Universal polar codes

Polar codes, invented by Arikan in 2009, are known to achieve the capacity of any binary-input memoryless output-symmetric channel. Further, both the encoding and the decoding can be accomplished in O(N log(N)) real operations, where N is the blocklength. One of the few drawbacks of the original polar code construction is that it is not universal. This means that the code has to be tailored to the channel if we want to transmit close to capacity. We present two “polar-like” schemes that are capable of achieving the compound capacity of the whole class of binaryinput memoryless symmetric channels with low complexity. Roughly speaking, for the first scheme we stack up N polar blocks of length N on top of each other but shift them with respect to each other so that they form a “staircase.” Then by coding across the columns of this staircase with a standard ReedSolomon code, we can achieve the compound capacity using a standard successive decoder to process the rows (the polar codes) and in addition a standard Reed-Solomon erasure decoder to process the columns. Compared to standard polar codes this scheme has essentially the same complexity per bit but a block length which is larger by a factor O(N log2(N)/ϵ). Here N is the required blocklength for a standard polar code to achieve an acceptable block error probability for a single channel at a distance of at most c from capacity. For the second scheme we first show how to construct a true polar code which achieves the compound capacity for a finite number of channels. We achieve this by introducing special “polarization” steps which “align” the good indices for the various channels. We then show how to exploit the compactness of the space of binary-input memoryless output-symmetric channels to reduce the compound capacity problem for this class to a compound capacity problem for a finite set of channels. This scheme is similar in spirit to standard polar codes, but the price for universality is a considerably larger blocklength.

[1]  Shlomo Shamai,et al.  Polar coding for reliable communications over parallel channels , 2010, 2010 IEEE Information Theory Workshop.

[2]  D. Blackwell,et al.  The Capacity of a Class of Channels , 1959 .

[3]  J.L. Massey,et al.  Theory and practice of error control codes , 1986, Proceedings of the IEEE.

[4]  Emre Telatar,et al.  On the construction of polar codes , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[5]  Eren Sasoglu Polar Coding Theorems for Discrete Systems , 2011 .

[6]  Lele Wang,et al.  Universal polarization , 2014, ISIT.

[7]  Wei Liu,et al.  The least degraded and the least upgraded channel with respect to a channel family , 2013, 2013 IEEE Information Theory Workshop (ITW).

[8]  Emre Telatar,et al.  On the rate of channel polarization , 2008, 2009 IEEE International Symposium on Information Theory.

[9]  Frédéric Didier Efficient erasure decoding of Reed-Solomon codes , 2009, ArXiv.

[10]  Jungwon Lee,et al.  Compound polar codes , 2013, 2013 Information Theory and Applications Workshop (ITA).

[11]  Rüdiger L. Urbanke,et al.  Polar Codes for Channel and Source Coding , 2009, ArXiv.

[12]  Ezio Biglieri,et al.  Polarization of quasi-static fading channels , 2013, 2013 IEEE International Symposium on Information Theory.

[13]  Seyed Hamed Hassani Polarization and Spatial Coupling - Two Techniques to Boost Performance , 2013 .

[14]  Alexander Vardy,et al.  How to Construct Polar Codes , 2011, IEEE Transactions on Information Theory.

[15]  Tobias J. Oechtering,et al.  Polar Coding for Bidirectional Broadcast Channels with Common and Confidential Messages , 2013, IEEE Journal on Selected Areas in Communications.

[16]  Rüdiger L. Urbanke,et al.  Finite-Length Scaling for Polar Codes , 2013, IEEE Transactions on Information Theory.

[17]  Rüdiger L. Urbanke,et al.  The compound capacity of polar codes , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[18]  Rüdiger L. Urbanke,et al.  Spatially coupled ensembles universally achieve capacity under belief propagation , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[19]  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.

[20]  Rüdiger L. Urbanke,et al.  Modern Coding Theory , 2008 .

[21]  Jungwon Lee,et al.  Performance Limits and Practical Decoding of Interleaved Reed-Solomon Polar Concatenated Codes , 2013, IEEE Transactions on Communications.

[22]  Mayank Bakshi,et al.  Concatenated Polar codes , 2010, 2010 IEEE International Symposium on Information Theory.