The Design of Transport Block-Based ROHC U-Mode for LTE Multicast

One important issue that confronts multicast service is multiple-user satisfaction under dynamic channel conditions over cellular networks. In practical Long Term Evolution (LTE) networks, a key mechanism that affects the transmission efficiency and robustness for each user is RObust Header Compression (ROHC). In this work, we improve the transmission performance of multicast aiming at satisfying all the users with a trans-layer design scheme. We first establish a practical system model for trans-layer multicast networks, with transport blocks (TBs) as the transmission units. Focusing on the optimization of ROHC, we formulate a novel trans-layer control framework in terms of partially observable Markov decision process (POMDP) to maximize the total number of successfully received payload bits among all users in one Multimedia Broadcast Multicast Service (MBMS). To address the complexity issue of the rigorous POMDP formulation, we further develop an Instantaneous Marginal Belief (IMB) policy algorithm to handle multiple-user. Our numerical results demonstrate substantial improvements by the proposed policy.

[1]  Marco Wiering,et al.  Reinforcement Learning , 2014, Adaptation, Learning, and Optimization.

[2]  Frank H. P. Fitzek,et al.  Performance evaluation and comparison of RObust Header Compression (ROHC) ROHCv1 and ROHCv2 for multimedia delivery , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[3]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[4]  Radford M. Neal Pattern Recognition and Machine Learning , 2007, Technometrics.

[5]  Nan Rong,et al.  What makes some POMDP problems easy to approximate? , 2007, NIPS.

[6]  Zhi Ding,et al.  On Efficient Packet-Switched Wireless Networking: A Markovian Approach to Trans-Layer Design and Optimization of ROHC , 2017, IEEE Transactions on Wireless Communications.

[7]  Nokia Siemens Channel-Aware Frequency Domain Packet Scheduling for MBMS in LTE , 2009 .

[8]  Hong Shen Wang,et al.  Finite-state Markov channel-a useful model for radio communication channels , 1995 .

[9]  Thomas Stockhammer,et al.  Video Streaming over MBMS: A System Design Approach , 2006, J. Multim..

[10]  Andrew G. Barto,et al.  Reinforcement learning , 1998 .

[11]  Carsten Bormann,et al.  RObust Header Compression (ROHC): Framework and four profiles: RTP, UDP, ESP, and uncompressed , 2001, RFC.

[12]  Zhi Ding,et al.  IP packet header compression and user grouping for LTE Multimedia Broadcast Multicast Services , 2017, 2017 International Conference on Computing, Networking and Communications (ICNC).

[13]  Matteo Berioli,et al.  On the Behavior of RObust Header Compression U-mode in Channels with Memory , 2013, IEEE Transactions on Wireless Communications.

[14]  Zhi Ding,et al.  LTE Multimedia Broadcast Multicast Service Provisioning Based on Robust Header Compression , 2018, IEEE Transactions on Wireless Communications.

[15]  Winston Khoon Guan Seah,et al.  A framework and source model for design and evaluation of Robust Header Compression , 2006, Comput. Networks.

[16]  John S. Thompson,et al.  Bandwidth and energy efficiency of video broadcasting services over LTE/LTE-A , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[17]  G. Monahan State of the Art—A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms , 1982 .

[18]  David Hsu,et al.  SARSOP: Efficient Point-Based POMDP Planning by Approximating Optimally Reachable Belief Spaces , 2008, Robotics: Science and Systems.