Cooperation for Interference Management: A GDoF Perspective

The impact of cooperation on interference management is investigated by studying an elemental wireless network, the so-called symmetric interference relay channel (IRC), from a generalized degrees of freedom (GDoF) perspective. This is motivated by the fact that the deployment of relays is considered as a remedy to overcome the bottleneck of current systems in terms of achievable rates. The focus of this paper is on the regime in which the interference link is weaker than the source-relay link in the IRC. Our approach toward studying the GDoF goes through the capacity analysis of the linear deterministic IRC (LD-IRC). New upper bounds on the sum capacity of the LD-IRC based on genie-aided approaches are established. These upper bounds together with some existing upper bounds are achieved by using four novel transmission schemes. Extending the upper bounds and the transmission schemes to the Gaussian case, the GDoF of the Gaussian IRC is characterized for the aforementioned regime. This completes the GDoF results available in the literature for the symmetric GDoF. It turns out that even if the incoming and outgoing links of the relay are both weaker than the desired channel, involving a relay can increase the GDoF. Interestingly, utilizing the relay in this case can increase the slope of the GDoF from -2 [in the interference channel (IC)] to -1 or 0. This shrinks the regime where ignoring the interference by treating it as noise is optimal. Furthermore, the analysis shows that if the relay ingoing and outgoing links are sufficiently strong, the relay is able to neutralize the interference completely. In this case, the bottleneck of the transmission will be the interference links, and hence, the GDoF increases if the interference link gets stronger. It is shown that in the strong interference regime, in contrast to the IC, the GDoF can be a monotonically decreasing function of the interference level.

[1]  Sriram Vishwanath,et al.  Generalized Degrees of Freedom of the Symmetric Gaussian $K$ User Interference Channel , 2010, IEEE Transactions on Information Theory.

[2]  Hua Wang,et al.  Gaussian Interference Channel Capacity to Within One Bit , 2007, IEEE Transactions on Information Theory.

[3]  Michael Gastpar,et al.  Compute-and-Forward: Harnessing Interference Through Structured Codes , 2009, IEEE Transactions on Information Theory.

[4]  Aylin Yener,et al.  Symmetric Capacity of the Gaussian Interference Channel With an Out-of-Band Relay to Within 1.15 Bits , 2012, IEEE Transactions on Information Theory.

[5]  Alexander Sprintson,et al.  Joint Physical Layer Coding and Network Coding for Bidirectional Relaying , 2008, IEEE Transactions on Information Theory.

[6]  Abbas El Gamal,et al.  Capacity theorems for the relay channel , 1979, IEEE Trans. Inf. Theory.

[7]  Aydin Sezgin,et al.  Achieving Net Feedback Gain in the Butterfly Network with a Full-Duplex Bidirectional Relay , 2012, ArXiv.

[8]  Elza Erkip,et al.  Achievable Rates for the Gaussian Interference Relay Channel , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[9]  Michael Gastpar,et al.  Cooperative strategies and capacity theorems for relay networks , 2005, IEEE Transactions on Information Theory.

[10]  Aydin Sezgin,et al.  Relays for interference management: Feedback, amplification and neutralization , 2013, 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[11]  Uri Erez,et al.  Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding , 2004, IEEE Transactions on Information Theory.

[12]  Suhas N. Diggavi,et al.  Wireless Network Information Flow: A Deterministic Approach , 2009, IEEE Transactions on Information Theory.

[13]  Thomas M. Cover,et al.  Elements of Information Theory: Cover/Elements of Information Theory, Second Edition , 2005 .

[14]  Aydin Sezgin,et al.  Cooperation strategies for the butterfly network: Neutralization, feedback, and computation , 2012, 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

[15]  Bobak Nazer Successive compute-and-forward , 2012 .

[16]  Daniela Tuninetti,et al.  Capacity to within 3 bits for a class of Gaussian Interference Channels with a Cognitive Relay , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[17]  Syed Ali Jafar,et al.  Interference Alignment and Degrees of Freedom of the $K$-User Interference Channel , 2008, IEEE Transactions on Information Theory.

[18]  Andrea J. Goldsmith,et al.  Relaying in the Presence of Interference: Achievable Rates, Interference Forwarding, and Outer Bounds , 2012, IEEE Transactions on Information Theory.

[19]  Syed Ali Jafar,et al.  Interference Alignment and the Generalized Degrees of Freedom of the $X$ Channel , 2009, IEEE Transactions on Information Theory.

[20]  Syed A. Jafar,et al.  Interference Alignment and the Degrees of Freedom for the 3 User Interference Channel , 2007 .

[21]  A. Sridharan Broadcast Channels , 2022 .

[22]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[23]  David Tse,et al.  The two-user Gaussian interference channel: a deterministic view , 2008, Eur. Trans. Telecommun..

[24]  Daniel Zahavi,et al.  On the generalized degrees-of-freedom of the phase fading Z-interference channel with a relay , 2014, 2014 IEEE International Symposium on Information Theory.

[25]  Aydin Sezgin,et al.  Multi-way Communications: An Information Theoretic Perspective , 2015, Found. Trends Commun. Inf. Theory.

[26]  Syed Ali Jafar,et al.  Degrees of Freedom of Wireless Networks With Relays, Feedback, Cooperation, and Full Duplex Operation , 2009, IEEE Transactions on Information Theory.

[27]  Andrea J. Goldsmith,et al.  The capacity of the interference channel with a cognitive relay in strong interference , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[28]  Aydin Sezgin,et al.  Information Theory Capacity of the two-way relay channel within a constant gap , 2010, Eur. Trans. Telecommun..

[29]  Shlomo Shamai,et al.  On the capacity of cognitive relay assisted Gaussian interference channel , 2008, 2008 IEEE International Symposium on Information Theory.

[30]  Aydin Sezgin,et al.  The generalized degrees of freedom of the interference relay channel with strong interference , 2013, 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[31]  Te Sun Han,et al.  A new achievable rate region for the interference channel , 1981, IEEE Trans. Inf. Theory.

[32]  Joy A. Thomas,et al.  Feedback can at most double Gaussian multiple access channel capacity , 1987, IEEE Trans. Inf. Theory.

[33]  Syed Ali Jafar,et al.  Interference alignment and the generalized degrees of freedom of the X channel , 2009, ISIT.

[34]  Aylin Yener,et al.  The Gaussian Interference Relay Channel: Improved Achievable Rates and Sum Rate Upperbounds Using a Potent Relay , 2011, IEEE Transactions on Information Theory.

[35]  Aydin Sezgin,et al.  On the Generalized Degrees of Freedom of the Gaussian Interference Relay Channel , 2012, IEEE Transactions on Information Theory.

[36]  Venugopal V. Veeravalli,et al.  Gaussian Interference Networks: Sum Capacity in the Low-Interference Regime and New Outer Bounds on the Capacity Region , 2008, IEEE Transactions on Information Theory.

[37]  Daniela Tuninetti,et al.  Outer bounds for the interference channel with a cognitive relay , 2010, 2010 IEEE Information Theory Workshop.

[38]  Aydin Sezgin,et al.  Achieving Net Feedback Gain in the Linear-Deterministic Butterfly Network with a Full-Duplex Relay , 2013, Information Theory, Combinatorics, and Search Theory.

[39]  Pablo Piantanida,et al.  Constant-gap results and cooperative strategies for a class of Interference Relay Channels , 2014, 2014 IEEE International Symposium on Information Theory.