Capacity Results for Binary Fading Interference Channels With Delayed CSIT

To study the effect of lack of up-to-date channel state information at the transmitters (CSITs), we consider two-user binary fading interference channels with Delayed-CSIT. We characterize the capacity region for such channels under homogeneous assumption, where channel gains have identical and independent distributions across time and space, eliminating the possibility of exploiting time/space correlation. We introduce and discuss several novel coding opportunities created by outdated CSIT that can enlarge the achievable rate region. The capacity-achieving scheme relies on accurate combination, concatenation, and merging of these opportunities, depending on the channel statistics. The outer-bounds are based on an extremal inequality we develop for a binary broadcast channel with delayed-CSIT. We further extend the results and characterize the capacity region when output feedback links are available from the receivers to the transmitters in addition to the delayed knowledge of the channel state information. We also discuss the extension of our results to the nonhomogeneous setting.

[1]  W. Hoeffding Probability Inequalities for sums of Bounded Random Variables , 1963 .

[2]  Shlomo Shamai,et al.  Retrospective interference alignment , 2010, 2011 IEEE International Symposium on Information Theory Proceedings.

[3]  Jack K. Wolf,et al.  The capacity region of a multiple-access discrete memoryless channel can increase with feedback (Corresp.) , 1975, IEEE Trans. Inf. Theory.

[4]  Amir K. Khandani,et al.  On the degrees of freedom of X channel with delayed CSIT , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[5]  Shlomo Shamai,et al.  Degrees of Freedom Region of the MIMO Interference Channel With Output Feedback and Delayed CSIT , 2011, IEEE Transactions on Information Theory.

[6]  Mahesh K. Varanasi,et al.  The Degrees of Freedom Region and Interference Alignment for the MIMO Interference Channel With Delayed CSIT , 2011, IEEE Transactions on Information Theory.

[7]  Dongning Guo,et al.  Ergodic Fading Z-Interference Channels Without State Information at Transmitters , 2011, IEEE Transactions on Information Theory.

[8]  Mohammad Ali Maddah-Ali,et al.  Approximate Capacity Region of the MISO Broadcast Channels With Delayed CSIT , 2016, IEEE Transactions on Communications.

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

[10]  Amir Salman Avestimehr,et al.  Interference Channels With Rate-Limited Feedback , 2011, IEEE Transactions on Information Theory.

[11]  Mohammad Ali Maddah-Ali,et al.  Communication through collisions: Opportunistic utilization of past receptions , 2013, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[12]  Peter Elias,et al.  The Noisy Channel Coding Theorem for Erasure Channels , 1974 .

[13]  Mohammad Ali Maddah-Ali,et al.  Interference channel with binary fading: Effect of delayed network state information , 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[14]  Amir K. Khandani,et al.  On the degrees of freedom of SISO interference and X channels with delayed CSIT , 2011, Allerton.

[15]  Claude E. Shannon,et al.  The zero error capacity of a noisy channel , 1956, IRE Trans. Inf. Theory.

[16]  Mahesh K. Varanasi,et al.  The degrees of freedom region of the two-user MIMO broadcast channel with delayed CSIT , 2010, 2011 IEEE International Symposium on Information Theory Proceedings.

[17]  Silas L. Fong,et al.  Two-Hop Interference Channels: Impact of Linear Schemes , 2013, IEEE Transactions on Information Theory.

[18]  Mohammad Ali Maddah-Ali,et al.  Binary fading interference channel with delayed feedback , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

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

[20]  Aydin Sezgin,et al.  Divide-and-Conquer: Approaching the Capacity of the Two-Pair Bidirectional Gaussian Relay Network , 2012, IEEE Transactions on Information Theory.

[21]  Ilan Shomorony,et al.  Degrees of Freedom of Two-Hop Wireless Networks: Everyone Gets the Entire Cake , 2012, IEEE Transactions on Information Theory.

[22]  Shlomo Shamai,et al.  Retrospective Interference Alignment Over Interference Networks , 2012, IEEE Journal of Selected Topics in Signal Processing.

[23]  Sae-Young Chung,et al.  Aligned interference neutralization and the degrees of freedom of the 2 × 2 × 2 interference channel , 2010, 2011 IEEE International Symposium on Information Theory Proceedings.

[24]  Ilan Shomorony,et al.  Two-Unicast Wireless Networks: Characterizing the Degrees of Freedom , 2011, IEEE Transactions on Information Theory.

[25]  Lawrence H. Ozarow,et al.  The capacity of the white Gaussian multiple access channel with feedback , 1984, IEEE Trans. Inf. Theory.

[26]  Amir K. Khandani,et al.  On the Degrees of Freedom of K-User SISO Interference and X Channels With Delayed CSIT , 2011, IEEE Transactions on Information Theory.

[27]  Roy D. Yates,et al.  Fading broadcast channels with state information at the receivers , 2009, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

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

[29]  Ilan Shomorony,et al.  Degrees of freedom of two-hop wireless networks: “Everyone gets the entire cake” , 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[30]  Amir K. Khandani,et al.  On the degrees of freedom of MIMO X channel with delayed CSIT , 2011, 2012 IEEE International Symposium on Information Theory Proceedings.

[31]  Mahesh K. Varanasi,et al.  The Degrees-of-Freedom Region of the MIMO Interference Channel With Shannon Feedback , 2011, IEEE Transactions on Information Theory.

[32]  Silas L. Fong,et al.  Two-hop interference channels: Impact of linear time-varying schemes , 2013, 2013 IEEE International Symposium on Information Theory.

[33]  Mohammad Ali Maddah-Ali,et al.  Completely Stale Transmitter Channel State Information is Still Very Useful , 2010, IEEE Transactions on Information Theory.

[34]  Abhay Parekh,et al.  The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels , 2008, IEEE Transactions on Information Theory.

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

[36]  AbdoliMohammad Javad,et al.  On the Degrees of Freedom of K-User SISO Interference and X Channels With Delayed CSIT , 2013 .

[37]  David Tse,et al.  Feedback Capacity of the Gaussian Interference Channel to Within 2 Bits , 2010, IEEE Transactions on Information Theory.

[38]  Jeff M. Phillips,et al.  Chernoff-Hoeffding Inequality and Applications , 2012, ArXiv.

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

[40]  Amir Salman Avestimehr,et al.  The two-user deterministic interference channel with rate-limited feedback , 2010, 2010 IEEE International Symposium on Information Theory.