Tech Explained: BLE 6.3 Inline PCT Transfer

Bluetooth 6.3 spec was released a couple of weeks back, and I finally got time yesterday to go through the changes. The most interesting one is Inline PCT Transfer. Lets discuss that today.

I had written about Channel Sounding for distance measurement in older posts. In that, 2 BLE devices exchange known radio tones and watch how the phase shifts across frequencies. That phase shift carries distance information, so it can do better than signal-strength guessing.

Now the tricky part is the oscillator error. Each device has its own local oscillator. When the reflector receives a tone, the measured phase mixes the useful air-path phase with the phase difference between the two oscillators. Earlier, the reflector reported Phase Correction Term(PCT) data back. It used I and Q values, which describe amplitude and phase. The initiator combined its own phase reading with the reflector’s data and cancelled the oscillator error digitally.

BLE 6.3 moves that correction closer to the radio itself. With Inline PCT Transfer, the reflector looks at the phase of the tone it received and uses that information to shift the phase of the tone it sends back. So instead of sending all the correction details to the initiator for later math, part of the correction is built into the returned signal.

When that signal comes back, the initiator gets a cleaner phase measurement. It effectively sees the phase change from the signal travelling to the reflector and coming back again, so the useful channel phase appears doubled. That is helpful because the initiator needs less extra PCT data over HCI, which is the interface between the Bluetooth host and controller. So what’s the use case? Less reported data means less processing, less procedure time, and potentially lower power for repeated ranging.

The other BLE 6.3 changes are useful too. PHY-specific RTT accuracy improves timing and BR/EDR RF limits are relaxed for dual-mode radio design. Overall 6.3 is a good update.

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Advanced Tech: Microfluidic cooling

During some reading, I came across a cooling technology Microsoft published a few months back, and it felt somehwat more interesting than the usual “AI hardware” headline. The work focuses on cooling directly into the silicon itself.

To understand why this is important, we need to understand how chips are cooled today. Most high-power processors rely on cold plates where coolant flows through channels above the package, while heat still has to travel through silicon, thermal interfaces and packaging layers before reaching the liquid. So additional layers adds thermal resistance, and as chip power density keeps increasing, cooling becomes a bottleneck.

What Microsoft is exploring are microfluidic channels etched directly into the back of the silicon so coolant moves much closer to hotspots on the die. The interesting part for me is the leaf-like channel structure they discussed. Chips do not heat uniformly, so a simple straight-channel layout is inefficient. A branching structure inspired by leaf veins distributes coolant more intelligently toward hotter regions while avoiding unnecessary flow elsewhere. I think they modeled channels with some AI patterning customized to each chip based on the heat produced, mimicking how leaf veins move water/nutrients via branching.

In Microsoft’s lab-scale testing, this reportedly improved heat removal by up to 3x compared to conventional cold plates and reduced maximum GPU silicon temperature rise by as much as 65%, although I would still treat these as controlled research numbers rather than production ones.

Training and inference clusters already consume massive power. Data centres used ~486 TWh in 2025. In inefficient setups, cooling alone can cross 30%, about 146 TWh, enough to power ~12.5 crore Indian homes for a year.

I think the solution in its current format would have reliability issues. Moving coolant this close to silicon introduces risks around clogging, leakage & pressure balance. A tiny blockage inside microscopic channels can impact an entire hotspot region. It might be a while before this rolls out in production.

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