Multipoint decentralized processing of interfered Gaussian channel: Scaling laws

We investigate achievable communication rates and some corresponding upper bounds of distributed reception in the presence of strong interferers. The scheme comprises one transmitter communicating to a remote destination via several relays, which forward messages to the remote destination through lossless links with finite capacities. The relays receive the transmission along with some strong unknown interferers. The final destination manages to decode the original message overcoming the strong interference relying only on the non-cooperative (distributed) processing at the relays. Lattices, implying structured coding, are found to be most beneficiary for the distributed processing at the relays. We focus on the scaling laws for fixed channel coefficients, where the powers of the transmitter and the interferers are taken to infinity. Scaling laws basically reflect the degrees of freedom of the interfered scheme. It is shown that in order to overcome the interference, a defined amount of information about the interferers needs to be forwarded, along with the desired message, to the destination. This amount of information grows with the number of interferers and decreases with of the number of relays. We propose necessary conditions for the general case and derive sufficient conditions for the case with M interferers and M +1 relays. For this special case we identify the exact scaling laws and also provide a finite gap capacity results. An example is provided for three relays and one interferer demonstrating the effectiveness of the necessary conditions.