Transmission Bandwidth and Sampling frequency
Complex (I/Q) signal processing is used in this case. With a complex-valued signal sampled at a rate $B \text{ Hz}$, you can unambiguously represent a total bandwidth of $B \text{ Hz}$. 

What you're thinking of is the real-valued signal case, where a signal sampled at $B \text{ Hz}$ can unambiguously represent a total bandwidth of $\frac{B}{2} \text{ Hz}$. This is the most common statement of the Nyquist theorem, but it only holds for real-valued signals.

Note that the total number of "values" per second is the same, as each complex sample consists of a real and imaginary part. So, there's no "information gain" to be made by using complex sampling, it's just more convenient for many applications (including digital communications signal processing).