Video Multicast With Joint Resource Allocation and Adaptive Modulation and Coding in 4G Networks
- Authors
- Yoon, Jongwon; Zhang, Honghai; Banerjee, Suman; Rangarajan, Sampath
- Issue Date
- Oct-2014
- Publisher
- Institute of Electrical and Electronics Engineers
- Keywords
- 4G cellular; algorithm; orthogonal frequency-division multiple access (OFDMA); optimization; resource allocation; video multicast; WiMAX
- Citation
- IEEE/ACM Transactions on Networking, v.22, no.5, pp.1531 - 1544
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE/ACM Transactions on Networking
- Volume
- 22
- Number
- 5
- Start Page
- 1531
- End Page
- 1544
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/21589
- DOI
- 10.1109/TNET.2013.2279887
- ISSN
- 1063-6692
- Abstract
- Although wireless broadband technologies have evolved significantly over the past decade, they are still insufficient to support the fast-growing mobile traffic, especially due to the increasing popularity of mobile video applications. Wireless multicast, aiming to exploit the wireless broadcast advantage, is a viable approach to bridge the gap between the limited wireless capacity and the ever-increasing mobile video traffic demand. In this paper, we propose MuVi, a Multicast Video delivery scheme through joint optimal resource allocation and adaptive modulation and coding scheme in OFDMA-based 4G cellular networks. MuVi differentiates video frames based on their importance in reconstructing the video and incorporates an efficient radio resource allocation algorithm to optimize the overall video quality across all users in the multicast group. MuVi is a lightweight solution with most of the implementation in the gateway, slight modification in the base station, and no modification at the clients. We implement MuVi on a WiMAX testbed and compare its performance to a Naive wireless multicast scheme that employs the most robust Modulation and Coding Scheme (MCS), and an Adaptive scheme that employs the highest MCS supportable by all clients. Experimental results show that MuVi improves the average video peak signal-to-noise ratio (PSNR) by up to 13 and 7 dB compared to the Naive and the Adaptive schemes, respectively. MuVi does not require modification to the video encoding scheme or the air interface. Thus, it allows speedy deployment in existing systems.
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