GHz). It has a large spectrum of resources. Extremely high frequencies, massive MIMO, and beamforming are crucial 5G technologies that will address future telecom network needs or demands. Read More about 5G in detail...

That are also key technologies for 6G, and beyond. Sub-terahertz frequencies are expected to be used for 6G.


Explore 5G Technologies


Also read about

[1] Wireless Communication Projects/Thesis Ideas

Q. What type of multiplexing is widely used in the second-generation (2g and third-generation (3g wireless communication?

A. TDM, FDM, CDMA, WCDMA

Q. What is the typical power range of an LTE signal received on a mobile device?

A. The typical range of received LTE signal's average power is between -44 dBm (excellent) to -140 dBm (bad).

#how cellular communication is different from radio communication? 

What is the communication method that uses symbolic codes for data transmission?

A. Telegraphy. It uses Morse code.





Contact Us

Name

Email *

Message *

Popular Posts

MIMO Channel Matrix | Rank and Condition Number

MIMO / Massive MIMO MIMO Channel Matrix | Rank and Condition...   The channel matrix in wireless communication is a matrix that describes the impact of the channel on the transmitted signal. The channel matrix can be used to model the effects of the atmospheric or underwater environment on the signal, such as the absorption, reflection or scattering of the signal by surrounding objects. When addressing multi-antenna communication, the term "channel matrix" is used. Let's assume that only one TX and one RX are in communication and there's no surrounding object. Here, in our case, we can apply the proper threshold condition to a received signal and get the original transmitted signal at the RX side. However, in real-world situations, we see signal path blockage, reflections, etc.,  (NLOS paths [↗]) more frequently. The obstruction is typically caused by building walls, etc. Multi-antenna communication was introduced to address this issue. It makes diversity app...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...(MATLAB Code + Simulator)

Bit Error Rate (BER) & SNR Guide Analyze communication system performance with our interactive simulators and MATLAB tools. 📘 Theory 🧮 Simulators 💻 MATLAB Code 📚 Resources BER Definition SNR Formula BER Calculator MATLAB Comparison 📂 Explore M-ary QAM, PSK, and QPSK Topics ▼ 🧮 Constellation Simulator: M-ary QAM 🧮 Constellation Simulator: M-ary PSK 🧮 BER calculation for ASK, FSK, and PSK 🧮 Approaches to BER vs SNR Calculation What is Bit Error Rate (BER)? The BER indicates how many corrupted bits are received compared to the total number of bits sent. It is the primary figur...

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 ...

How to Mount Google Drive in Google Colab

How to Mount Google Drive in Google Colab Google Colab provides temporary storage during a session. Any files stored in the /content directory will be deleted when the runtime disconnects. To store datasets, trained models, and results permanently, it is recommended to mount your Google Drive in Colab. Mounting Google Drive allows your notebook to access files directly from your Drive and save outputs there so they remain available even after the Colab session ends. Step 1: Import the Drive Module First import the Google Colab drive module. from google.colab import drive Step 2: Mount Google Drive Run the following command to mount your Google Drive. from google.colab import drive drive.mount('/content/drive') After running the command: A link will appear in the output. Click the link and log in to your Google account. Copy the authentication code provided. Paste the code back into the notebook. Or, a Google authentication page will a...

MATLAB Code for OTFS (Orthogonal Time Frequency Space)

MATLAB Code for OTFS (Orthogonal Time Frequency Space) %% Clear workspace clc; clear; close all ; %% Step 1: OTFS Parameters N_delay = 4; % Number of delay bins (rows) N_doppler = 4; % Number of Doppler bins (columns) N_sym = N_delay * N_doppler; modOrder = 4; % QPSK SNR_dB = 20; % Noise level %% Step 2: Generate random data symbols data = randi([0 modOrder-1], N_sym, 1); txSymbols = pskmod(data, modOrder, pi/4); disp( 'Transmitted Delay-Doppler symbols:' ); disp(reshape(txSymbols, N_delay, N_doppler)); %% Step 3: Map Delay-Doppler → Time-Frequency (ISFFT) % ISFFT: Inverse Symplectic Finite Fourier Transform % 1. Take IDFT along Doppler (columns) % 2. Take DFT along Delay (rows) ddSymbols = reshape(txSymbols, N_delay, N_doppler); % Step 3a: IDFT along columns (Doppler) tfGrid = ifft(ddSymbols, N_doppler, 2); %IFFT (accross columns) along Doppler → spreads in time (Delay → Time) %FFT (accross rows)along Delay → spreads in frequency (Delay → Frequency) % Step 3b: DFT along ...

Wiener Filter in MATLAB

  MATLAB Code  % Wiener Filter Based on Wiener-Hopf Equation % This script demonstrates how to apply the Wiener filter to recover % a reference signal from a noisy signal using the Wiener-Hopf equation. % The filter minimizes the mean squared error between the noisy signal and the reference signal. clear; close all; clc; % Signal Parameters fs = 4000; % Sampling frequency (Hz) T = 1; % Total recording time (seconds) L = T * fs; % Signal length (samples) tt = (0:L-1) / fs; % Time vector ff = (0:L-1) * fs / L; % Frequency vector % Generate Reference Signal (a sinusoid) y = sin(2 * pi * 120 * tt); % Reference sinusoidal signal y = y(:); % Ensure column vector % Create Noisy Signal by Adding Gaussian Noise x = 0.50 * randn(L, 1) + y; % Noisy signal x = x(:); % Ensure column vector % Define Filter Order (Number of Coefficients) N = 200; % Apply Wiener Filter using custom function [xest, b, MSE] = wienerFilt(x, y, N); % Plot Results figure; subplot(411); plot(tt, x, 'k'), hold on, p...

Overmodulation & Distortion in AM

Overmodulation in AM and How It Causes Distortion 1. AM Signal Equation s(t) = A c [1 + μ m(t)] cos(2π f c t) A c = carrier amplitude m(t) = normalized modulating signal (|m(t)| ≤ 1) μ = modulation index 2. Modulation Index μ = A m / A c - Normal AM: 0 < μ ≤ 1 → no distortion - Overmodulation: μ > 1 → distortion occurs 3. Envelope and Overmodulation A(t) = A c [1 + μ m(t)] - For undistorted AM: 1 + μ m(t) ≥ 0 at all times - If μ > 1: 1 + μ m(t) < 0 at negative peaks → carrier flips Example: Let m(t) = cos(2π f m t), A c = 1 V, μ = 1.2 Minimum envelope: A min = A c [1 - 1.2] = -0.2 V Negative amplitude → envelope crosses zero → 180° phase flip 4. Mathematical Consequence -A c cos(θ) = A c cos(θ + π) This phase reversal is what causes distortion in the demodulated signal. 5. Instantaneous AM Signal s...

Phase Modulation (PM) & Demodulation

Advanced Analysis of Phase Modulation Phase Modulation (PM): Theoretical Foundations and Spectral Dynamics 1. Analytical Characterization Phase Modulation (PM) is a subset of Angle Modulation , where the information residing in the message signal \( m(t) \) is mapped linearly onto the instantaneous phase of a high-frequency carrier. Unlike Amplitude Modulation (AM), PM is a non-linear modulation process, resulting in an expansion of the signal bandwidth into an infinite dimensional Hilbert space. \[ S_{PM}(t) = A_c \cos\left[ 2\pi f_c t + \phi(t) \right] = A_c \cos\left[ 2\pi f_c t + K_p m(t) \right] \] The instantaneous frequency \( f_i(t) \) is defined as the time derivative of the total angle: \[ f_i(t) = \frac{1}{2\pi} \frac{d\theta_i(t)}{dt} = f_c + \frac{K_p}{2\pi} \frac{dm(t)}{dt} \] ...