Interference Channel with Constrained Partial Group Decoding

We propose novel coding and decoding methods for a fully connected K-user Gaussian interference channel. Each transmitter encodes its information into multiple layers and transmits the superposition of those layers. Each receiver employs a constrained partial group decoder (CPGD) that decodes its designated message along with a part of the interference. In particular, each receiver performs a twofold task by first identifying which interferers it should decode and then determining which layers of them should be decoded. Determining the layers to be decoded and decoding them are carried out in a successive manner, where in each step a group of layers with a constraint on its group size is identified and jointly decoded while the remaining layers are treated as Gaussian noise. The decoded layers are then subtracted from the received signal and the same procedure is repeated for the remaining layers. We provide a distributed algorithm, tailored to the nature of the interference channels, that determines the transmission rate at each transmitter based on some optimality measure and also finds the order of the layers to be successively decoded at each receiver. We also consider practical design of a system that employs the quadrature amplitude modulations (QAM) and rateless codes. Numerical results are provided on the achievable sum-rate under the ideal case of Gaussian signaling with random codes as well as on the system throughput under practical modulations and channel codes. The results show that the proposed multi-layer coding scheme with CPGD offers significant performance gain over the traditional un-layered transmission with single-user decoding.

[1]  Syed Ali Jafar,et al.  Interference Alignment and Degrees of Freedom of the $K$-User Interference Channel , 2008, IEEE Transactions on Information Theory.

[2]  Xiaodong Wang,et al.  Outage Minimization and Rate Allocation for the Multiuser Gaussian Interference Channels With Successive Group Decoding , 2009, IEEE Transactions on Information Theory.

[3]  Giuseppe Caire,et al.  Bit-Interleaved Coded Modulation , 2008, Found. Trends Commun. Inf. Theory.

[4]  Xiaodong Wang,et al.  Fair rate adaptation in multiuser interference channels , 2010, 2010 IEEE International Symposium on Information Theory.

[5]  Te Sun Han,et al.  A new achievable rate region for the interference channel , 1981, IEEE Trans. Inf. Theory.

[6]  Stephan ten Brink,et al.  Design of low-density parity-check codes for modulation and detection , 2004, IEEE Transactions on Communications.

[7]  Xiaodong Wang,et al.  Beamforming and Rate Allocation in MISO Cognitive Radio Networks , 2009, IEEE Transactions on Signal Processing.

[8]  Omid Etesami,et al.  Raptor codes on binary memoryless symmetric channels , 2006, IEEE Transactions on Information Theory.

[9]  Rüdiger L. Urbanke,et al.  Design of capacity-approaching irregular low-density parity-check codes , 2001, IEEE Trans. Inf. Theory.

[10]  Guosen Yue,et al.  Analysis and optimization of a rateless coded joint relay system , 2010, IEEE Transactions on Wireless Communications.

[11]  Amir K. Khandani,et al.  Communication Over MIMO X Channels: Interference Alignment, Decomposition, and Performance Analysis , 2008, IEEE Transactions on Information Theory.

[12]  Amir K. Khandani,et al.  To Decode the Interference or to Consider It as Noise , 2007, IEEE Transactions on Information Theory.