On the Rate Region of I.I.D. Discrete Signaling and Treating Interference as Noise for the Gaussian Broadcast Channel
This work addresses communication efficiency in broadcast channels, offering a practical and theoretically grounded approach with incremental improvements over existing methods.
The paper tackles the Gaussian broadcast channel by proposing a scheme using i.i.d. discrete signaling with treating interference as noise, proving it achieves a rate region within a constant gap to capacity independent of channel parameters, and showing via simulation that PAM can outperform Gaussian signaling for the weak user in some cases.
We revisit the Gaussian broadcast channel (GBC) and explore the rate region achieved by purely discrete inputs with treating interference as noise (TIN) decoding. Specifically, we introduce a simple scheme based on superposition coding with identically and independently distributed (i.i.d.) inputs drawn from discrete constellations, e.g., pulse amplitude modulations (PAM). Most importantly, we prove that the resulting achievable rate region under TIN decoding is within a constant gap to the capacity region of the GBC, where the gap is independent of all channel parameters. In addition, we show via simulation that the weak user can achieve a higher rate with PAM than with Gaussian signaling in some cases.