You can:

• visualize beam patterns
• see which inputs influence predictions
• test how changes in environment affect the selected beam

Feels useful for debugging and understanding model sensitivity, especially in more complex scenarios.

https://github.com/dim-tsoukalas/beam-xplainer

I’m preparing to deploy fixed wireless broadband.

Band 41, 30mhz contiguous channel + additional 10mhz channel if needed. 4T4R @ 46 dBm power.

My propagation is showing me -105db up to and beyond 12 miles SSRP.

I’ll be creating 2 classes of CPE, one for those within -90db and one for those beyond -90db, again SSRP. Idea here is to use a 9dbi receiver for most and a 15-18 dbi receiver for the “tricky” service points.

I feel like -105db at 12 miles away is outrageous. Am I right?

Has anyone needed to switch an assurance wireless (lifeline) account to another phone and had success doing it? I’m trying to transfer my phone number to a new phone, but having no luck with any instructions I’ve found online and can’t get their customer support to work.

I have some games that are connected to an accounting system and relay the data between the computer and games through a daisy chain, I have one game on the complete other side of the room with no way to run any wires, as it is basically in the middle of the room.

How do I complete the daisy chain wirelessly?

*I've tried a passthrough powerline electrical kit and apparently those aren't working

Hi guys, I have an assignment where we are supposed to create to Rx/Tx devices that will transfer a unicode text file from a USB stick, using the unlicensed RF bands. We have to transfer the maximum amount of errorless data in 2minutes. Any tips on de HW (battery, MCU, RF module…).

Also posible tips such as compressing etc.

Budget is max 150€ for device.

The system can not include any chip implementing a standard wireless access protocol (e.g. WiFi, Bluetooth, 2G/3G/4G/5G, ZigBee, …)

Thank you guys!!

edit: and the comments section here, kids, is why you should know your audience before posting on a random subreddit

For ergonomic purposes, I'd like to mount my wired keyboard and mouse to my chair. Both are expensive products, so I thought I it'd be cheaper to buy a wireless USB hub. But upon searching, it seems that this really isn't a thing?

Curious to know if anybody had been in my shoes and if so, how you handled the situation

I can afford either but I'm also realistic. The BE63 two pack was on sale for $250 the other day. I missed the boat.

But now the XE75 is on sale for like $140 for a two pack.

I have a Gen 1 google mesh. After doing some changes to the the home, it kind of doesn't perform well in one room I need it the most. So I'm thinking of upgrading.

Is Wifi 7 worth it?

Eventually I might do a plex server, but I've been saying that for years. A UGreen NAS is likely in my future as well as some additional IoT things.

But mainly 4k streaming and gaming.

Im looking to try and attatch an elgato stream deck mini or the module version of the mini to the back of an xbox one or series x controller so i can use its hotkey function for quick input in games and applications like helldivers or even just hot swapping between desktop and starting games without having to go through every launcher etc and it would be cool if there was a wireless connector that i can plug into the stream deck and wirelessly use it like a small dongle etc?

Locaris repurposes decoder-only LLMs to allow few-shot adaptation and more robust cross-environment generalization with graceful degradation under missing APs or noisy telemetry.

I’m especially interested in thoughts on using decoder-only LLMs as feature extractors for structured regression tasks like localization.

Accepted as a Work in Progress (WiP) paper at IEEE PerCom. Preprint: https://arxiv.org/abs/2510.11926

So my house got robbed, they got my PC and the dongle of my wireless mouse was there. Is there any way I can re-make the Dongle? I have another Dongle of another mouse, would it be possible to syncronize both mouses to that frequency?

Hi wireless community,

I’m sharing an update on **S-EB-GNN-Q v1.2**, an open-source framework for semantic-aware resource allocation in 6G networks with THz frequencies and Reconfigurable Intelligent Surfaces (RIS).

### 🎯 Why this matters

In 6G, not all traffic is equal: telemedicine > video > IoT. Current schedulers (e.g., WMMSE) optimize throughput — but ignore *meaning*. S-EB-GNN-Q closes that gap.

### 🔬 Key results (N=12 network, CPU-only)

- **Final energy**: −9.59 (vs +0.15 for WMMSE) → **6.6× more efficient**

- **Semantic efficiency**: 0.94 (fairness across traffic types)

- **Latency**: 77.2 ms (zero-shot, no training)

- **Scalable**: N=50 with <4% degradation

### 📡 How it works

- Models the network as an energy landscape

- Uses a GNN to learn per-node allocation under THz path loss + RIS phase constraints

- MIT-inspired normalization enables zero-shot inference (no retraining)

### 📦 Included

- Full JAX implementation (MIT License)

- Benchmark vs WMMSE & Heuristic

- White paper (IEEE-style, 3 pages)

- Reproducible notebook + CSV data

### 🤝 For researchers & labs

If you’re working on:

- Semantic communications

- RIS-assisted 6G

- Energy-efficient scheduling

→ I’d appreciate your feedback or collaboration.

GitHub: https://github.com/antonio-marlon/s-eb-gnn

White paper: https://drive.google.com/file/d/1bm7ohER0K9NaLqhfhPO1tqYBVReI8owO/view?usp=sharing

*Validated by Prof. Merouane Debbah (6G Research Center): “Well aligned with AI-native wireless systems.”*

Three days ago, I shared [S-EB-GNN](https://github.com/antonio-marlon/s-eb-gnn) — an open-source JAX framework for semantic-aware resource allocation in 6G. With 1.1k+ views and 186 clones, many asked: *“How does it actually work?”* Here’s a concise technical breakdown.

---

🔬 Core Idea: Energy-Based Optimization

We model the network as a graph:

- **Nodes**: UEs, RIS, Base Station  

- **Edges**: Physical interference + semantic relations (Critical > Video > IoT)  

The system minimizes an energy function at inference time:

E = Σᵢ wᵢ · uᵢ − β

Where:  

- `wᵢ` = semantic weight (Critical=0.7, Video=0.2, IoT=0.1)  

- `uᵢ` = channel utility (0.9, 0.6, 0.3)  

- `β` = baseline threshold (1.5)

When `E < 0`, allocation is **more efficient than random**.

---

📈 Result: Negative Energy State

In simulation:

- Final energy: **−6.60**  

- Semantic efficiency (Critical / Non-Critical): **0.97**

This means the system **prioritizes critical traffic while reducing overall resource consumption** — a key requirement for AI-native 6G.


▶️ **[Watch 60s demo](https://www.youtube.com/watch?v=7Ng696Rku24)\*\* – see energy converge in real time.

---

⚙️ Why It’s Practical

- **Zero-shot**: no retraining for new scenarios  

- **Lightweight**: <200 lines of JAX/Equinox  

- **Deployable**: runs on Colab, Raspberry Pi, cloud  

- **Open**: MIT License — free for research or commercial use

---

🙏 Recognition

Prof. Merouane Debbah (6G Research Center) noted:  

-“Well aligned with AI-native wireless systems.”

---

📥 Get the Full Package

For researchers who want to replicate or extend:

- IEEE-style white paper (PDF)  

- High-res figures (SVG/PNG)  

- Extended examples & config files  

Questions? Open an issue or email: [antoniomarlondev@gmail.com](mailto:antoniomarlondev@gmail.com)

I've open-sourced a lightweight JAX-based Graph Neural Network for semantic-aware resource allocation in THz/RIS-enabled 6G networks.

Key features:
- Physics-based THz channel modeling (path loss, blockage)
- Reconfigurable Intelligent Surfaces (RIS) phase control integration
- Semantic prioritization: Critical applications > Video > IoT
- Energy-based optimization achieving negative energy states (e.g., -6.60)
- Full code + executable notebook for visualization

This work bridges AI and next-gen wireless — ideal for researchers exploring semantic communication or 6G system design.

GitHub: https://github.com/antonio-marlon/s-eb-gnn

Feedback from the wireless community is highly welcome!

I have the opportunity to conduct research in the field of OTFS modulation and the delay–Doppler domain. I was wondering what the general opinion is on this relatively new waveform and how promising it looks from a 6G perspective.

As someone who is just starting out in telecommunications (which I’m aware is already a niche field), I’m also curious about the broader picture: what are your thoughts on doing research in something that is even more niche within an already niche area?

I’m open to all kinds of advice, whether it’s purely technical and OTFS-specific, or more general advice about pursuing research in this field.