Flow Level QoE of Video Streaming in Wireless Networks

The Quality of Experience (QoE) of streaming service is often degraded by frequent playback interruptions. To mitigate the interruptions, the media player prefetches streaming contents before starting playback, at a cost of delay. We study the QoE of streaming from the perspective of flow dynamics. First, a framework is developed for QoE when streaming users join the network randomly and leave after downloading completion. We compute the distribution of prefetching delay using partial differential equations (PDEs), and the probability generating function of playout buffer starvations using ordinary differential equations (ODEs) for CBR streaming. Second, we extend our framework to characterize the throughput variation caused by opportunistic scheduling at the base station, and the playback variation of VBR streaming. Our study reveals that the flow dynamics is the fundamental reason of playback starvation. The QoE of streaming service is dominated by the first moments such as the average throughput of opportunistic scheduling and the mean playback rate. While the variances of throughput and playback rate have very limited impact on starvation behavior.Comment: 14 page

Spatial CSMA: A Distributed Scheduling Algorithm for the SIR Model with Time-varying Channels

Recent work has shown that adaptive CSMA algorithms can achieve throughput optimality. However, these adaptive CSMA algorithms assume a rather simplistic model for the wireless medium. Specifically, the interference is typically modelled by a conflict graph, and the channels are assumed to be static. In this work, we propose a distributed and adaptive CSMA algorithm under a more realistic signal-to-interference ratio (SIR) based interference model, with time-varying channels. We prove that our algorithm is throughput optimal under this generalized model. Further, we augment our proposed algorithm by using a parallel update technique. Numerical results show that our algorithm outperforms the conflict graph based algorithms, in terms of supportable throughput and the rate of convergence to steady-state.Comment: This work has been presented at National Conference on Communication, 2015, held at IIT Bombay, Mumbai, Indi

A Queueing Characterization of Information Transmission over Block Fading Rayleigh Channels in the Low SNR

Unlike the AWGN (additive white gaussian noise) channel, fading channels suffer from random channel gains besides the additive Gaussian noise. As a result, the instantaneous channel capacity varies randomly along time, which makes it insufficient to characterize the transmission capability of a fading channel using data rate only. In this paper, the transmission capability of a buffer-aided block Rayleigh fading channel is examined by a constant rate input data stream, and reflected by several parameters such as the average queue length, stationary queue length distribution, packet delay and overflow probability. Both infinite-buffer model and finite-buffer model are considered. Taking advantage of the memoryless property of the service provided by the channel in each block in the the low SNR (signal-to-noise ratio) regime, the information transmission over the channel is formulated as a \textit{discrete time discrete state} $D/G/1$ queueing problem. The obtained results show that block fading channels are unable to support a data rate close to their ergodic capacity, no matter how long the buffer is, even seen from the application layer. For the finite-buffer model, the overflow probability is derived with explicit expression, and is shown to decrease exponentially when buffer size is increased, even when the buffer size is very small.Comment: 29 pages, 11 figures. More details on the proof of Theorem 1 and proposition 1 can be found in "Queueing analysis for block fading Rayleigh channels in the low SNR regime ", IEEE WCSP 2013.It has been published by IEEE Trans. on Veh. Technol. in Feb. 201

Prediction of performance of the DVB-SH system relying on mutual information

DVB-SH (Digital Video Broadcasting-Satellite Handled) is a broadcasting standard dedicated to hybrid broadcasting systems combining a satellite and a terrestrial part. On the satellite part, dedicated interleaving and time slicing mechanisms are proposed to mitigate the effects of Land Mobile Satellite (LMS) channel, based on a convolutional interleaver. Depending on the parameters of this interleaver, this mechanism enables to split in time a codeword on duration from 100 ms to about 30s. This mechanism signi?cantly improves the error recovery performance of the code but in literature, exact evaluation at system level of this improvement is missing. The objective of this paper is to propose a prediction method compatible with fast simulations, to quantitatively evaluate the system performance in terms of Packet Error Rate (PER). The main dif?culty is to evaluate the decoding probability of a codeword submitted to several levels of attenuation. The method we propose consists in using as metric the Mutual Information (MI) between coded bit at the emitter side and the received symbol. It is shown that, by averaging the MI over the codeword and by using the decoding performance function g such that PER=g(MI)determined on the Gaussian channel, we can signi?cantly improve the precision of the prediction compared to the two other methods based on SNR and Bit Error Rate (BER). We evaluated these methods on three arti?cial channels where each codeword is transmitted with three or four different levels of attenuations. The prediction error of the SNR-based (resp. the input BER-based) method varies from 0.5 to 1.7 dB (resp. from 0.7 to 1.2 dB) instead of the MI-based method achieves a precision in the order of 0.1 dB in the three cases. We then evaluate this method on real LMS channels with various DVB-SH interleavers and show that the instantaneous PER can also be predicted with high accuracy