Scaling Analysis of Multilevel Polar Coded Modulation

In this paper, we analyze and prove the capacity-achieving property of the equivalent asymmetric channels of multilevel polar-coded modulation in view of the scaling assuming regime, which employ some techniques of symmetric channels. Based on the previous framework of the proof of multilevel coding modulation, we apply the scaling exponent to the equivalent asymmetric channels of multilevel polar-coded modulation under the constraint of the finite code length of component polar codes. Then, we prove that the overall capacity is still achievable under the capacity rule of the design concepts of multilevel coding. In order to accomplish reliable communication of the proposed scheme, we combine Gallager’s mapping conception and source-channel coding theorems to generate the component polar codes with the optimal input distribution for each equivalent asymmetric channel. The optimal property refers to asymptotic optimization under a total variation distance measure. Finally, we describe the detailed design process of multilevel polar-coded modulation versus multistage decoding applying polar codes as the component codes analytically.

[1]  Meir Feder,et al.  Capacity and error exponent analysis of multilevel coding with multistage decoding , 2009, 2009 IEEE International Symposium on Information Theory.

[2]  R. Urbanke,et al.  Polar codes are optimal for lossy source coding , 2009 .

[3]  Junya Honda,et al.  Polar Coding Without Alphabet Extension for Asymmetric Models , 2013, IEEE Transactions on Information Theory.

[4]  Erdal Arikan,et al.  Source polarization , 2010, 2010 IEEE International Symposium on Information Theory.

[5]  Robert F. H. Fischer,et al.  Multilevel codes: Theoretical concepts and practical design rules , 1999, IEEE Trans. Inf. Theory.

[6]  Aria Ghasemian Sahebi,et al.  Multilevel polarization of polar codes over arbitrary discrete memoryless channels , 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[7]  R. Gallager Information Theory and Reliable Communication , 1968 .

[8]  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.

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

[10]  Joseph M. Renes,et al.  Achieving the capacity of any DMC using only polar codes , 2012, 2012 IEEE Information Theory Workshop.

[11]  N. J. A. Sloane,et al.  Sphere Packings, Lattices and Groups , 1987, Grundlehren der mathematischen Wissenschaften.

[12]  David Burshtein,et al.  Improved Bounds on the Finite Length Scaling of Polar Codes , 2013, IEEE Transactions on Information Theory.

[13]  Vincent Y. F. Tan,et al.  Scaling Exponent and Moderate Deviations Asymptotics of Polar Codes for the AWGN Channel , 2017, Entropy.

[14]  Rüdiger L. Urbanke,et al.  Unified scaling of polar codes: Error exponent, scaling exponent, moderate deviations, and error floors , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[15]  Shlomo Shamai,et al.  Performance analysis of a multilevel coded modulation system , 1994, IEEE Trans. Commun..

[16]  Hideki Imai,et al.  A new multilevel coding method using error-correcting codes , 1977, IEEE Trans. Inf. Theory.

[17]  David Burshtein,et al.  On the Finite Length Scaling of $q$ -Ary Polar Codes , 2018, IEEE Transactions on Information Theory.

[18]  Vincent Y. F. Tan,et al.  On the Scaling Exponent of Polar Codes for Binary-Input Energy-Harvesting Channels , 2016, IEEE Journal on Selected Areas in Communications.

[19]  Rüdiger L. Urbanke,et al.  Polar Codes: Characterization of Exponent, Bounds, and Constructions , 2010, IEEE Transactions on Information Theory.

[20]  Rüdiger L. Urbanke,et al.  How to achieve the capacity of asymmetric channels , 2014, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton).