#signalprocessing — Public Fediverse posts

### **Синергия внешнего приема и Wi-Fi Calling: Технический разбор**
Использование внешнего CPE-роутера (Customer Premises Equipment) в связке с технологией Wi-Fi Calling — это не просто «улучшение связи», а создание **автономного узла доступа** в условиях полной изоляции от макросети. В такой архитектуре мы переносим точку дедупликации и обработки сигнала из зоны радио-тени (внутри помещения) непосредственно в зону прямой видимости базовой станции (на крышу или мачту).
#### **1. Архитектурные преимущества «Выносного решения»**
* **Исключение затухания в фидере:** В классических схемах с пассивной антенной сигнал теряет до **0.5–1.0 дБ на метр** коаксиального кабеля. Внешний роутер передает данные по Ethernet (PoE), где потери на дистанции до 100 метров равны нулю.
* **Высокий SINR (Signal-to-Interference-plus-Noise Ratio):** За счет узконаправленных антенн внешнего блока (панельных или параболических) отсекаются интерференционные шумы от соседних базовых станций, что критически важно для стабильности IPsec-туннеля Wi-Fi Calling.
* **Агрегация частот (Carrier Aggregation):** Внешние модемы высоких категорий (Cat.12 и выше) способны суммировать полосы из разных диапазонов (например, B3+B7+B20), обеспечивая канал, достаточный не только для голоса, но и для передачи тяжелого контента параллельно со звонком.
#### **2. Механика взаимодействия**
Когда смартфон подключается к Wi-Fi сети, созданной таким роутером:
1. **IKEv2 аутентификация:** Смартфон инициирует защищенное соединение с ePDG (evolved Packet Data Gateway) оператора.
2. **Виртуальный туннель:** Весь голосовой трафик инкапсулируется в UDP-пакеты. Благодаря внешнему роутеру, джиттер (дрожание фазы) минимален, что предотвращает металлический голос или прерывания.
3. **Бесшовная передача (Handover):** При выходе из здания, если сигнал на улице станет достаточным, сессия переключится на VoLTE без обрыва разговора.
#### **3. Сценарии применения**
* **Бункеры и цокольные этажи:** Где бетон и арматура создают эффект клетки Фарадея.
* **Удаленные промзоны:** Где плотность базовых станций низкая, и смартфон в помещении тратит весь заряд на попытки «достучаться» до сети.
* **Объекты с EW-активностью (РЭБ):** Выносная направленная антенна с высоким коэффициентом усиления позволяет «пробить» помехи за счет узкого луча и пространственной фильтрации.
### **Техническая спецификация системы**

| Параметр | Значение / Описание |
| :--- | :--- |
| **Протокол передачи** | Voice over Wi-Fi (IEEE 802.11 / 3GPP TS 23.402) |
| **Транспортный протокол** | IPsec (IKEv2) через внешний LTE/5G канал |
| **Усиление антенны** | от 15 dBi (панель) до 27 dBi (сетчатый параболик) |
| **Метод питания** | Passive PoE или 802.3af/at (по одной «витой паре») |
| **Кодеки** | AMR-WB (G.722.2) для HD Voice качества |

> **Атрибуция:** Анализ основан на архитектуре сетей IMS (IP Multimedia Subsystem) и стандартах развертывания Outdoor CPE для фиксированного беспроводного доступа (FWA).
>
#NetworkEngineering #SystemIntegration #LTE_CPE #WiFiCalling #HighGain #SignalProcessing #VoWiFi #Infrastructure #Connectivity #TechDeepDive

### **Синергия внешнего приема и Wi-Fi Calling: Технический разбор**
Использование внешнего CPE-роутера (Customer Premises Equipment) в связке с технологией Wi-Fi Calling — это не просто «улучшение связи», а создание **автономного узла доступа** в условиях полной изоляции от макросети. В такой архитектуре мы переносим точку дедупликации и обработки сигнала из зоны радио-тени (внутри помещения) непосредственно в зону прямой видимости базовой станции (на крышу или мачту).
#### **1. Архитектурные преимущества «Выносного решения»**
* **Исключение затухания в фидере:** В классических схемах с пассивной антенной сигнал теряет до **0.5–1.0 дБ на метр** коаксиального кабеля. Внешний роутер передает данные по Ethernet (PoE), где потери на дистанции до 100 метров равны нулю.
* **Высокий SINR (Signal-to-Interference-plus-Noise Ratio):** За счет узконаправленных антенн внешнего блока (панельных или параболических) отсекаются интерференционные шумы от соседних базовых станций, что критически важно для стабильности IPsec-туннеля Wi-Fi Calling.
* **Агрегация частот (Carrier Aggregation):** Внешние модемы высоких категорий (Cat.12 и выше) способны суммировать полосы из разных диапазонов (например, B3+B7+B20), обеспечивая канал, достаточный не только для голоса, но и для передачи тяжелого контента параллельно со звонком.
#### **2. Механика взаимодействия**
Когда смартфон подключается к Wi-Fi сети, созданной таким роутером:
1. **IKEv2 аутентификация:** Смартфон инициирует защищенное соединение с ePDG (evolved Packet Data Gateway) оператора.
2. **Виртуальный туннель:** Весь голосовой трафик инкапсулируется в UDP-пакеты. Благодаря внешнему роутеру, джиттер (дрожание фазы) минимален, что предотвращает металлический голос или прерывания.
3. **Бесшовная передача (Handover):** При выходе из здания, если сигнал на улице станет достаточным, сессия переключится на VoLTE без обрыва разговора.
#### **3. Сценарии применения**
* **Бункеры и цокольные этажи:** Где бетон и арматура создают эффект клетки Фарадея.
* **Удаленные промзоны:** Где плотность базовых станций низкая, и смартфон в помещении тратит весь заряд на попытки «достучаться» до сети.
* **Объекты с EW-активностью (РЭБ):** Выносная направленная антенна с высоким коэффициентом усиления позволяет «пробить» помехи за счет узкого луча и пространственной фильтрации.
### **Техническая спецификация системы**

| Параметр | Значение / Описание |
| :--- | :--- |
| **Протокол передачи** | Voice over Wi-Fi (IEEE 802.11 / 3GPP TS 23.402) |
| **Транспортный протокол** | IPsec (IKEv2) через внешний LTE/5G канал |
| **Усиление антенны** | от 15 dBi (панель) до 27 dBi (сетчатый параболик) |
| **Метод питания** | Passive PoE или 802.3af/at (по одной «витой паре») |
| **Кодеки** | AMR-WB (G.722.2) для HD Voice качества |

> **Атрибуция:** Анализ основан на архитектуре сетей IMS (IP Multimedia Subsystem) и стандартах развертывания Outdoor CPE для фиксированного беспроводного доступа (FWA).
>
#NetworkEngineering #SystemIntegration #LTE_CPE #WiFiCalling #HighGain #SignalProcessing #VoWiFi #Infrastructure #Connectivity #TechDeepDive

#CFP

Recent Advances in Music Processing

Special Session at APSIPA ASC 2026 exploring music signal processing, computational musicology, deep learning for music, interactive music systems, MIR, and AI-based music research.

📍 Hanoi, Vietnam
📅 9–12 November 2026

https://www.apsipa2026.org/call_special_session.html

Organizers:
Tetsuro Kitahara ([email protected]) &
Eita Nakamura

Deadline: 15/05/2026

#MusicTechnology #MIR #MusicInformationRetrieval #SignalProcessing #AI #ComputationalMusicology

#CFP

Recent Advances in Music Processing

Special Session at APSIPA ASC 2026 exploring music signal processing, computational musicology, deep learning for music, interactive music systems, MIR, and AI-based music research.

📍 Hanoi, Vietnam
📅 9–12 November 2026

https://www.apsipa2026.org/call_special_session.html

Organizers:
Tetsuro Kitahara ([email protected]) &
Eita Nakamura

Deadline: 15/05/2026

#MusicTechnology #MIR #MusicInformationRetrieval #SignalProcessing #AI #ComputationalMusicology

#CFP

Recent Advances in Music Processing

Special Session at APSIPA ASC 2026 exploring music signal processing, computational musicology, deep learning for music, interactive music systems, MIR, and AI-based music research.

📍 Hanoi, Vietnam
📅 9–12 November 2026

https://www.apsipa2026.org/call_special_session.html

Organizers:
Tetsuro Kitahara ([email protected]) &
Eita Nakamura

Deadline: 15/05/2026

#MusicTechnology #MIR #MusicInformationRetrieval #SignalProcessing #AI #ComputationalMusicology

#CFP

Recent Advances in Music Processing

Special Session at APSIPA ASC 2026 exploring music signal processing, computational musicology, deep learning for music, interactive music systems, MIR, and AI-based music research.

📍 Hanoi, Vietnam
📅 9–12 November 2026

https://www.apsipa2026.org/call_special_session.html

Organizers:
Tetsuro Kitahara ([email protected]) &
Eita Nakamura

Deadline: 15/05/2026

#MusicTechnology #MIR #MusicInformationRetrieval #SignalProcessing #AI #ComputationalMusicology

#CFP

Recent Advances in Music Processing

Special Session at APSIPA ASC 2026 exploring music signal processing, computational musicology, deep learning for music, interactive music systems, MIR, and AI-based music research.

📍 Hanoi, Vietnam
📅 9–12 November 2026

https://www.apsipa2026.org/call_special_session.html

Organizers:
Tetsuro Kitahara ([email protected]) &
Eita Nakamura

Deadline: 15/05/2026

#MusicTechnology #MIR #MusicInformationRetrieval #SignalProcessing #AI #ComputationalMusicology

here's the STELLA paper:

https://doi.org/10.1016/j.acra.2025.11.040

#radiology #science #medicine #webdev #biomedical #image #imageProcessing #signalProcessing #medicalImaging #imaging #CT #MRI

here's the STELLA paper:

https://doi.org/10.1016/j.acra.2025.11.040

#radiology #science #medicine #webdev #biomedical #image #imageProcessing #signalProcessing #medicalImaging #imaging #CT #MRI

here's the STELLA paper:

https://doi.org/10.1016/j.acra.2025.11.040

#radiology #science #medicine #webdev #biomedical #image #imageProcessing #signalProcessing #medicalImaging #imaging #CT #MRI

here's the STELLA paper:

https://doi.org/10.1016/j.acra.2025.11.040

#radiology #science #medicine #webdev #biomedical #image #imageProcessing #signalProcessing #medicalImaging #imaging #CT #MRI

here's the STELLA paper:

https://doi.org/10.1016/j.acra.2025.11.040

#radiology #science #medicine #webdev #biomedical #image #imageProcessing #signalProcessing #medicalImaging #imaging #CT #MRI

What if birdsong isn’t random?
Lucio Arese is mapping bird communication into structured data: → identifying repeating patterns → clustering signals → analyzing sequences over time
What humans hear as noise may contain real structure.
This is bigger than biology.
It’s a preview of what happens when AI meets signal processing: non-human communication becoming interpretable.
When sound becomes data, meaning can emerge.
#AI #Data #SignalProcessing #FutureOfAI

just learned from the Stanford Alumni Magazine that Bernard Widrow passed away last September... inventor of the least-mean-square filter, which despite the funny name (it sounds a lot like least squares, minimum residual, etc.) was one of the most important developments in late 20th century adaptive signal processing and digital control. a true pioneer of modern engineering!

https://en.wikipedia.org/wiki/Least_mean_squares_filter

#StanfordUniversity #LeastMeanSquare #LMS #signalProcessing #adaptiveFilter

just learned from the Stanford Alumni Magazine that Bernard Widrow passed away last September... inventor of the least-mean-square filter, which despite the funny name (it sounds a lot like least squares, minimum residual, etc.) was one of the most important developments in late 20th century adaptive signal processing and digital control. a true pioneer of modern engineering!

https://en.wikipedia.org/wiki/Least_mean_squares_filter

#StanfordUniversity #LeastMeanSquare #LMS #signalProcessing #adaptiveFilter

just learned from the Stanford Alumni Magazine that Bernard Widrow passed away last September... inventor of the least-mean-square filter, which despite the funny name (it sounds a lot like least squares, minimum residual, etc.) was one of the most important developments in late 20th century adaptive signal processing and digital control. a true pioneer of modern engineering!

https://en.wikipedia.org/wiki/Least_mean_squares_filter

#StanfordUniversity #LeastMeanSquare #LMS #signalProcessing #adaptiveFilter

just learned from the Stanford Alumni Magazine that Bernard Widrow passed away last September... inventor of the least-mean-square filter, which despite the funny name (it sounds a lot like least squares, minimum residual, etc.) was one of the most important developments in late 20th century adaptive signal processing and digital control. a true pioneer of modern engineering!

https://en.wikipedia.org/wiki/Least_mean_squares_filter

#StanfordUniversity #LeastMeanSquare #LMS #signalProcessing #adaptiveFilter

just learned from the Stanford Alumni Magazine that Bernard Widrow passed away last September... inventor of the least-mean-square filter, which despite the funny name (it sounds a lot like least squares, minimum residual, etc.) was one of the most important developments in late 20th century adaptive signal processing and digital control. a true pioneer of modern engineering!

https://en.wikipedia.org/wiki/Least_mean_squares_filter

#StanfordUniversity #LeastMeanSquare #LMS #signalProcessing #adaptiveFilter

How Passive Radar Works

https://www.passiveradar.com/how-passive-radar-works/

#HackerNews #PassiveRadar #Technology #RadarSystems #Innovation #SignalProcessing

How Passive Radar Works

https://www.passiveradar.com/how-passive-radar-works/

#HackerNews #PassiveRadar #Technology #RadarSystems #Innovation #SignalProcessing

How Passive Radar Works

https://www.passiveradar.com/how-passive-radar-works/

#HackerNews #PassiveRadar #Technology #RadarSystems #Innovation #SignalProcessing

How Passive Radar Works

https://www.passiveradar.com/how-passive-radar-works/

#HackerNews #PassiveRadar #Technology #RadarSystems #Innovation #SignalProcessing

the European Association for Signal Processing has a public library of PhD theses: https://theses.eurasip.org/ #phdchat #signalprocessing

the European Association for Signal Processing has a public library of PhD theses: https://theses.eurasip.org/ #phdchat #signalprocessing

the European Association for Signal Processing has a public library of PhD theses: https://theses.eurasip.org/ #phdchat #signalprocessing

the European Association for Signal Processing has a public library of PhD theses: https://theses.eurasip.org/ #phdchat #signalprocessing

I've gone straight down the rabbit hole on an Analog TV simulation. This page has the details and links to the iOS app (free download): https://analogtv.ambor.com/#

#CRT #AnalogTV #RetroTech #iOSDev #SignalProcessing #NTSC #PAL #SECAM #IndieApp

I've gone straight down the rabbit hole on an Analog TV simulation. This page has the details and links to the iOS app (free download): https://analogtv.ambor.com/#

#CRT #AnalogTV #RetroTech #iOSDev #SignalProcessing #NTSC #PAL #SECAM #IndieApp

I've gone straight down the rabbit hole on an Analog TV simulation. This page has the details and links to the iOS app (free download): https://analogtv.ambor.com/#

#CRT #AnalogTV #RetroTech #iOSDev #SignalProcessing #NTSC #PAL #SECAM #IndieApp

We are building out a new curriculum day for our #ComputationalNeuroscience course focused on time series analysis and #SignalProcessing. We're looking for 5-10 volunteer contributors w #CompNeuro & #DSP experience.

This is a #volunteer position. Learn more & apply: https://neuromatch.io/volunteer/

#Neuroscience #DataScience #OpenScience #volunteer #BuildYourCV

We are building out a new curriculum day for our #ComputationalNeuroscience course focused on time series analysis and #SignalProcessing. We're looking for 5-10 volunteer contributors w #CompNeuro & #DSP experience.

This is a #volunteer position. Learn more & apply: https://neuromatch.io/volunteer/

#Neuroscience #DataScience #OpenScience #volunteer #BuildYourCV

We are building out a new curriculum day for our #ComputationalNeuroscience course focused on time series analysis and #SignalProcessing. We're looking for 5-10 volunteer contributors w #CompNeuro & #DSP experience.

This is a #volunteer position. Learn more & apply: https://neuromatch.io/volunteer/

#Neuroscience #DataScience #OpenScience #volunteer #BuildYourCV

We are building out a new curriculum day for our #ComputationalNeuroscience course focused on time series analysis and #SignalProcessing. We're looking for 5-10 volunteer contributors w #CompNeuro & #DSP experience.

This is a #volunteer position. Learn more & apply: https://neuromatch.io/volunteer/

#Neuroscience #DataScience #OpenScience #volunteer #BuildYourCV

We are building out a new curriculum day for our #ComputationalNeuroscience course focused on time series analysis and #SignalProcessing. We're looking for 5-10 volunteer contributors w #CompNeuro & #DSP experience.

This is a #volunteer position. Learn more & apply: https://neuromatch.io/volunteer/

#Neuroscience #DataScience #OpenScience #volunteer #BuildYourCV

(1/2)
I found a nice improvement to the Constant-Q Sliding DFT¹.

Using single precision calculation (32-bit float) generates some remanent noise because of the recursive nature of the algorithm: a running sum combined with complex rotations.

Replacing the complex multiply in eq. 3 for the twiddle factors (outer exponential) with the Martin Vicanek’s quadrature oscillator² helps a lot in the low frequencies. About 30 dB of improvement here, almost no extra CPU cost.

¹ A transform turning a PCM signal into a frequency spectrum. https://www.dafx.de/paper-archive/details.php?id=QMFQa1rIAM7mwu9tMIZAlg

² https://vicanek.de/articles/QuadOsc.pdf

#audio #DSP #SignalProcessing #CQSDFT #DFT #Spectrogram

I'm on this project where we want to do #realtime #radar but are sort of starting with nothing (apart from world-class radar transmitters, receivers and expertise...)

One very smart but non-#software person wrote a bunch of good #signalprocessing #code and some "gets the job done" #gui code

Or it did until we went higher bandwidth

Last week I rewrote all the non-sigproc parts into #pyqt and #pyqtgraph. Today I benchmarked both.

Exactly the same speed....except pyqtgraph is

THREE ORDERS OF MAGNITUDE

faster than #matplotlib

#python peeps, please hear me. mpl has its place and uses. High data rate animated displays is not that place.

I'm on this project where we want to do #realtime #radar but are sort of starting with nothing (apart from world-class radar transmitters, receivers and expertise...)

One very smart but non-#software person wrote a bunch of good #signalprocessing #code and some "gets the job done" #gui code

Or it did until we went higher bandwidth

Last week I rewrote all the non-sigproc parts into #pyqt and #pyqtgraph. Today I benchmarked both.

Exactly the same speed....except pyqtgraph is

THREE ORDERS OF MAGNITUDE

faster than #matplotlib

#python peeps, please hear me. mpl has its place and uses. High data rate animated displays is not that place.

I'm on this project where we want to do #realtime #radar but are sort of starting with nothing (apart from world-class radar transmitters, receivers and expertise...)

One very smart but non-#software person wrote a bunch of good #signalprocessing #code and some "gets the job done" #gui code

Or it did until we went higher bandwidth

Last week I rewrote all the non-sigproc parts into #pyqt and #pyqtgraph. Today I benchmarked both.

Exactly the same speed....except pyqtgraph is

THREE ORDERS OF MAGNITUDE

faster than #matplotlib

#python peeps, please hear me. mpl has its place and uses. High data rate animated displays is not that place.

I'm on this project where we want to do #realtime #radar but are sort of starting with nothing (apart from world-class radar transmitters, receivers and expertise...)

One very smart but non-#software person wrote a bunch of good #signalprocessing #code and some "gets the job done" #gui code

Or it did until we went higher bandwidth

Last week I rewrote all the non-sigproc parts into #pyqt and #pyqtgraph. Today I benchmarked both.

Exactly the same speed....except pyqtgraph is

THREE ORDERS OF MAGNITUDE

faster than #matplotlib

#python peeps, please hear me. mpl has its place and uses. High data rate animated displays is not that place.

I'm on this project where we want to do #realtime #radar but are sort of starting with nothing (apart from world-class radar transmitters, receivers and expertise...)

One very smart but non-#software person wrote a bunch of good #signalprocessing #code and some "gets the job done" #gui code

Or it did until we went higher bandwidth

Last week I rewrote all the non-sigproc parts into #pyqt and #pyqtgraph. Today I benchmarked both.

Exactly the same speed....except pyqtgraph is

THREE ORDERS OF MAGNITUDE

faster than #matplotlib

#python peeps, please hear me. mpl has its place and uses. High data rate animated displays is not that place.

Engineering Signal Analysis - From Fourier to filtering
https://books.open.tudelft.nl/home/catalog/book/247

#freebook #openbook #book #dsp #fourier #filtering #pdf #signalanalysis #signalprocessing #audio #sound

Engineering Signal Analysis - From Fourier to filtering
https://books.open.tudelft.nl/home/catalog/book/247

#freebook #openbook #book #dsp #fourier #filtering #pdf #signalanalysis #signalprocessing #audio #sound

Engineering Signal Analysis - From Fourier to filtering
https://books.open.tudelft.nl/home/catalog/book/247

#freebook #openbook #book #dsp #fourier #filtering #pdf #signalanalysis #signalprocessing #audio #sound

Engineering Signal Analysis - From Fourier to filtering
https://books.open.tudelft.nl/home/catalog/book/247

#freebook #openbook #book #dsp #fourier #filtering #pdf #signalanalysis #signalprocessing #audio #sound

Engineering Signal Analysis - From Fourier to filtering
https://books.open.tudelft.nl/home/catalog/book/247

#freebook #openbook #book #dsp #fourier #filtering #pdf #signalanalysis #signalprocessing #audio #sound

Given everything that we can do with noise-cancelling headphones and signal processing, why are they not able to cancel out the whine of the drones when doing follow-cam in sporting events? 🧐

#WinterOlympics #Drones #SignalProcessing #AudioProcessing

Given everything that we can do with noise-cancelling headphones and signal processing, why are they not able to cancel out the whine of the drones when doing follow-cam in sporting events? 🧐

#WinterOlympics #Drones #SignalProcessing #AudioProcessing

Given everything that we can do with noise-cancelling headphones and signal processing, why are they not able to cancel out the whine of the drones when doing follow-cam in sporting events? 🧐

#WinterOlympics #Drones #SignalProcessing #AudioProcessing

Given everything that we can do with noise-cancelling headphones and signal processing, why are they not able to cancel out the whine of the drones when doing follow-cam in sporting events? 🧐

#WinterOlympics #Drones #SignalProcessing #AudioProcessing

Given everything that we can do with noise-cancelling headphones and signal processing, why are they not able to cancel out the whine of the drones when doing follow-cam in sporting events? 🧐

#WinterOlympics #Drones #SignalProcessing #AudioProcessing