CAJ | 학술논문

现有无线分组调度算法一般以最大化系统吞吐量或者保证用户之间公平性为目标。然而，不同视频分组之间存在着重要性差异，使得传统的内容无关调度算法不适用于无线视频传输。充分发掘视频分组之间存在的重要性差异并准确衡量视频分组的传输失真，能够在资源受限的无线环境下更合理地分配资源，提高视频传输质量。该文首先提出一种分组级别视频传输失真衡量模型，用于预测视频分组丢失对视频质量的影响，然后考虑分组时限的影响，提出分组级别的时限扩展模型。在此基础上，利用正交频分复用(OFDM)技术在无线资源(时域、频域及功率)分配上的灵活性，提出一种基于梯度的失真和时限感知调度算法。仿真结果表明该文所提出的调度算法相对于传统内容无关算法最大有4.3 dB的平均峰值信噪比(PSNR)增益。
현유무선분조조도산법일반이최대화계통탄토량혹자보증용호지간공평성위목표。연이，불동시빈분조지간존재착중요성차이，사득전통적내용무관조도산법불괄용우무선시빈전수。충분발굴시빈분조지간존재적중요성차이병준학형량시빈분조적전수실진，능구재자원수한적무선배경하경합리지분배자원，제고시빈전수질량。해문수선제출일충분조급별시빈전수실진형량모형，용우예측시빈분조주실대시빈질량적영향，연후고필분조시한적영향，제출분조급별적시한확전모형。재차기출상，이용정교빈분복용(OFDM)기술재무선자원(시역、빈역급공솔)분배상적령활성，제출일충기우제도적실진화시한감지조도산법。방진결과표명해문소제출적조도산법상대우전통내용무관산법최대유4.3 dB적평균봉치신조비(PSNR)증익。
Most of current wireless packet scheduling algorithms aim at maximizing overall system throughput or achieving a certain type of fairness among mobile users. However, these content-independent algorithms can not be applied to wireless video transmission because different video packets have different levels of contribution to the overall video quality at the receiver side. Fully exploring the differences between the video packets and accurate predicting the transmission distortion caused by lost video packets can significantly improve the performance of video streaming over resource-constrained wireless networks. In this paper, a packet-level transmission distortion model is proposed to predict the quality degradation of decoded videos by lost video packets, the packet-level deadline is defined to extend the model. Based on this packet-level transmission distortion model and packet-level deadline extended model, a gradient-based distortion and deadline aware scheduling algorithm is proposed, which prioritizes the transmissions of different users by considering distortion impact, deadline requirements and fully exploit the flexibility of resource allocation provided by the Orthogonal Frequency Division Multiplexing (OFDM) technology in terms of time, frequency and power. The experimental results demonstrate that the proposed algorithm outperforms the content-independent algorithms with a gain of as much as 4.3 dB in terms of average Peak Signal-to-Noise Ratio (PSNR).