Implementing Statistical Multiplexing in DVB-H

Abstract

A novel technique for implementing statistical multiplexing (StatMux) of broadcast services over Digital Video Broadcasting for Handhelds (DVB-H) channels is proposed. DVB-H uses a time-sliced transmission scheme to reduce the power consumption used for radio reception part in DVB-H receivers. Due to the time-sliced transmission scheme, the implementation of known StatMux methods for DVB-H application presents some challenges which are addressed in this paper. The proposed StatMux technique is implemented in conjunction with the time-slicing transmission scheme. The combination is similar to a time division multiplexing (TDM) scheme. The proposed StatMux method considerably decreases the end-to-end delay of DVB-H services while it maximizes the usage of available bandwidth. Moreover, the proposed method can effectively decrease the channel switching delay of DVB-H services. Simulation results show a high performance for the proposed StatMux method.

Predictive Encoder and Buffer Control for Statistical Multiplexing of Multimedia Contents

“…QoS is related to both buffer load and delay (probability of buffer overflow and delay violation). Rate control and buffering delay are also addressed in [11] where a technique for performing SM in conjunction with time slicing in DVB-H, implemented in the IP encapsulator is proposed. This method achieves a satisfactory use of the channel rate and a minimum buffering delay for all multiplexed programs.…”

“…This method achieves a satisfactory use of the channel rate and a minimum buffering delay for all multiplexed programs. Nevertheless, in both [11] and [12], no constraint on the video quality is considered.…”

“…Apart from the optimal use of the available channel rate, SM systems may target the satisfaction of several constraints linked to the quality-of-service (QoS) of the delivered programs, including video quality and transmission delay. For example, SM systems may be designed in such a way that • programs are encoded with a minimum quality (minimum quality constraint [8]), • programs are encoded with similar quality (fairness constraint [9]), • the quality of each decoded program varies smoothly with time (smoothness constraint [10]), • latency at the receiver side, including switching between programs, is minimized [11]. Finding a SM system able to satisfy simultaneously all these constraints in the context of video broadcasting is still a challenging task.…”

Efficient mobile multimedia streaming

“…Rezaei et al [104] propose a burst scheduling algorithm for mobile TV networks. They divide the broadcast time into fixed-length scheduling windows, and then schedule all video streams in round-robin fashion in each window.…”

“…We note that a small lookahead window is a reasonable assumption because many programs are prerecorded, while live streams are often delayed to allow censoring and editing. Since the work in [104] probabilistically schedules bursts, it has to wake up receiving circuits earlier to accommodate any prediction errors. Therefore, its energy saving can never be better than the current base stations in closed-loop networks, which employ the same round-robin scheduling but use actual frame sizes which are more accurate than the predicted frame sizes.…”