Abstract
Providing reliable transmission for real-time traffic in wireless cellular networks is a great challenge due to the unreliable wireless links. This paper concentrates on the resource allocation problem aiming to improve the real-time throughput. First, the resource allocation problem is formulated as a Markov Decision Process and thus the optimal resource allocation policy could be obtained by adopting the value iteration algorithm. Considering the high time complexity of the optimal algorithm, we further propose an approximate algorithm which decomposes the resource allocation problem into two subproblems, namely link scheduling problem and packet scheduling problem. By this method, the unreliable wireless links are only constrained in the link scheduling problem, and we can focus on the real-time requirement of traffic in packet scheduling problem. For the link scheduling problem, we propose the maxRel algorithm to maximize the long-term network reliability, and we theoretically prove that the maxRel algorithm is optimal in scenarios with dynamic link reliabilities. The Least Laxity First algorithm is adopted for the packet scheduling problem. Extensive simulation results show that the proposed approximate resource allocation algorithm makes remarkable improvement in terms of time complexity, packet loss rate and delay.
Similar content being viewed by others
References
Sadi, Y., & ColeriErgen, S. (2015). Energy and delay constrained maximum adaptive schedule for wireless networked control systems. IEEE Transactions on Wireless Communications, 14(7), 3738–3751.
Song, J., Han, S., Mok, A. K., Chen, D., Lucas, M., & Nixon, M. (2008). WirelessHART: Applying Wireless Technology in real-time industrial process control. RTAS, 2008, pp. 377–386.
Yan, M., Lam, K. Y., Han, S., Chan, E., Chen, Q., Fan, P., et al. (2014). Hypergraph-based data link layer scheduling for reliable packet delivery in wireless sensing and control networks with end-to-end delay constraints. Information Sciences, 278, 34–55.
Shakkottai, S., & Srikant, R. (2002). Scheduling real-time traffic with deadlines over a wireless channel. Wireless Networks, 8(1), 13–26.
Li, Y., Zhang, H., Huang, Z., & Albert, M. (2014). Optimal link scheduling for delay-constrained periodic traffic over unreliable wireless links. INFOCOM, 2014, pp. 1465–1473
Hou, I. H., Borkar, V., & Kumar, P. R. (2009). A theory of QoS for wireless. INFOCOM, 2009, pp. 486–494
Nan, F., Yu, F. R., Sun, H., & Li, M. (2016). Adaptive power allocation schemes for spectrum sharing in interference-alignment-based cognitive radio networks. IEEE Transactions on Vehicular Technology, 65(5), 3700–3714.
Jiang, H., Zhou, C., Wu, L., et al. (2015). TDOCP: A two-dimensional optimization integrating channel assignment and power control for large-scale WLANs with dense users. Ad Hoc Networks, 26, 114–127.
Gabale, V., Raman, B., Dutta, P., & Kalyanraman, S. (2013). A classification framework for scheduling algorithms in wireless mesh networks. IEEE Communications Surveys and Tutorials, 15(1), 199–222.
Tassiulas, L., & Ephremides, A. (1992). Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks. IEEE Transactions on Automatic Control, 37(12), 1936–1948.
Hou, I. H., & Kumar, P. R. (2011). A survey of recent results on real-time wireless networking. In Proceedings of the real-time wireless for industrial applications, pp. 1–6.
Hou, I. H., & Kumar, P. R. (2009). Scheduling heterogeneous real-time traffic over fading wireless channels. IEEE/ACM Transactions on Networking, 22(5), 1631–1644.
Puterman, M. L. (1994). Markov decision processes: Discrete stochastic dynamic programming. New Jersey: Wiley.
Abu Alsheikh, M., Hoang, D. T., Niyato, D., Tan, H. P., & Lin, S. (2015). Markov decision processes with applications in wireless sensor networks: A survey. IEEE Communications Surveys and Tutorials, 17(3), 1239–1267.
Willig, A., & Uhlemann, E. (2014). Deadline-aware scheduling of cooperative relayers in TDMA-based wireless industrial networks. Wireless Networks, 20(1), 73–88.
Wang, R., & Lau, V. K. (2013). Delay-aware two-hop cooperative relay communications via approximate MDP and stochastic learning. IEEE Transactions on Information Theory, 59(11), 7645–7670.
Zhou, B., Cui, Y., & Tao, M. (2015). Stochastic throughput optimization for two-hop systems with finite relay buffers. IEEE Transactions on Signal Processing, 63(20), 5546–5560.
Moghadari, M., Hossain, E., & Le, L. B. (2013). Delay-optimal distributed scheduling in multi-user multi-relay cellular wireless networks. IEEE Transactions on Communications, 61(4), 1349–1360.
Niafar, S., Tan, X., & Tsang, D. H. (2016). Optimal downlink scheduling for heterogeneous traffic types in LTE-A based on MDP and chance-constrained approaches. Mobile Networks and Applications, 21(3), 390–401.
Xu, J., Yang, J., Xie, Y., Guo, C., & Yu, Y. (2016). MDP based link scheduling in wireless networks to maximize the reliability. Wireless Networks, 22(5), 1659–1671.
Lei, L., Kuang, Y., Cheng, N., Shen, X., & Lin, C. (2016). Delay-optimal dynamic mode selection and resource allocation in device-to-device communications-Part I: Optimal policy. IEEE Transactions on Vehicular Technology, 65(5), 3474–3490.
Lei, L., Kuang, Y., Cheng, N., Shen, X., & Lin, C. (2015). Delay-optimal dynamic mode selection and resource allocation in device-to-device communications-Part II: Practical algorithm. IEEE Transactions on Vehicular Technology, 65(5), 3491–3505.
Wu, H., Lin, X., Liu, X., Tan, K., & Zhang, Y. (2014). Decomposition of large-scale MDPs for wireless scheduling with load-and channel-awareness. In IEEE information theory and applications workshop, pp. 1–10
Gilbert, E. N. (1960). Capacity of a burst-noise channel. Bell System Technical Journal, 39(5), 1253–1265.
Elliott, E. O. (1963). Estimates of error rates for codes on burst-noise channels. The Bell System Technical Journal, 42(5), 1977–1997.
Hong, S. W., & Moayeri, N. (1995). Finite-state Markov channel-a useful model for radio communication channels. IEEE Transactions on Vehicular Technology, 44(1), 163–171.
Liu, J. W. (2000). Real-time systems. New York: Prentice Hall.
Jain, R., Hawe W., & Chiu D. (1984). A Quantitative measure of fairness and discrimination for resource allocation in Shared Computer Systems. DEC-TR-301, September, 1984.
Acknowledgements
This work is supported by Grant No. 413000016 from Wuhan University.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Xu, J., Guo, C., Zhang, H. et al. Resource allocation for real-time traffic in unreliable wireless cellular networks. Wireless Netw 24, 1405–1418 (2018). https://doi.org/10.1007/s11276-016-1413-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-016-1413-x