Abstract
The state-dependent point-to-point Gaussian channel with a helper is first studied, in which a transmitter communicates with a receiver via a state-corrupted channel. The state is not known to the transmitter nor to the receiver, but known to a helper noncausally, which then wishes to assist the receiver to cancel the state. Differently from the previous work that characterized the capacity only in the infinite state power regime, this paper explores the general case with arbitrary state power. A lower bound on the capacity is derived based on an achievable scheme that integrates direct state subtraction and single-bin dirty paper coding. By analyzing this lower bound and further comparing it with the existing upper bounds, the capacity of the channel is characterized for a wide range of channel parameters. Such an idea of characterizing the capacity is further extended to study the two-user state-dependent multiple access channel with a helper. By comparing the derived inner and outer bounds, the channel parameters are partitioned into appropriate cases, and for each case, either segments on the capacity region boundary or the full capacity region are characterized.
Highlights
H ELPER-ASSISTED state-dependent models have been an active research topic recently
For the point-to-point model with a helper, our achievable scheme is based on integration of single-bin dirty paper coding and direct state subtraction with optimal trade-off between the two schemes
By comparing the achievable rate in Corollary 1 with the upper bound in Lemma 2, we characterize the capacity for various channel parameters in the following theorem
Summary
H ELPER-ASSISTED state-dependent models have been an active research topic recently. The basic point-topoint model (see Figure 2) was studied in [1], in which a transmitter wishes to send the message W to a receiver over the state-corrupted channel, and a helper knows the state information noncausally and wishes to assist the receiver to cancel state interference. For the point-to-point model with a helper, our achievable scheme is based on integration of single-bin dirty paper coding and direct state subtraction (i.e., the helper directly cancels partial state in the received output) with optimal trade-off between the two schemes. Single-bin dirty paper coding is optimal and direct state subtraction is not necessary Such characterization of the capacity reduces to the capacity result for infinite state power regime obtained in the previous studies [1], [5], [7], [8], [10]. We derive an inner bound based on a scheme that integrates direct state cancellation and single-bin dirty paper coding. If the helper’s power is below a threshold, the helper can assist to fully cancel the state only when the state power is small enough
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
