A New Coding Paradigm for the Primitive Relay Channel

We consider the primitive relay channel, where the source sends a message to the relay and to the destination, and the relay helps the communication by transmitting an additional message to the destination via a separate channel. Two well-known coding techniques have been introduced for this setting: decode-and-forward and compress-and-forward. In decode-and-forward, the relay completely decodes the message and sends some information to the destination; in compress-and-forward, the relay does not decode, and it sends a compressed version of the received signal to the destination using Wyner–Ziv coding. In this paper, we present a novel coding paradigm that provides an improved achievable rate for the primitive relay channel. The idea is to combine compress-and-forward and decode-and-forward via a chaining construction. We transmit over pairs of blocks: in the first block, we use compress-and-forward; and, in the second block, we use decode-and-forward. More specifically, in the first block, the relay does not decode, it compresses the received signal via Wyner–Ziv, and it sends only part of the compression to the destination. In the second block, the relay completely decodes the message, it sends some information to the destination, and it also sends the remaining part of the compression coming from the first block. By doing so, we are able to strictly outperform both compress-and-forward and decode-and-forward. Note that the proposed coding scheme can be implemented with polar codes. As such, it has the typical attractive properties of polar coding schemes, namely, quasi-linear encoding and decoding complexity, and error probability that decays at super-polynomial speed. As a running example, we take into account the special case of the erasure relay channel, and we provide a comparison between the rates achievable by our proposed scheme and the existing upper and lower bounds.

[1]  Dennis Hui,et al.  Capacity-achieving rate-compatible polar codes , 2015, 2016 IEEE International Symposium on Information Theory (ISIT).

[2]  Mohammad Reza Aref,et al.  The capacity of the semideterministic relay channel , 1982, IEEE Trans. Inf. Theory.

[3]  Erdal Arikan,et al.  Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels , 2008, IEEE Transactions on Information Theory.

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

[5]  E. Meulen,et al.  Three-terminal communication channels , 1971, Advances in Applied Probability.

[6]  Feng Xue,et al.  A New Upper Bound on the Capacity of a Primitive Relay Channel Based on Channel Simulation , 2014, IEEE Transactions on Information Theory.

[7]  Sennur Ulukus,et al.  Polar Coding for the General Wiretap Channel With Extensions to Multiuser Scenarios , 2016, IEEE Journal on Selected Areas in Communications.

[8]  Mikael Skoglund,et al.  Nested Polar Codes for Wiretap and Relay Channels , 2010, IEEE Communications Letters.

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

[10]  George K. Karagiannidis,et al.  Smart Decode-and-Forward Relaying with Polar Codes , 2014, IEEE Wireless Communications Letters.

[11]  Michael Langberg,et al.  Asymmetric Error Correction and Flash-Memory Rewriting Using Polar Codes , 2014, IEEE Transactions on Information Theory.

[12]  Rüdiger L. Urbanke,et al.  How to Achieve the Capacity of Asymmetric Channels , 2018, IEEE Trans. Inf. Theory.

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

[14]  Mikael Skoglund,et al.  Polar Codes for Cooperative Relaying , 2012, IEEE Transactions on Communications.

[15]  Ayfer Özgür,et al.  Improving on the Cut-Set Bound via Geometric Analysis of Typical Sets , 2016, IEEE Transactions on Information Theory.

[16]  Rüdiger L. Urbanke,et al.  Achieving Marton's Region for Broadcast Channels Using Polar Codes , 2015, IEEE Trans. Inf. Theory.

[17]  Zhen Zhang,et al.  Partial converse for a relay channel , 1988, IEEE Trans. Inf. Theory.

[18]  Young-Han Kim Capacity of a Class of Deterministic Relay Channels , 2008, IEEE Trans. Inf. Theory.

[19]  Sae-Young Chung,et al.  Noisy Network Coding , 2010, IEEE Transactions on Information Theory.

[20]  Deniz Gündüz,et al.  Capacity of a Class of State-Dependent Orthogonal Relay Channels , 2014, IEEE Transactions on Information Theory.

[21]  A. Robert Calderbank,et al.  Soft-Decoding-Based Strategies for Relay and Interference Channels: Analysis and Achievable Rates Using LDPC Codes , 2010, IEEE Transactions on Information Theory.

[22]  Rüdiger L. Urbanke,et al.  A New Coding Paradigm for the Primitive Relay Channel , 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

[23]  Sung Hoon Lim,et al.  A Unified Approach to Hybrid Coding , 2015, IEEE Transactions on Information Theory.

[24]  Wei Yu,et al.  Capacity of a Class of Modulo-Sum Relay Channels , 2007, IEEE Transactions on Information Theory.