Analog coding for Gaussian source and state interference estimation

We consider zero-delay analog coding of a Gaussian source over a Gaussian channel with additive correlated Gaussian interference known to the transmitter. The receiver aims to jointly estimate the source signal and the state interference. We propose a layered parametric analog coding scheme based on linear and sawtooth mappings. We derive an upper bound on the distortion for the parametric scheme by assuming a suboptimal decoder. To optimize the system parameters, we use two suboptimal methods. The first one is partially numerical and part of the parameters are derived assuming no sawtooth mapping; the other one, however, is based on minimizing the derived upper bound. To improve the performance whenever storage and offline design complexity are not an issue, we design a nonparametric mapping through an iterative process based on joint optimization between the encoder and the decoder using the necessary conditions for optimality. Numerical results show that the nonparametric and parametric mappings outperform the linear scheme and overcome the saturation effect.

[1]  Yu-Chih Huang,et al.  Joint Source-Channel Coding with Correlated Interference , 2012, IEEE Transactions on Communications.

[2]  Mikael Skoglund,et al.  Sawtooth Relaying , 2008, IEEE Communications Letters.

[3]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[4]  Mikael Skoglund,et al.  Optimized low-delay source-channel-relay mappings , 2010, IEEE Transactions on Communications.

[5]  Mung Chiang,et al.  Channel capacity and state estimation for state-dependent Gaussian channels , 2005, IEEE Transactions on Information Theory.

[6]  Nariman Farvardin,et al.  On the performance and complexity of channel-optimized vector quantizers , 1991, IEEE Trans. Inf. Theory.

[7]  Michael Gastpar,et al.  To code, or not to code: lossy source-channel communication revisited , 2003, IEEE Trans. Inf. Theory.

[8]  Yuval Kochman,et al.  Joint Wyner–Ziv/Dirty-Paper Coding by Modulo-Lattice Modulation , 2008, IEEE Transactions on Information Theory.

[9]  Fady Alajaji,et al.  Source-Channel Coding for Fading Channels With Correlated Interference , 2014, IEEE Transactions on Communications.

[10]  Shlomo Shamai,et al.  Capacity and lattice strategies for canceling known interference , 2005, IEEE Transactions on Information Theory.

[11]  Mikael Skoglund,et al.  Low-Delay Joint Source-Channel Mappings for the Gaussian MAC , 2014, IEEE Communications Letters.

[12]  Fady Alajaji,et al.  Low-Latency Source-Channel Coding for Fading Channels with Correlated Interference , 2014, IEEE Wireless Communications Letters.

[13]  Ieee Staff,et al.  2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) , 2015 .

[14]  Yichuan Hu,et al.  Analog Joint Source-Channel Coding Using Non-Linear Curves and MMSE Decoding , 2011, IEEE Transactions on Communications.

[15]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[16]  Mikael Skoglund,et al.  Zero-Delay Joint Source-Channel Coding for a Bivariate Gaussian on a Gaussian MAC , 2012, IEEE Transactions on Communications.

[17]  Tor A. Ramstad,et al.  Shannon-kotel-nikov mappings in joint source-channel coding , 2009, IEEE Transactions on Communications.