Opportunistic Noisy Network Coding for Fading Relay Networks Without CSIT

The parallel relay network is studied, in which a single source node sends a message to a single destination node with the help of N parallel relays. Channel coefficients are assumed to vary over time and channel state information (CSI) is causally available only at the receiver side (CSIR). Opportunistic noisy network coding is proposed for intelligently exploiting CSIR at each relay in a distributed manner by operating the noisy network coding scheme with adaptive compression. More specifically, each relay opportunistically vector-quantizes the collection of received symbols that is received with channel gains larger than a certain threshold. It then forwards the digital compression information to the destination node using independently generated Gaussian codes. For independent and identically distributed (i.i.d.) Rayleigh fading, the proposed scheme is shown to achieve the ergodic capacity in the large number of relays regime. Furthermore, the proposed scheme is extensively compared with several alternative schemes, the decode-forward scheme, the adaptive amplify-forward scheme, and the non-adaptive noisy network coding scheme over geometric models. We show that the new proposed scheme provides significant gain over these schemes in various cases.

[1]  Yuhong Yang Elements of Information Theory (2nd ed.). Thomas M. Cover and Joy A. Thomas , 2008 .

[2]  Sae-Young Chung,et al.  Capacity of the Gaussian Two-way Relay Channel to within 1/2 Bit , 2009, ArXiv.

[3]  Min Chen,et al.  Distributed power allocation strategies for parallel relay networks , 2008, IEEE Transactions on Wireless Communications.

[4]  Andrea J. Goldsmith,et al.  Multihop Analog Network Coding via Amplify-and-Forward: The High SNR Regime , 2012, IEEE Transactions on Information Theory.

[5]  Helmut Bölcskei,et al.  Fading relay channels: performance limits and space-time signal design , 2004, IEEE Journal on Selected Areas in Communications.

[6]  Mai H. Vu,et al.  MISO Capacity with Per-Antenna Power Constraint , 2010, IEEE Transactions on Communications.

[7]  Gregory W. Wornell,et al.  Cooperative diversity in wireless networks: Efficient protocols and outage behavior , 2004, IEEE Transactions on Information Theory.

[8]  Mohammad Reza Aref,et al.  Slepian–Wolf Coding Over Cooperative Relay Networks , 2011, IEEE Transactions on Information Theory.

[9]  Yuval Kochman,et al.  Rematch-and-Forward: Joint Source–Channel Coding for Parallel Relaying With Spectral Mismatch , 2014, IEEE Transactions on Information Theory.

[10]  Sae-Young Chung,et al.  Noisy network coding , 2010 .

[11]  Amir K. Khandani,et al.  A new achievable rate for the Gaussian parallel relay channel , 2009, 2009 IEEE International Symposium on Information Theory.

[12]  Aggelos Bletsas,et al.  A simple Cooperative diversity method based on network path selection , 2005, IEEE Journal on Selected Areas in Communications.

[13]  David Tse,et al.  Outage Capacity of the Fading Relay Channel in the Low-SNR Regime , 2006, IEEE Transactions on Information Theory.

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

[15]  Abdel R. El Gamal,et al.  On information flow in relay networks , 1981 .

[16]  Xiugang Wu,et al.  On the Optimal Compressions in the Compress-and-Forward Relay Schemes , 2010, IEEE Transactions on Information Theory.

[17]  Sae-Young Chung,et al.  Capacity of the Gaussian Two-Way Relay Channel to Within ${1\over 2}$ Bit , 2009, IEEE Transactions on Information Theory.

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

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

[20]  Suhas N. Diggavi,et al.  The Approximate Capacity of the Gaussian $N$-Relay Diamond Network , 2013, IEEE Trans. Inf. Theory.

[21]  Michael Gastpar,et al.  On the capacity of large Gaussian relay networks , 2005, IEEE Transactions on Information Theory.

[22]  Gerhard Kramer,et al.  Short Message Noisy Network Coding With a Decode–Forward Option , 2013, IEEE Transactions on Information Theory.

[23]  Abbas El Gamal,et al.  Network Information Theory , 2021, 2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT).

[24]  Shlomo Shamai,et al.  Fading Channels: Information-Theoretic and Communication Aspects , 1998, IEEE Trans. Inf. Theory.

[25]  Armin Wittneben,et al.  Achievable Rate Regions for the Two-way Relay Channel , 2006, 2006 IEEE International Symposium on Information Theory.

[26]  Wan Choi,et al.  Performance Analysis of Two Relay Selection Schemes for Cooperative Diversity , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[27]  Panganamala Ramana Kumar,et al.  A network information theory for wireless communication: scaling laws and optimal operation , 2004, IEEE Transactions on Information Theory.

[28]  Sachin Katti,et al.  Embracing wireless interference: analog network coding , 2007, SIGCOMM.

[29]  Sergio VerdÂ,et al.  Fading Channels: InformationTheoretic and Communications Aspects , 2000 .

[30]  Brett Schein,et al.  Distributed coordination in network information theory , 2001 .

[31]  R. Gallager,et al.  The Gaussian parallel relay network , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[32]  Anders Høst-Madsen,et al.  Capacity bounds and power allocation for wireless relay channels , 2005, IEEE Transactions on Information Theory.

[33]  Andrea J. Goldsmith,et al.  Joint Relaying and Network Coding in Wireless Networks , 2007, 2007 IEEE International Symposium on Information Theory.