Parallel Gaussian Networks with a Common State-Cognitive Helper

TL;DR

This paper investigates the capacity of parallel state-dependent networks with a helper that knows the state noncausally, deriving bounds and characterizing capacity regions in high state power regimes for various models.

Contribution

It introduces new capacity bounds and characterizations for complex parallel networks with a state-cognitive helper, extending understanding of interference cancellation with asymmetric state knowledge.

Findings

Capacity bounds are derived for all models.

Full or partial capacity region boundaries are characterized.

Results apply in high state power regimes.

Abstract

A class of state-dependent parallel networks with a common state-cognitive helper, in which $K$ transmitters wish to send $K$ messages to their corresponding receivers over $K$ state-corrupted parallel channels, and a helper who knows the state information noncausally wishes to assist these receivers to cancel state interference. Furthermore, the helper also has its own message to be sent simultaneously to its corresponding receiver. Since the state information is known only to the helper, but not to the corresponding transmitters $1,\dots,K$, transmitter-side state cognition and receiver-side state interference are mismatched. Our focus is on the high state power regime, i.e., the state power goes to infinity. Three (sub)models are studied. Model I serves as a basic model, which consists of only one transmitter-receiver (with state corruption) pair in addition to a helper that assists the receiver to cancel state in addition to transmitting its own message. Model II consists of two transmitter-receiver pairs in addition to a helper, and only one receiver is interfered by a state sequence. Model III generalizes model I include multiple transmitter-receiver pairs with each receiver corrupted by independent state. For all models, inner and outer bounds on the capacity region are derived, and comparison of the two bounds leads to characterization of either full or partial boundary of the capacity region under various channel parameters.