Deterministic capacity modeling for cellular channels: building blocks, approximate regions, and optimal transmission strategies

One of the tools that arised in the context of capacity approximations is the linear deterministic model (LDM), which aims at approximating the physical channel by a deterministic bit vector mapping. In this paper, we give a brief review of the LDM and the corresponding models for some of the basic network building blocks. We then go on to demonstrate how the LDM can be applied to a two-user multiple access channel mutually interfering with a point to point link. This constitutes a basic model for a cellular channel and also for the situation of device-to-device communication inside a cell. We give the capacity region for weak interference, the sum capacity for arbitrary interference and apply the results to the Gaussian channel in order to obtain a lower bound on the achievable generalized degrees of freedom in the system.

[1]  Hua Wang,et al.  Gaussian Interference Channel Capacity to Within One Bit , 2007, IEEE Transactions on Information Theory.

[2]  Aydin Sezgin,et al.  On the Capacity of the 2-user Gaussian MAC Interfering with a P2P Link , 2011, EW.

[3]  Gerhard Wunder,et al.  On interference alignment and the deterministic capacity for cellular channels with weak symmetric cross links , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[4]  Suhas N. Diggavi,et al.  Wireless Network Information Flow: A Deterministic Approach , 2009, IEEE Transactions on Information Theory.

[5]  Suhas N. Diggavi,et al.  A Deterministic Approach to Wireless Relay Networks , 2007, ArXiv.

[6]  Syed Ali Jafar,et al.  Interference alignment and the generalized degrees of freedom of the X channel , 2009, ISIT.

[7]  Gerhard Wunder,et al.  The multiple access channel interfering with a point to point link: Linear deterministic sum capacity , 2012, 2012 IEEE International Conference on Communications (ICC).

[8]  Abbas El Gamal,et al.  On the sum capacity of a class of cyclically symmetric deterministic interference channels , 2009, 2009 IEEE International Symposium on Information Theory.

[9]  Sriram Vishwanath,et al.  Generalized Degrees of Freedom of the Symmetric Gaussian $K$ User Interference Channel , 2010, IEEE Transactions on Information Theory.

[10]  Roy D. Yates,et al.  Fading broadcast channels with state information at the receivers , 2009, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

[11]  Sriram Vishwanath,et al.  The capacity region of a class of deterministic Z channels , 2009, 2009 IEEE International Symposium on Information Theory.

[12]  Abhay Parekh,et al.  The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels , 2008, IEEE Transactions on Information Theory.

[13]  David Tse,et al.  The two-user Gaussian interference channel: a deterministic view , 2008, Eur. Trans. Telecommun..