The Ergodic Capacity of Phase-Fading Interference Networks

We identify the role of equal strength interference links as bottlenecks on the ergodic sum capacity of a K user phase-fading interference network, i.e., an interference network where the fading process is restricted primarily to independent and uniform phase variations while the channel magnitudes are held fixed across time. It is shown that even though there are K(K-1) cross-links, only about K/2 disjoint and equal strength interference links suffice to determine the capacity of the network regardless of the strengths of the rest of the cross channels. This scenario is called a minimal bottleneck state. It is shown that ergodic interference alignment is capacity optimal for a network in a minimal bottleneck state. The results are applied to large networks. It is shown that large networks are close to bottleneck states with a high probability, so that ergodic interference alignment is close to optimal for large networks. Limitations of the notion of bottleneck states are also highlighted for channels where both the phase and the magnitudes vary with time. It is shown through an example that for these channels, joint coding across different bottleneck states makes it possible to circumvent the capacity bottlenecks.

[1]  Amir K. Khandani,et al.  Communication Over MIMO X Channels: Interference Alignment, Decomposition, and Performance Analysis , 2008, IEEE Transactions on Information Theory.

[2]  Vahid Tarokh,et al.  On the degrees-of-freedom of the MIMO interference channel , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.

[3]  Matthew Aldridge,et al.  Asymptotic sum-capacity of random Gaussian interference networks using interference alignment , 2010, 2010 IEEE International Symposium on Information Theory.

[4]  Syed Ali Jafar The Ergodic Capacity of Interference Networks , 2009, ArXiv.

[5]  Sriram Vishwanath,et al.  Ergodic Interference Alignment , 2009, IEEE Transactions on Information Theory.

[6]  Matthew Aldridge,et al.  Interference Alignment-Based Sum Capacity Bounds for Random Dense Gaussian Interference Networks , 2011, IEEE Transactions on Information Theory.

[7]  Syed Ali Jafar,et al.  Parallel Gaussian Interference Channels Are Not Always Separable , 2009, IEEE Transactions on Information Theory.

[8]  Ayfer Özgür,et al.  Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks , 2006, IEEE Transactions on Information Theory.

[9]  G. V. Balakin On Random Matrices , 1967 .

[10]  H.V. Poor,et al.  Ergodic two-user interference channels: Is separability optimal? , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

[11]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

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

[13]  Axthonv G. Oettinger,et al.  IEEE Transactions on Information Theory , 1998 .

[14]  Syed Ali Jafar,et al.  Multiple Access Outerbounds and the Inseparability of Parallel Interference Channels , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

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

[16]  Shlomo Shamai,et al.  Degrees of Freedom Region of the MIMO $X$ Channel , 2008, IEEE Transactions on Information Theory.

[17]  M. Stephanov,et al.  Random Matrices , 2005, hep-ph/0509286.

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