Optimal partial decode-and-forward rates for stochastically degraded Gaussian relay channels

For the Gaussian MIMO relay channel, we consider rates that can be achieved with the relay using the partial decode-and-forward (PDF) scheme, which is a generalization of the decode-and-forward (DF) scheme. Since for the general case the optimal channel input distribution for the PDF strategy is unknown, the maximum PDF rate for the Gaussian relay channel can only be determined if the best PDF strategy is equivalent to the DF strategy, point-to-point (P2P) transmission from source to destination, or if PDF achieves the cut-set bound (CSB), where Gaussian channel inputs are known to be optimal. In this paper, we identify and discuss two new such special cases, the stochastically degraded and the reversely stochastically degraded Gaussian relay channel.

[1]  Michael Gastpar,et al.  Cooperative strategies and capacity theorems for relay networks , 2005, IEEE Transactions on Information Theory.

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

[3]  Abbas El Gamal,et al.  Capacity of a class of relay channels with orthogonal components , 2005, IEEE Transactions on Information Theory.

[4]  Yuhong Yang.  Elements of Information Theory (2nd ed.). Thomas M. Cover and Joy A. Thomas , 2008 .

[5]  Wolfgang Utschick,et al.  A zero-forcing partial decode-and-forward scheme for the Gaussian MIMO relay channel , 2013, 2013 IEEE International Conference on Communications (ICC).

[6]  Wolfgang Utschick,et al.  Partial decode-and-forward rates for the Gaussian MIMO relay channel: Inner approximation of non-convex rate constraints , 2013, 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[7]  Wolfgang Utschick,et al.  On Achievable Rate Regions for Half-Duplex Gaussian MIMO Relay Channels: A Decomposition Approach , 2012, IEEE Journal on Selected Areas in Communications.

[8]  Gerhard Kramer,et al.  Topics in Multi-User Information Theory , 2008, Found. Trends Commun. Inf. Theory.

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

[10]  Abbas El Gamal,et al.  Bounds on capacity and minimum energy-per-bit for AWGN relay channels , 2006, IEEE Transactions on Information Theory.

[11]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[12]  H. Vincent Poor,et al.  Noisy-Interference Sum-Rate Capacity for Vector Gaussian Interference Channels , 2011, IEEE Transactions on Information Theory.

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

[14]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[15]  Bo Wang,et al.  On the capacity of MIMO relay channels , 2005, IEEE Transactions on Information Theory.

[16]  James L. Massey,et al.  Proper complex random processes with applications to information theory , 1993, IEEE Trans. Inf. Theory.

[17]  Chris T. K. Ng,et al.  Transmit Signal and Bandwidth Optimization in Multiple-Antenna Relay Channels , 2010, IEEE Transactions on Communications.