Skip to main content

What are the main lobe and side lobes in Beamforming

 

 What are the main lobe and side lobes in Beamforming?

You've probably noticed that in the diagram of beamforming, there are two types of lobes in beamforming patterns. One is the main lobe, while the others are side lobes. We intend to communicate with receivers with a stronger directional path from the transmitter when we produce beams for wireless communication. We can also see side lobes in this scenario. These side lobes, on the other hand, are not necessary for effective communication. As a result, we take various procedures to remove those side lobes or to reduce the number of side lobes as much as feasible; otherwise, inter-symbol interference occurs, and signal quality suffers.

Figure: Illustration of Main Lobe and Side lobes, where the x-axis denotes the angle of arrival (AOA) and angle of departure (AOD), respectively, while, the y-axis denotes the gain/power in dB (decibel).
   

In the case of MIMO antennas, our major goal is to reduce inter-symbol interface (ISI) by minimizing the number of side lobes, therefore we deploy antenna elements at half-wavelength intervals. It's a common practice to increase the power of the main lobe while reducing the power of the side lobes.


How to plot Main Lobes and Side lobes

The plotting of the main lobe and side lobes is not difficult. To begin, measure the received power at the receiver for a specific angle of arrival or departure (AOA/AOD).

For Example

At 28 GHz, UMi - LOS, 372-meter TX-RX Separation, Transmitted Power 30 dBm


The received power changes with parameters like the angle of arrival at the receiver, as seen in the example above.



We've plotted the graph of received power against the angle of arrival of the received signal in the diagram above. These are termed side lobes.

What causes the lobes to form?

Assume we have multiple transmitting antennas. Now, we gradually shift the phases of the antennas (using phase shifters (PSs) or manually), and the signal focuses on the resulting phase angles of those antennas.

# mimo beamforming
 

Further Reading

  1.  How Windowing Affects Your Periodogram (Mainlobe Power & Sidelobe Power)
  2. Why Half-Power (−3 dB) Is Used 
📊 MATLAB & ONLINE SIMULATIONS (Web-Based)
🎓 GATE & UGC - NET SOLUTIONS
📡 WIRELESS & SIGNAL PROCESSING


Contact Us

Name

Email *

Message *

Popular Posts

Q-function in BER vs SNR Calculation (with Simulation)

Q-function in BER vs. SNR Calculation In digital communications and signal processing, the Q-function plays a significant role in predicting system reliability. It allows engineers to quantify the probability that Gaussian noise will exceed a specific threshold, causing a bit error. What is the Q-function? The Q-function is a mathematical function representing the tail probability of the standard normal (Gaussian) distribution. It is the complementary cumulative distribution function (CCDF) of a standard Gaussian distribution. Q(x) = (1 / √(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt Q-Function Interactive Simulator Move the slider to see how the "Tail Probability" (the area in red) changes. This area represents the Probability of Error (BER) . Threshold Distance ( x ) — (Simulates Increasing SNR) x = 1.0 Q(x) = 0.1587 ...
Read more

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 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 figure of merit f...
Read more

Pulse Width Modulation (PWM)

Pulse-width modulation (PWM), or pulse-duration modulation (PDM), is a method of controlling the average power delivered by an electrical signal.   Fig: An example of PWM in an idealized inductor driven by a blue line voltage source modulated as a series of sawtooth pulses, resulting in a red line current in the inductor.    Generating a PWM Signal The simplest way to generate a PWM signal is the intersection method, which requires only a sawtooth or a triangle waveform (easily generated using a simple oscillator) and a comparator. When the value of the reference signal is more than the modulation waveform, the PWM signal (magenta) is in the high state; otherwise, it is in the low state.      Duty cycle A low duty cycle equates to low power because the power is off for most of the time; the word duty cycle reflects the ratio of "on" time to the regular interval or "period" of time. The duty cycle is measured in percent, with 100% representing full o...
Read more

Frequency Shift Keying (FSK) Modulation & Demodulation (with Simulation)

Frequency Shift Keying (FSK) Theoretical Foundations: Frequency Shift Keying (FSK) is a discrete frequency modulation scheme wherein the digital information is encoded via instantaneous shifts in the carrier signal's frequency. The fundamental implementation is Binary FSK (BFSK), which maps binary data onto two distinct, discrete spectral states. A binary '1' (the "mark" state) is represented by a carrier frequency \( f_1 \), while a binary '0' (the "space" state) corresponds to frequency \( f_2 \). Each symbol is sustained for a bit interval denoted by \( T_b \). FSK Transmitter Characterization: The mathematical model for the modulated BFSK output \( s(t) \) is defined as: \[ s(t) = \begin{cases} A_c \cos(2\pi f_1 t), & \text{for } m = 1 \\ A_c \cos(2\pi f_2 t), & \text{for } m = 0 \end{cases} \] ...
Read more

FFT Butterfly Method Explained (with Example of 4-point DFT)

  FFT Using Butterfly Method Given: x[n] = {0, 1, 2, 3} Step 1: Split into Even & Odd Even indices: x e = {0, 2} Odd indices: x o = {1, 3} Step 2: 2-point DFT For any {a, b}: DFT = {a + b, a - b} Even Part: E = {0+2, 0-2} = {2, -2} Odd Part: O = {1+3, 1-3} = {4, -2} Step 3: Combine Using Butterfly X[k] = E[k] + W k O[k] X[k + N/2] = E[k] - W k O[k] For N = 4: W 0 = 1 W 1 = -j Final Calculations X[0] = 2 + 4 = 6 X[2] = 2 - 4 = -2 X[1] = -2 + (-j)(-2) = -2 + 2j X[3] = -2 - (-j)(-2) = -2 - 2j Final Answer: X[k] = {6, -2 + 2j, -2, -2 - 2j} Try Interactive Online Simulations Interactive FFT Online Simulator (For understanding Fundamentals)  Interactive FFT Online Simulator (Analyze .CSV, .MP3, .MP4, etc. Further Reading Fourier Transform OFDM Return to Fourier Transform Main Page →
Read more

Design of CMOS Flip-Flops (SR, D, JK)

Design of CMOS Flip-Flops (SR, D, JK) A flip-flop or latch is a circuit with two stable states, used to store state information. It is the basic storage element in sequential logic and a fundamental building block in digital electronics systems, including computers and communication devices. Flip-flops and latches act as data storage elements for states, pulse counting, and synchronization of variably-timed input signals to a reference clock. Flip-flops can be transparent/opaque (latches) or clocked (synchronous, edge-triggered). Latches are level-sensitive, while flip-flops are edge-sensitive. In sequential logic, the output depends on current inputs and previous states. Fig.1 shows a sequential circuit combining a combinational block and a memory element. ...
Read more

AM Modulation Online Simulator

Amplitude Modulation Simulator s AM (t) = A c [1 + k a m(t)] cos(ω c t) where, ω = 2πf & k a = Amplitude Sensitivity Modulation index, μ = k a A m Message Frequency (fm): Carrier Frequency (fc): Carrier Amplitude (Ac): Modulation Index (m = Am / Ac):
Read more