Video streaming over cognitive radio networks

Abstract

In recent years, there has been a tremendous growth in multimedia applications over the wireless Internet. The significant bandwidth requirement for multimedia services has increased the demand for radio spectrum. The scarcity of radio spectrum has challenged the conventional fixed spectrum assignment policy. As a result, cognitive radio emerged as a new paradigm to address the spectrum underutilization problem by enabling users to opportunistically access unused spectrum bands. In this thesis, we propose a framework for video transmission over cognitive radio networks. Our objective is to determine the optimal streaming policy in order to maximize the overall perceived video quality while keeping quality fluctuation at minimum. In our framework, we introduce a channel usage model based on a two-state Markov model and estimate the future busy and idle durations of the spectrum based on past observations. On the basis of this scheme, we formulate the streaming optimization problem under the constraint of the available bandwidth budget so that the optimal number of enhancement layer bits are assigned to each frame. We extend this algorithm for three different optimization levels: frame, GOP and scene. We evaluate our algorithm through extensive trace-driven simulation, and show that it improves the perceived video quality and increases bandwidth utilization.

Multimedia Communication over Cognitive Radio Networks from QoS/QoE Perspective; A Comprehensive Survey

“…The authors in [231] introduced a channel usage model based on a two-state Markov model and estimated the future busy and idle duration of the channels based on the previous monitoring results. The main objective was to optimize the bit rate of the ELs according to the available channel condition.…”

Window‐based adaptive technique for real‐time streaming of scalable video over cognitive radio networks

“…A Markovian game problem with dynamic switching control was formulated in [9] to improve the resultant video quality of multiple SUs with different data rates. A two‐state Markov model was used in [10] to model the channel to optimise the bit rate of the enhancement layers (ELs) of the video frames transmitted under bandwidth constraints with the objective of minimising any possible fluctuations in the reconstructed quality. The channel availability was modelled as an on–off Markov process in [11], then an optimisation framework was formulated for the channel allocation problem which considered the playback buffer storage of the SUs as well as the bandwidth capacity with the objective of maximising the overall network throughput while ensuring smooth video playback at the SUs.…”