A simulation study of video conferencing system over IEEE 802.11n Wireless LAN

Wireless local area network (WLAN) is the core of the classic wireless communications systems and owns the infrastructure which wide spreads in many regions in the world. IEEE 802.11n is an attractive standard of WLAN and offers a data capacity of the cell. This paper estimates the maximum limits of the IEEE 802.11n standard cell as a term of number of users which are successfully served by the cell in case of video conference application. The results shown that, the cell of 802.11n could serve about 9 users under the service of video conference in case of 20MHz channel bandwidth before congestion occurs while the 40MHz channel could support 18 users

Delay-Power-Rate-Distortion Optimization of Video Representations for Dynamic Adaptive Streaming

Dynamic adaptive streaming addresses user heterogeneity by providing multiple encoded representations at different rates and/or resolutions for the same video content. For delay-sensitive applications, such as live streaming, there is however a stringent requirement on the encoding delay, and usually the encoding power (or rate) budget is also limited by the computational (or storage) capacity of the server. It is therefore important, yet challenging, to optimally select the source coding parameters for each encoded representation in order to minimize the resource consumption while maintaining a high quality of experience for the users. To address this, we propose an optimization framework with an optimal representation selection problem for delay, power, and rate constrained adaptive video streaming. Then, by the optimal selection of source coding parameters for each selected representation, we maximize the overall expected user satisfaction, subject not only to the encoding rate constraint, but also to the delay and power constraints at the server. We formulate the proposed optimization problem as an integer linear program formulation to provide the performance upper bound, and as a submodular maximization problem with two knapsack constraints to develop a practically feasible algorithm. Simulation results show that the proposed weighted rate and power cost benefit greedy algorithm is able to achieve a near-optimal performance with very low time complexity. In addition, it can strike the best tradeoff both between the rate and power cost, and between the algorithm's performance and the delay requirements proposed by delay sensitive applications