Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems

Abstract

We consider multiuser video communication over uplink orthogonal frequency-division multiple access (OFDMA) systems. A cross-layer algorithm of joint bit allocation, packet scheduling and wireless resource assignment are proposed to minimize the end-to-end expected video distortion. Video rate adaptation is performed under the wireless resource constraints. The target number of encoding bits for each video packet is obtained to minimize the estimated distortion based on the online content-based rate-distortion function. Due to the inaccuracy of the rate control algorithm in H.265/HEVC encoding, the actual number of bits may differ from the target. Accordingly, the actual encoder distortion may deviate from the estimated distortion. Then, we propose an iterative algorithm to re-assign wireless resources based on the actual number of encoded bits to obtain the final resource allocation policy and packet scheduling decision. Numerical simulation results show that our proposed approach significantly outperforms the baseline algorithms in terms of received video quality.

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References

  1. 1.

    Awad MK, Mahinthan V, Mehrjoo M, Shen X, Mark JW (2010) A dual-decomposition-based resource allocation for OFDMA networks with imperfect CSI. IEEE Trans Vehi Technol 59(5):2394–2403

    Article  Google Scholar 

  2. 2.

    Biagioni A, Fantacci R, Marabissi D, Tarchi H (2009) Adaptive subcarrier allocation schemes for wireless OFDMA systems in WiMAX networks. IEEE J Sel Areas Commun 27(2):217–225

    Article  Google Scholar 

  3. 3.

    Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, Cambridge

    Google Scholar 

  4. 4.

    Cicalo S, Tralli V (2014) Distortion-fair cross-layer resource allocation for scalable video transmission in OFDMA wireless networks. IEEE Trans Multimed 16(3):848–863

    Article  Google Scholar 

  5. 5.

    Dani MN, AI-Abbasi ZQ, So DKC (2017) Power allocation for layered multicast video streaming in non-orthogonal multiple access system. In: Proceedings of the IEEE GLOBECOM workshops, pp 1–6

  6. 6.

    de la Fuente A, Escudero-Garzás JJ, García-Armada A (2017) Radio resource allocation for multicast services based on multiple video layers. IEEE Trans Broadcast. https://doi.org/10.1109/TBC.2017.2781121

  7. 7.

    Feng T, Field TR (2008) Statistical analysis of mobile radio reception: an extension of Clarke’s model. IEEE Trans Commun 56(12):2007–2012

    Article  Google Scholar 

  8. 8.

    Gao L, Cui S (2008) Efficient subcarrier, power, and rate allocation with fairness consideration for OFDMA uplink. IEEE Trans Wireless Commun 7(5):1507–1511

    Article  Google Scholar 

  9. 9.

    He L, Liu G (2014) Quality-driven cross-layer design for H.264/AVC video transmission over OFDMA system. IEEE Trans Wireless Commun 13(12):6768–6782

    Article  Google Scholar 

  10. 10.

    He Z, Cai J, Chen CW (2002) Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding. IEEE Trans Circ Syst Video Technol 12(6):511–523

    Article  Google Scholar 

  11. 11.

    HEVC Test Model 15.0 (2014) [Online]. Available: http://hevc.kw.bbc.co.uk/git/w/jctvc-tmuc.git

  12. 12.

    JCTVC-K0103 Rate control by R-lambda model for HEVC Shanghai (2012)

  13. 13.

    Ji X, Huang J, Chiang M, Lafruit G, Catthoor F (2009) Scheduling and resource allocation for SVC streaming over OFDM downlink systems. IEEE Trans Circ Syst Video Technol 19(10):1549–1555

    Article  Google Scholar 

  14. 14.

    Jung YH, Song Q, Kim KH, Cosman P, Milstein L (2017) Cross-layer resource allocation using video slice header information for wireless transmission over LTE. IEEE Trans Circ Syst Video Technol. https://doi.org/10.1109/TCSVT.2017.2701503

  15. 15.

    Kim K, Han Y, Kim S-L (2005) Joint subcarrier and power allocation in uplink OFDMA systems. IEEE Commun Lett 9(6):526–528

    Article  Google Scholar 

  16. 16.

    Le H, Behboodi A, Wolisz A (2015) Quality driven resource allocation for adaptive video streaming in OFDMA uplink. In: Proceedings of the 26th annual international symposium on personal indoor, and mobile radio communications (PIMRC), pp 1277–1282

  17. 17.

    Li F, Liu G, He L (2009) Application-driven cross-layer approaches to video transmission over downlink OFDMA networks. In: Proceedings of the IEEE GLOBECOM workshops, pp 1–6

  18. 18.

    Li F, Ren P, Du Q (2012) Joint packet scheduling and subcarrier assignment for video communication over downlink OFDMA systems. IEEE Trans Vehi Technol 61(6):2753–2767

    Article  Google Scholar 

  19. 19.

    Li F, Fu S, Liu Z, Qian X (2018) A Cost-constrained video quality satisfaction study on mobile devices. IEEE Trans Multimed 20(5):1154–1168

    Article  Google Scholar 

  20. 20.

    Ng CY, Sung CW (2008) Low complexity subcarrier and power allocation for utility maximization in uplink OFDMA systems. IEEE Trans Wireless Commun 7(5):1667–1675

    Article  Google Scholar 

  21. 21.

    Qian L, Cheng Z, Fang Z, Ding L, Yang F, Huang W (2017) A QoE-driven encoder adaptation scheme for multi-user video streaming in wireless networks. IEEE Trans Broadcast 63(1):20–31

    Article  Google Scholar 

  22. 22.

    Rohling M, May T, Bruninghaus K, Grunheid R (1999) Broadband OFDM radio transmission for multimedia application. Proc IEEE 87(10):1778–1789

    Article  Google Scholar 

  23. 23.

    Sabir MF, Heath RW, Bovik AC (2009) Joint source-channel distortion modeling for MPEG-4 video. IEEE Trans Image Process 18(1):90–105

    MathSciNet  Article  MATH  Google Scholar 

  24. 24.

    Tseng S-M, Chen Y-F (2018) Average PSNR optimized cross layer user grouping and resource allocation for uplink MU-MIMO OFDMA video communications. IEEE Access 6:50559–50571

    Article  Google Scholar 

  25. 25.

    Wang D, Toni L, Cosman PC, Milstein LB (2013) Uplink resource management for multiuser OFDM video transmission systems: analysis and algorithm design. IEEE Trans Commun 61(5):2060–2073

    Article  Google Scholar 

  26. 26.

    Wu D, Yu D, Cai Y (2008) Subcarrier and power allocation in uplink OFDMA systems based on game theory. In: Proceedings of the IEEE international conference on neural networks and signal processing, pp 522–526

  27. 27.

    Wu P-H, Huang C-W, Hwang J-N, Pyun J-Y, Zhang J (2015) Video-quality-driven resource allocation for real-time surveillance video uplinking over OFDMA-based wireless networks. IEEE Trans Veh Technol 64(7):3233–3246

    Google Scholar 

  28. 28.

    Zhang R, Regunathan SL, Rose K (2000) Video encoding with optimal inter/intra-mode switching for packet loss resilience. IEEE J Sel Areas Commun 18(6):966–976

    Article  Google Scholar 

  29. 29.

    Zhang H, Ma Y, Yuan D, Chen HH (2011) Quality-of-service driven power and subcarrier allocation policy for vehicular communication networks. IEEE J Sel Areas Commun 29(1):197–206

    Article  Google Scholar 

  30. 30.

    Zhang Z, Liu D, Wang X (2018) Joint carrier matching and power allocation for wireless video with general distortion measure. IEEE Trans Mobile Comput 17 (3):577–589

    Article  Google Scholar 

  31. 31.

    Zhou N, Zhu X, Huang Y, Lin H (2010) Low-complexity cross-layer design with packet-dependent scheduling for heterogeneous traffic in multiuser OFDM systems. IEEE Trans Wireless Commun 9(6):1912–1923

    Article  Google Scholar 

Download references

Acknowledgements

This research work was supported in part by the National Science Foundation of China Project No.61671365, and Joint Foundation of Ministry of Education of China No.6141A02022344.

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Correspondence to Fan Li.

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Appendix: R-D parameter updating

Appendix: R-D parameter updating

We use the LMS method to derive the update formulation of the R-D parameters (4). For simplicity, we use Dest, a, b and r to represent \(D_{k,m}^{est}\), \(a_{k,m}^{est}\), \(b_{k,m}^{est}\) and Rk, m/Ik, m, respectively. We take the logarithm for both side of (4).

$$ \begin{array}{@{}rcl@{}} &&{D^{est}} = a \cdot {r^{- b}}\\ &&\Rightarrow \ln {D^{est}} = \ln a - b \cdot \ln r\buildrel {\Delta} \over = a^{\prime} - b \cdot \ln r \end{array} $$
(27)

where a = ln a. The squared error between the predicted distortion Dest and actual distortion Dact can be expressed as

$$ {e^{2}} = {\left( {\ln {D^{est}} - \ln {D^{act}}} \right)^{2}} $$
(28)

Taking the derivatives with respect to a and b, we have

$$ \begin{array}{@{}rcl@{}} &&\frac{{\partial {e^{2}}}}{{\partial a^{\prime}}} = 2\left( {\ln {D^{est}} - \ln {D^{act}}} \right)\\ &&\frac{{\partial {e^{2}}}}{{\partial b}} = 2\left( {\ln {D^{est}} - \ln {D^{act}}} \right)\left( { - \ln r} \right) \end{array} $$
(29)

According to the adaptive Least Mean Square (LMS) method

$$ {a^{\prime}_{new}} = {a^{\prime}_{old}} - {\delta_{a}}\left( {\ln {D^{est}} - \ln {D^{act}}} \right) $$
(30)

where δa is the update step of a. Therefore,

$$ \begin{array}{@{}rcl@{}} \ln {a_{new}} &=& \ln {a_{old}} - {\delta_{a}}\left( {\ln {D^{est}} - \ln {D^{act}}} \right)\\ {a_{new}}& =& {a_{old}}{e^{- {\delta_{a}}\left( {\ln {D^{est}} - \ln {D^{act}}} \right)}} \end{array} $$
(31)

After Taylor’s expansion and ignoring high-order terms,

$$ \begin{array}{@{}rcl@{}} {a_{new}} &=& {a_{old}}\left( {1 - {\delta_{a}}\left( {\ln {D^{est}} - \ln {D^{act}}} \right)} \right)\\ &=& {a_{old}} - {\delta_{a}}\left( {\ln {D^{est}} - \ln {D^{act}}} \right){a_{old}} \end{array} $$
(32)

For b,

$$ {b_{new}} = {b_{old}} + {\delta_{b}}\left( {\ln {D^{est}} - \ln {D^{act}}} \right)\ln r $$
(33)

where δb is the update step of b.

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Li, F., Wang, T. & Cosman, P.C. Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems. Multimed Tools Appl 78, 26807–26831 (2019). https://doi.org/10.1007/s11042-019-07868-8

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Keywords

  • Video communication
  • Wireless resource allocation
  • Encoding rate adaptation
  • Video packet scheduling
  • OFDMA