Short codes with mismatched channel state information: A case study

The rising interest in applications requiring the transmission of small amounts of data has recently lead to the development of accurate performance bounds and of powerful channel codes for the transmission of short-data packets over the AWGN channel. Much less is known about the interaction between error control coding and channel estimation at short blocks when transmitting over channels with states (e.g., fading channels, phase-noise channels, etc…) for the setup where no a priori channel state information (CSI) is available at the transmitter and the receiver. In this paper, we use the mismatched-decoding framework to characterize the fundamental tradeoff occurring in the transmission of short data packet over an AWGN channel with unknown gain that stays constant over the packet. Our analysis for this simplified setup aims at showing the potential of mismatched decoding as a tool to design and analyze transmission strategies for short blocks. We focus on a pragmatic approach where the transmission frame contains a codeword as well as a preamble that is used to estimate the channel (the codeword symbols are not used for channel estimation). Achievability and converse bounds on the block error probability achievable by this approach are provided and compared with simulation results for schemes employing short low-density parity-check codes. Our bounds turn out to predict accurately the optimal trade-off between the preamble length and the redundancy introduced by the channel code.

[1]  Erik G. Ström,et al.  Low-latency Ultra Reliable 5G Communications: Finite-Blocklength Bounds and Coding Schemes , 2016, ArXiv.

[2]  Robert G. Gallager,et al.  Low-density parity-check codes , 1962, IRE Trans. Inf. Theory.

[3]  H. Jin,et al.  Irregular repeat accumulate codes , 2000 .

[4]  Emre Telatar,et al.  Mismatched decoding revisited: General alphabets, channels with memory, and the wide-band limit , 2000, IEEE Trans. Inf. Theory.

[5]  Marc P. C. Fossorier,et al.  Sphere-packing bounds revisited for moderate block lengths , 2004, IEEE Transactions on Information Theory.

[6]  Amos Lapidoth,et al.  Mismatched decoding and the multiple-access channel , 1994, IEEE Trans. Inf. Theory.

[7]  D. A. Bell,et al.  Information Theory and Reliable Communication , 1969 .

[8]  S. Shamai,et al.  Information rates and error exponents of compound channels with application to antipodal signaling in a fading environment , 1993 .

[9]  Dariush Divsalar,et al.  Code Performance as a Function of Block Size , 1998 .

[10]  Evangelos Eleftheriou,et al.  Regular and irregular progressive edge-growth tanner graphs , 2005, IEEE Transactions on Information Theory.

[11]  Giuseppe Durisi,et al.  Short-Packet Communications Over Multiple-Antenna Rayleigh-Fading Channels , 2016, IEEE Transactions on Communications.

[12]  H. Vincent Poor,et al.  Channel Coding Rate in the Finite Blocklength Regime , 2010, IEEE Transactions on Information Theory.

[13]  Imre Csiszár,et al.  Channel capacity for a given decoding metric , 1995, IEEE Trans. Inf. Theory.

[14]  William E. Ryan,et al.  Quasi-cyclic generalized ldpc codes with low error floors , 2007, IEEE Transactions on Communications.

[15]  Gianluigi Liva,et al.  Code Design for Short Blocks: A Survey , 2016, ArXiv.

[16]  Albert Guillén i Fàbregas,et al.  MIMO Block-Fading Channels With Mismatched CSI , 2014, IEEE Transactions on Information Theory.

[17]  Petar Popovski,et al.  Towards Massive, Ultra-Reliable, and Low-Latency Wireless Communication with Short Packets , 2015 .

[18]  Shlomo Shamai,et al.  Performance Analysis of Linear Codes under Maximum-Likelihood Decoding: A Tutorial , 2006, Found. Trends Commun. Inf. Theory.

[19]  Shlomo Shamai,et al.  On information rates for mismatched decoders , 1994, IEEE Trans. Inf. Theory.

[20]  C. Shannon Probability of error for optimal codes in a Gaussian channel , 1959 .

[21]  Giuseppe Durisi,et al.  Quasi-Static Multiple-Antenna Fading Channels at Finite Blocklength , 2013, IEEE Transactions on Information Theory.