Multicast in Networks of Broadcast Channels—Part II: Representation of Bounds on the Multicast Capacity Region

We apply the polymatroid broadcast model to inner and outer bounds on the multicast capacity region of networks of broadcast channels, which are a suitable network model to represent the wireless broadcast advantage in wireless networks. The considered model allows for a channel state such that the state sequence is noncausally known to all nodes to model for example medium access mechanisms. We establish that the cut-set outer bound and the noisy network coding inner bound with independent output quantization admit a formulation in the polymatroid broadcast model proposed in Part I for networks of broadcast channels with independent noise, i.e., the channel outputs are independent across all nodes given the channel inputs and the channel state. This applies in particular to networks of deterministic broadcast channels and networks of erasure broadcast channels with independent erasures given the channel state. The polymatroid broadcast structure inherent to these two bounds enables us to characterize the corresponding multicast rate regions by means of the weighted sum multicast rate maximization problem, which can be solved using the dual decomposition approach in Part I, which is based on the polymatroid broadcast model. For networks of erasure broadcast channels, we propose a simple erasure quantization strategy for noisy network coding based on this dual decomposition approach and submodular maximization. This approach achieves a sum rate performance that is close to the cut set outer bound, which is demonstrated in a bidirectional communication example.

[1]  Anthony Ephremides,et al.  On packet lengths and overhead for random linear coding over the erasure channel , 2007, IWCMC.

[2]  Gerhard Kramer,et al.  The multicast capacity of deterministic relay networks with no interference , 2006, IEEE Transactions on Information Theory.

[3]  Tracey Ho,et al.  Network Coding: An Introduction , 2008 .

[4]  Sung Hoon Lim,et al.  Distributed decode-forward for multicast , 2014, 2014 IEEE International Symposium on Information Theory.

[5]  Wolfgang Utschick,et al.  A Polymatroid Flow Model for Network Coded Multicast in Wireless Networks , 2014, IEEE Transactions on Information Theory.

[6]  Maximilian Riemensberger Submodular rate region models for multicast communication in wireless networks , 2017 .

[7]  Sae-Young Chung,et al.  Noisy Network Coding , 2010, IEEE Transactions on Information Theory.

[8]  Mohammad Reza Aref,et al.  Slepian–Wolf Coding Over Cooperative Relay Networks , 2011, IEEE Transactions on Information Theory.

[9]  U. Feige,et al.  Maximizing Non-monotone Submodular Functions , 2011 .

[10]  Ashutosh Sabharwal,et al.  Bounds on Achievable Rates for General Multi-terminal Networks with Practical Constraints , 2003, IPSN.

[11]  Mohammad Reza Aref,et al.  Information flow in relay networks , 1981 .

[12]  Tracey Ho,et al.  A Random Linear Network Coding Approach to Multicast , 2006, IEEE Transactions on Information Theory.

[13]  M. L. Fisher,et al.  An analysis of approximations for maximizing submodular set functions—I , 1978, Math. Program..

[14]  Satoru Fujishige,et al.  Polymatroidal Dependence Structure of a Set of Random Variables , 1978, Inf. Control..

[15]  Muriel Médard,et al.  On coding for reliable communication over packet networks , 2005, Phys. Commun..

[16]  Gerhard Kramer,et al.  Short Message Noisy Network Coding With a Decode–Forward Option , 2013, IEEE Transactions on Information Theory.

[17]  Abbas El Gamal,et al.  Network Information Theory , 2021, 2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT).

[18]  Muriel Médard,et al.  Scheduling for Network-Coded Multicast , 2012, IEEE/ACM Transactions on Networking.

[19]  Fang Zhao,et al.  Minimum-cost multicast over coded packet networks , 2005, IEEE Transactions on Information Theory.

[20]  Babak Hassibi,et al.  Capacity of wireless erasure networks , 2006, IEEE Transactions on Information Theory.

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

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

[23]  Gerhard Kramer,et al.  Short message noisy network coding for multiple sources , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[24]  Abdel R. El Gamal,et al.  On information flow in relay networks , 1981 .