You could have designed state of the art positional encoding

Rotary Positional Encoding (RoPE) improves transformer models by encoding relative token positions through vector rotations in self-attention. This method preserves semantic information while allowing models to better understand relationships between tokens, extending to multiple dimensions and potentially improving performance on longer sequences.