v1.2.0: MIMO, AI-for-wireless & MCP server

CommPy 1.2.0 adds multiple-antenna MIMO support, an optional deep-learning
layer (commpy.ml), and an optional MCP server exposing CommPy to AI agents.
No breaking changes to the public API.

What's new

MIMO — i.i.d. Rayleigh channel (rayleigh_channel_matrix, mimo_awgn),
Alamouti space-time block coding (alamouti_encode/alamouti_decode),
spatial-multiplexing detectors (zf_detector, mmse_detector, ml_detector,
kbest_detector), and MIMO capacity (mimo_capacity, ergodic_mimo_capacity).

AI-for-wireless (optional, commpy[ml]) — a PyTorch layer under commpy.ml:
a differentiable AWGN channel, an end-to-end learned Autoencoder, a
NeuralDemapper, and a trainable NeuralMinSumDecoder for LDPC. Not imported by
default, so the base install stays NumPy/SciPy-only.

MCP server (optional, commpy[mcp]) — a commpy-mcp Model Context Protocol
server: capability listing, channel capacity, and uncoded/coded BER sweeps.

Docs & tooling — a Gallery page with generated figures, an opt-in benchmark
suite, fixed doc links, and a quickstart notebook covering the modern codes.

Install

pip install --upgrade commpy          # base
pip install --upgrade "commpy[ml]"    # + PyTorch AI layer
pip install --upgrade "commpy[mcp]"   # + MCP server

Full changelog: v1.1.0...v1.2.0