To Decode the Interference or to Consider It as Noise

• Published in: IEEE transactions on information theory 2011-03, Vol.57 (3), p.1274-1283
• Main Authors: Motahari, A S, Khandani, A K
• Format: Article
• Language: English
• Subjects: Additives; Algorithms; Applied sciences; Capacity region; Channels; Coding, codes; combinatorial optimization; Communication; Decoding; Electric noise; Exact sciences and technology; Gaussian; Information; Information theory; Information, signal and communications theory; Interference; interference channel; Knowledge; Maximization; Noise; Normal distribution; Radiocommunications; Random variables; Receivers; Signal and communications theory; Strategy; submodular functions; Telecommunications; Telecommunications and information theory; Transmitters; Transmitters. Receivers; Users
• ISSN: 0018-9448; 1557-9654
• DOI: 10.1109/TIT.2010.2103756

In this paper, the impact of noncoordinated interfering signals on a point to point communication is addressed. While the transmitter has no information about the other users' messages, the receiver has full knowledge of the codebooks of the interfering users and can potentially decode some part of the interference. A simple coding strategy is proposed for this channel. Assuming its own data is decoded successfully, the receiver partitions the set of interfering users into two disjoint subsets, namely the set of decodable users and the set of nondecodable users. Then the transmitter's rate is chosen such that the intended signal can be jointly decoded with the set of decodable users. It is proved that the proposed strategy achieves the capacity of the additive Gaussian channel with Gaussian interfering users. A polynomial time algorithm is proposed to compute the achievable rate of the scheme. This algorithm is based a subroutine which separates the set of interfering users into decodable and nondecodable users in polynomial time. The proposed scheme is also applied to the case of -user interference channel and some achievable points are characterized by successive maximization of users' rates.