Skip to main content

UWB | Power Usage, Applications and Limitations


 
3. AoA & AoD detection:

Small-scale fading refers to rapid changes in the received signal caused by factors such as angle of arrival and departure (AOA and AOD), multipath, doppler frequency shift, and so on. UWB can also be used to calculate the angle of arrival and departure for a device. This also provides an additional benefit in terms of improving communication. It determines the AoA and AoD by detecting the phase difference between preceding and succeeding antenna elements in the received signal.


How much power does UWB use:

It adopts a pulse method that involves a huge spectrum as compared to other protocols. There are numerous advantages to employing an ultra-wideband. It uses less energy. We broadcast a narrow pulse, like in UWB band communication, with a duty cycle of roughly 1%. So, we do require not much power for such short-range communication. Just for simplicity, consider OFF-ON keying, in which we send bit '1' by simply dedicating some energy to it. We also send bit '0' by switching off the circuits. A similar situation occurs in this case. The pulse signal has a periodic cycle in this case. We assign power to a very small portion of that periodic cycle or period compared to the entire periodic time; the rest of the time, we send no power. However, because we use it for short-range communication, it easily overcomes the noise level.

Because UWB runs at such a high frequency, multiple reflections and refraction are a distinct possibility. As a result, the Saleh Valenzuala model is widely used in such bands. It's a clustered channel model built on the amplitude and time delay models. Because we keep the duty cycle of UWB low and assign less power, multi-paths or MPCs don't interact as much due to reflection or refraction. Because it is designed for short-range communication, it quickly overcomes noise even while transferring less power.

UWB positioning range:

UWB's range is less than half that of Wi-Fi's. Probably 50 meters. However, in practice, the location accuracy of UWB-enabled sensors and devices is less than 50 centimeters.


Applications:

Ultra-wideband (UWB) is used in various WSNs (wireless sensor networks), sensors (motion sensor, temperature sensor, light sensor, etc.), Real-time location detectors, AirTag, RFID, Digital Key, Signaling, Large data transfers, Radar, etc.

This frequency band was used in IEEE 802.15.4a standard and WPANs.


Limitations of UWB:

Short-range communication protocol
It doesn't technically use a carrier signal. Consequently, receiver signal processing may sometimes take time.


Also Read:

[1] MATLAB code for UWB modulation


Contact Us

Name

Email *

Message *

Popular Posts

CMOS Logic Gates: Inverter, NAND, and NOR

CMOS Logic Gates: Inverter, NAND, and NOR Complementary metal–oxide–semiconductor (CMOS) technology forms the backbone of modern digital IC design. Patented by Frank Wanlass in 1963 ( US patent 3,356,858 ), CMOS enables low-power, high-speed, and noise-immune logic circuits. CMOS gates, including inverters, NAND, and NOR, are widely used in both large-scale and small-scale integrated circuits due to their efficiency and versatility. CMOS Inverter A CMOS inverter consists of a complementary pair of PMOS and NMOS transistors. The PMOS transistor connects to the supply voltage V DD , while the NMOS connects to ground. The input voltage V IN controls both gates, and the output voltage V OUT is taken from the connected drains. CMOS inverters are highly energy-efficient and produce minimal heat due to their comple...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Download Papers and Solutions Exam Pattern Preparation Tips FAQs More Home / Engineering & Other Exams / UGC NET 2026 PYQ 📊 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 2026 - Question Paper Download PDF June 202...

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. ...

Decision Feedback Equalizer (DFE) in MATLAB

  MATLAB Code M = 4; % QPSK numSymbols = 10000; numTrainingSymbols = 5000; chtaps = [1 0.5*exp(1i*pi/6) 0.1*exp(-1i*pi/8)]; % Generate QPSK symbols data = randi([0 M-1], numSymbols, 1); tx = pskmod(data, M, pi/4); % DFE setup eq = comm.DecisionFeedbackEqualizer; eq.ReferenceTap = 1; eq.NumForwardTaps = 5; eq.NumFeedbackTaps = 3; % SNR sweep snrVec = 0:5:25; % 0,5,10,...25 dB berBefore = zeros(size(snrVec)); berAfter = zeros(size(snrVec)); for k = 1:length(snrVec) % Apply channel and AWGN rx = awgn(filter(chtaps,1,tx), snrVec(k), 'measured' ); % BER before equalization rxDataNoEq = pskdemod(rx, M, pi/4); [~, berBefore(k)] = biterr(data, rxDataNoEq); % Equalize [y,~,~] = eq(rx, tx(1:numTrainingSymbols)); % Phase correction phaseOffset = angle(mean(conj(tx(1:numTrainingSymbols)) .* y(1:numTrainingSymbols))); yCorrected = y * exp(-1i*phaseOffset); % BER after equalization rxDataEq = pskdemod(yCorrected, M, pi/4); [...

Flat vs Frequency Selective Online Simulator

Flat vs Frequency Selective Online Simulator Channel Type Without Fading Flat Fading Multipaths Nakagami m SNR(dB) Run Simulation Input Signal Signal After Fading Constellation Diagram BER vs SNR Explore Advanced Flat vs Frequency-Selective Fading Simulator Want to see these equations in action? Visualize it. Launch Simulator Tool Flat Fading and Frequency-Selective Fading Effects of Multipath Components and the Nakagami-m Parameter 1. Flat Fading Flat fading occurs when the signal bandwidth is smaller than the channel's coherence bandwidth, meaning that all frequency components of the transmitted signal experience approximately the same fading. It is typically associated with narrowband signals, where the multipath delay spread is small relative to the symbol duration. ...

MUSIC Algorithm Explained (with MATLAB + Simulator)

Practical Implementation of the MUSIC Algorithm The focus is on how the algorithm works computationally , not just theory, and it explains the denominator (a H E n E n H a) mathematically and intuitively. 1. Introduction The MUSIC (Multiple Signal Classification) algorithm is a high-resolution method used in signal processing and array processing to estimate the Direction of Arrival (DOA) of signals received by a sensor array. Unlike classical beamforming methods, MUSIC uses eigenvector decomposition of the covariance matrix to separate the signal subspace and noise subspace , allowing it to achieve much higher angular resolution. In practical implementations, MUSIC works by: Simulating or collecting array signals Computing the covariance matrix Performing eigenvalue decomposition Separating signal and noise subspaces Scanning possible angles using a steering vector Constructing a pseudo-spectrum where peaks indicate signal directions 2. Signal Mo...

Superheterodyne Receiver Online Simulator

Superheterodyne Receiver Simulator Simulation Controls Message Frequency (Hz): Carrier Frequency (Hz): Intermediate Frequency (Hz): Sampling Frequency (Hz): Simulation Duration (s): Run Simulation Signal Plots Numerical Values (first 10 samples) Superheterodyne Receiver Workflow The superheterodyne receiver converts a received RF signal to an intermediate frequency (IF) to simplify filtering and amplification, and finally recovers the original message signal. Steps: Input Message Signal: A low-frequency signal m(t) (e.g., sine wave). RF Modulation (AM): The message modulates the carrier with amplitude modulation: RF(t) = [1 + K_a * m(t)] * cos(2Ï€ f_c t) Mixing with Local Oscillator (LO): The RF signal is multiplied by a local oscillator LO(t) = cos(2Ï€ f_LO t) to produce: IF(t) = RF(t) * LO(t) Intermediate Frequency Filtering: A low-pass filter extracts t...

Linear vs Circular Convolution

Linear vs Circular Convolution Linear convolution vs circular convolution Linear convolution (what nature does) If: x[n] = transmitted signal h[n] = channel impulse response (multipath) Then the received signal is: y[n] = x[n] * h[n] This means: Past symbols spill into future symbols Causes inter-symbol interference (ISI) DFT of y[n] is not a simple product Circular convolution (what DFT assumes) The DFT assumes periodic signals : y[n] = x[n] ⊛ h[n], where indices wrap around modulo N Only under circular convolution does the DFT satisfy: Y[k] = X[k] · H[k] This is what enables one-tap frequency-domain equalization . What happens in the real channel (linear convolution) The channel performs linear convolution: y[n] = Σ l=0 Lh−1 h[l] x[n-l] But because: CP absorbs the “spillover” Receiver discards CP before DFT The useful part of the received symbol becomes: y[n] = Σ l=0 Lh−1 h[l] x[(n-l) mod N] Modulo inde...