• Tho Le-Ngoc
  • Khoa Tran Phan
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)


The past decade has seen the tremendous growth of wireless communications with the increasing demand for various emerging applications such as video transmissions, mobile entertainment, mobile healthcare etc., which require higher data rate and/or more stringent delay quality-of-service (QoS). Consequently, in the development of next-generation wireless systems, it is a crucial task to provide wireless connections with better QoS such as higher data rate, smaller delay etc. [1, 2]. However, such task is not easy due to many inherent challenges. One challenge is the fact that wireless signal strength randomly fluctuates over time due to varying fading [3]. There are large-scale fading effects, where the received signal strength changes over distance because of the path loss and shadowing, and small-scale fading effects, where the received signal strength changes because of the constructive and destructive interference of multiple reflecting and refracting signal paths. In addition, the available radio resources are limited. Hence, efficient (radio) resource allocation is crucial to combat the fading effects of wireless channels, and providing satisfactory QoS to the users [4].


Fading Channel Power Allocation Energy Harvesting Markov Decision Process Delay Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    M. Agiwal, A. Roy, and N. Saxena, “Next Generation 5G Wireless Networks: A Comprehensive Survey,” Commun. Surveys Tuts., vol. 18, no. 3, pp. 1617–1655, Feb. 2016.Google Scholar
  2. 2.
    J. Andrews, S. Buzzi, W. Choi, S. Hanly, A. Lozano, A. Soong, and J. Zhang, “What Will 5G be?” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, June 2014.Google Scholar
  3. 3.
    A. Goldsmith, Wireless Communications. Cambridge University Press, 2005.Google Scholar
  4. 4.
    Z. Han, An Optimization Theoretical Framework for Resource Allocation over Wireless Networks. PhD thesis, University of Maryland, USA, 2003.Google Scholar
  5. 5.
    M. Andrews, K. Kumaran, K. Ramanan, A. Stolyar, P. Whiting, and R. Vijayakumar, “Providing Quality of Service over a Shared Wireless Link,” IEEE Commun. Mag., vol. 39, no. 2, pp. 150–154, Feb. 2001.Google Scholar
  6. 6.
    J. Chen, Resource Allocation for Delay Constrained Wireless Communications. PhD thesis, University College London, UK, 2010.Google Scholar
  7. 7.
    X. Zhang, W. Cheng, and H. Zhang, “Heterogeneous Statistical QoS Provisioning Over 5G Mobile Wireless Networks,” IEEE Network Magazine, vol. 28, no. 6, pp. 46–53, Nov./Dec. 2014.Google Scholar
  8. 8.
    3rd Generation Partnership Project, Universal Mobile Telecommunications System (UMTS); Quality of Service Concept and Architecture. (3GPP TS 23.107 version 5.4.0 Release 5).Google Scholar
  9. 9.
    B. Collins, and R. Cruz, “Transmission Policies for Time Varying Channels with Average Delay Constraints,” in Proc. 1999 Allerton Conf. on Commun., Control, and Computing, Urbana, IL, USA.Google Scholar
  10. 10.
    X. Zhang, J. Tang, H.-H. Chen, S. Ci, and M. Guizani, “Cross-layer-based Modeling for Quality of Service Guarantees in Mobile Wireless Networks,” IEEE Commun. Mag., vol. 44, no. 1, pp. 100–106, Jan. 2006.Google Scholar
  11. 11.
    S. Meninger, J. O. Mur-Miranda, R. Amirtharajah, A. Chandrakasan, and J. H. Lang, “Vibration-to-Electric Energy Conversion,” IEEE Trans. on VLSI, vol. 9, no. 1, pp. 64–76, Feb. 2001.Google Scholar
  12. 12.
    V. Raghunathan, A. Kansal, J. Hsu, J. Friedman, and M. B. Srivastava, “Design Considerations for Solar Energy Harvesting Wireless Embedded Systems,” in Proc. 2005 IEEE IPSN, Los Angeles, CA, USA.Google Scholar
  13. 13.
    S. Chalasani, and J. M. Conrad, “A Survey of Energy Harvesting Sources for Embedded Systems,” in Proc. 2008 IEEE Southeastcon, Huntsville, AL, USA.Google Scholar
  14. 14.
    M. Gorlatova, P. Kinget, I. Kymissis, D. Rubenstein, X. Wang, and G. Zussman, “Challenge: Ultra-low-power Energy-harvesting Active Networked Tags (EnHANTs), ” in Proc. 2009 ACM Mobicom, Beijing, China.Google Scholar
  15. 15.
    H. Li, C. Huang, F. Alsaadi, A. M. Dobaie, and S. Cui, “Energy Harvesting based Green Heterogeneous Wireless Access for 5G,” in 5G Mobile Communications, Ed., Springer, 2016, pp. 475–502.Google Scholar
  16. 16.
    D. Mishra, and S. De, “Energy Harvesting and Sustainable M2M Communication in 5G Mobile Technologies,” in Internet of Things (IoT) in 5G Mobile Technologies, Ed., Springer, 2016, pp 99–125.Google Scholar
  17. 17.
    H. Shafieirad, R. S. Adve, and S. ShahbazPanahi, “Large Scale Energy Harvesting Sensor Networks with Applications in Smart Cities,” in Smart City 360, Ed., Springer, 2016, pp. 215–226.Google Scholar
  18. 18.
    T. R. Halford, and K. M. Chugg, “Barrage Relay Networks,” in Proc. 2010 IEEE ITA, San Diego, CA, USA.Google Scholar
  19. 19.
    D. Gunduz, K. Stamatiou, N. Michelusi, and M. Zorzi, “Designing Intelligent Energy Harvesting Communication Systems,” IEEE Commun. Mag., vol. 52, no. 1, pp. 210–216, Jan. 2014.Google Scholar
  20. 20.
    I. Ahmeda, M. M. Butta, C. Psomasb, A. Mohamed, I. Krikidisb, and M. Guizania, “Survey on Energy Harvesting Wireless Communications: Challenges and Opportunities for Radio Resource Allocation,” Computer Networks, vol. 88, no. 9, pp. 234–248, Sept. 2015.Google Scholar
  21. 21.
    S. Ulukus, A. Yener, E. Erkip, O. Simeone, M. Zorzi, P. Grover, and K. Huang. “Energy Harvesting Wireless Communications: A Review of Recent Advances,” IEEE J. Sel. Areas Commun., vol. 33, no. 5, pp. 360–381, Mar. 2015.Google Scholar
  22. 22.
    Y. Cui, V. Lau, R. Wang, and H. Huang, “A Survey on Delay-aware Resource Control for Wireless Systems - Large Derivation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning,” IEEE Trans. Infor. Theory, vol. 58, no. 3, pp. 1677–1701, March 2012.Google Scholar
  23. 23.
    R. Berry, and R. Gallager, “Communication over Fading Channels with Delay Constraints,” IEEE Trans. Infor. Theory, vol. 48, no. 5, pp. 1135–1149, May 2002.Google Scholar
  24. 24.
    D. S. W. Hui, V. K. N. Lau, and H. L. Wong, “Cross-layer Design for OFDMA Wireless Systems with Heterogeneous Delay Requirements,” IEEE Trans. Wireless Commun., vol. 6, no. 8, pp. 2872–2880, Aug. 2007.Google Scholar
  25. 25.
    M. J. Neely, “Energy Optimal Control for Time Varying Wireless Networks,” IEEE Trans. Infor. Theory, vol. 52, no. 7, pp. 2915–2934, July 2006.Google Scholar
  26. 26.
    N. Salodkar, A. Bhorkar, A. Karandikar, and V. S. Borkar, “On-Line Learning Algorithm for Energy Efficient Delay Constrained Scheduling over Fading Channel,” IEEE J. Sel. Areas Commun., vol. 26, no. 4, pp. 732–742, May 2008.Google Scholar
  27. 27.
    F. Fu, and M. van der Schaar, “Structure-Aware Stochastic Control for Transmission Scheduling,” IEEE Trans. Veh. Tech., vol. 61, no. 9, pp. 3931–3945, Nov. 2012.Google Scholar
  28. 28.
    A. Abdrabou and W. Zhuang, “Stochastic Delay Guarantees and Statistical Call Admission Control for IEEE 802.11 Single-hop Ad hoc Networks,” IEEE Trans. Wireless Commun., vol. 7, no. 10, pp. 3972–3981, Oct. 2008.Google Scholar
  29. 29.
    M. Zafer, and E. Modiano, “Minimum Energy Transmission over a Wireless Channel with Deadline and Power Constraints,” IEEE Trans. Auto. Control, vol. 54, no. 12, pp. 2841–2852, Dec. 2009.Google Scholar
  30. 30.
    W. Chen, M. J. Neely, and U. Mitra, “Energy-efficient Transmissions with Individual Packet Delay Constraints,” IEEE Trans. Inf. Theory, vol. 54, no. 5, pp. 2090–2109, May 2008.Google Scholar
  31. 31.
    V. Hanly, and D. Tse, “Multiaccess Fading Channels. Part II: Delay-limited Capacities,”IEEE Trans. Inf. Theory, vol. 44, no. 7, pp. 2816–2831, Nov. 1998.Google Scholar
  32. 32.
    C.-S Chang, “Stability, Queue Length, and Delay of Deterministic and Stochastic Queuing Networks,” IEEE Trans. Auto. Control, vol. 39, no. 5, pp. 913–931, May 1994.Google Scholar
  33. 33.
    D. Wu, and R. Negi, “Effective Capacity: A Wireless Link Model for Support of Quality of Service,” IEEE Trans. Wireless Commun., vol. 2, no. 4, pp. 630–643, Jul. 2003.Google Scholar
  34. 34.
    D. Wu, Providing Quality-of-Service Guarantees in Wireless Networks. PhD thesis, Carnegie Mellon University, USA, 2003.Google Scholar
  35. 35.
    X. Zhang, and Q. Du, “Cross-Layer Modeling for QoS-Driven Multimedia Multicast/Broadcast Over Fading Channels in Mobile Wireless Networks,” IEEE Commun. Mag., vol. 45, no. 8, pp. 62–70, Aug. 2007.Google Scholar
  36. 36.
    E. Altman, Constrained Markov Decision Processes: Stochastic Modeling. London, UK.: Chapman & Hall CRC, 1999.Google Scholar
  37. 37.
    P. Blasco, D. Gunduz, and M. Dohler, “A Learning Theoretic Approach to Energy Harvesting Communication System Optimization,” IEEE Trans. Wireless Commun., vol. 12, no. 4, pp. 1872–1882, Apr. 2013.Google Scholar
  38. 38.
    O. Ozel, K. Tutuncuoglu, J. Yang, S. Ulukus, and A. Yener, “Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies,” IEEE J. Sel. Areas Commun., vol. 29, no. 8, pp. 1732–1743, Sept. 2011.Google Scholar
  39. 39.
    C. K. Ho, and R. Zhang, “Optimal Energy Allocation for Wireless Communications with Energy Harvesting Constraints,” IEEE Trans. Signal Process., vol. 60, no. 9, pp. 4808–4818, Sept. 2012.Google Scholar
  40. 40.
    D. P. Bertsekas. Dynamic Programming and Optimal Control Vol. 1. Belmont, MA: Athens Scientific, 1995.Google Scholar
  41. 41.
    R. S. Sutton, and A. G. Barto, Reinforcement Learning: An Introduction. The MIT Press, 1998.Google Scholar
  42. 42.
    V. S. Borkar, Stochastic Approximation: A Dynamical Systems Viewpoint. Cambridge University Press, 2008.Google Scholar
  43. 43.
    B. Xia, Y. Fan, J. Thompson, and H. V. Poor, “Buffering in a Three-node Relay Network,” IEEE Trans. Wireless Commun., vol. 7, no. 11, pp. 4492–4496, Nov. 2008.Google Scholar
  44. 44.
    I. Krikidis, T. Charalambous, and J. Thompson, “Buffer-aided Relay Selection for Cooperative Diversity Systems without Delay Constraints,” IEEE Trans. Wireless Commun., vol. 11, no. 5, pp. 1957–1967, 2012.CrossRefGoogle Scholar
  45. 45.
    N. Zlatanov, A. Ikhlef, T. Islam, and R. Schober, “Buffer-aided Cooperative Communications: Opportunities and Challenges,” IEEE Commun. Magazine, vol. 52, no. 4, pp. 146–153, April 2014.Google Scholar
  46. 46.
    N. Zlatanov, R. Schober, and P. Popovski, “Buffer-aided Relaying with Adaptive Link Selection,” IEEE J. Sel. Areas Commun., vol. 31, no. 8, pp. 1530–1542, Aug. 2013.Google Scholar
  47. 47.
    N. Zlatanov, and R. Schober, “Buffer-aided Relaying With Adaptive Link Selection - Fixed and Mixed Rate Transmission,” IEEE Trans. on Inform. Theory, vol. 59, no. 5, pp. 2816–2840, Jan. 2013.Google Scholar
  48. 48.
    M. Jain, J. I. Choi, T. M. Kim, D. Bharadia, S. Seth, K. Srinivasan, P. Levis, S. Katti, and P. Sinha, “Practical, Real-time, Full-Duplexing Wireless,” in Proc. 2011 ACM Mobicom, Las Vegas, NV, USA.Google Scholar
  49. 49.
    M. Duarte, C. Dick, and A. Sabharwal, “Experiment-driven Characterization of Full-duplex Wireless Systems,” IEEE Trans. Wireless Commun., vol. 11, no. 12, pp. 4296–4307, Dec. 2012.Google Scholar
  50. 50.
    D. Bharadia, E. McMilin, and S. Katti, “Full-Duplex Radios,” in SIGCOMM Comput. Commun. Rev., vol. 43, no. 4, pp. 375–386, Aug. 2013.Google Scholar
  51. 51.
    T. Riihonen, S. Werner, and R. Wichman, “Comparison of Full-duplex and Half-duplex Modes with a Fixed Amplify-and-Forward Relay,” in Proc. 2009 IEEE WCNC, Budapest, Hungary.Google Scholar
  52. 52.
    T. Riihonen, S. Werner, and R. Wichman, “Hybrid Full-duplex/Half-duplex Relaying with Transmit Power Adaptation,” IEEE Trans. Wireless Commun., vol. 10, no. 9, pp. 3074–3085, Sept. 2011.Google Scholar
  53. 53.
    H. Q. Ngo, H. A. Suraweera, M. Matthaiou, and E. G. Larsson, “Multipair Full-duplex Relaying with Massive Arrays and Linear Processing,” IEEE J. Sel. Areas Commun., vol. 32, no. 9, pp. 1721–1737, June 2014.Google Scholar
  54. 54.
    L. J. Rodriguez, N. H. Tran, and T. Le-Ngoc, “Optimal Power Allocation and Capacity of Full-Duplex AF Relaying under Residual Self-Interference,” IEEE Wireless Commun. Letters, vol. 3, no. 2, pp. 233–236, Apr. 2014.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Tho Le-Ngoc
    • 1
  • Khoa Tran Phan
    • 2
  1. 1.Department of Electrical and Computer EngineeringMcGill UniversityMontrealCanada
  2. 2.Department of Electrical and Computer Systems EngineeringMonash UniversityClaytonAustralia

Personalised recommendations