Lifetime maximization via joint channel and power assignment for incremental-relay multi-channel systems


A comprehensive resource optimization framework is designed for incremental amplify-and-forward orthogonal frequency division multiplexing (AF-OFDM) relaying systems to maximize the network lifetime. Specifically, joint channel and power assignment, i.e., all degrees of freedom such as incremental policy, channel pairing, relay selection, and power allocation, are optimized with quality of service (QoS) constraints. The lifetime maximization problem is formulated as a mixed-integer nonlinear programming which at first glance seems mathematically intractable. However, a two-nested search loop, in which the outer loop varies the lifetime based on bisection criterion until finding the optimum while the inner loop attempts to derive the corresponding feasible solution set for that given lifetime by employing dual decomposition and subgradient techniques, is then presented to solve it. Numerical results are shown to verify the near-optimality and the effectiveness of our proposal.

This is a preview of subscription content, access via your institution.


  1. 1

    Nosratinia A, Hunter T E, Hedayat A. Cooperative communication in wireless networks. IEEE Commun Mag, 2004, 42: 74–80

    Article  Google Scholar 

  2. 2

    Laneman J N, Tse D N C, Wornell G W. Cooperative diversity in wireless networks: efficient protocols and outage behavior. IEEE Trans Inf Theory, 2004, 50: 3062–3080

    MathSciNet  Article  Google Scholar 

  3. 3

    Silva B M C, Rodrigues J J P C, Kumar N, et al. Cooperative strategies for challenged networks and applications: a survey. IEEE Syst J, 2017, 11: 2749–2760

    Article  Google Scholar 

  4. 4

    Andrews J G, Buzzi S, Choi W, et al. What will 5G be? IEEE J Sel Areas Commun, 2014, 32: 1065–1082

    Article  Google Scholar 

  5. 5

    Zhang S Q, Wu Q Q, Xu S G, et al. Fundamental green tradeoffs: progresses, challenges, and impacts on 5G networks. IEEE Commun Surv Tut, 2017, 19: 33–56

    Article  Google Scholar 

  6. 6

    Al-Tous H, Barhumi I. Resource allocation for multiple-sources single-relay cooperative communication OFDMA systems. IEEE Trans Mobile Comput, 2016, 15: 964–981

    Article  Google Scholar 

  7. 7

    Zhu Q, Zhou Z K. Joint energy-efficient power allocation and subcarrier pairing in orthogonal frequency division multiple-based multi-relay networks. IET Commun, 2015, 9: 649–657

    Article  Google Scholar 

  8. 8

    Zhang Y, Pang L H, Ren G L, et al. Spectrum and energy efficient relaying algorithms for selective AF-OFDM systems. In: Proceedings of the 83rd Vehicular Technology Conference, Nanjing, 2016

    Google Scholar 

  9. 9

    Li L, Peng M G, Jiang J M, et al. Adaptive radio resource allocation to optimize throughput in multi-cell energy harvesting wireless networks. In: Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), Istanbul, 2014. 3094–3099

    Google Scholar 

  10. 10

    He P, Zhao L, Zhou S, et al. Recursive waterfilling for wireless links with energy harvesting transmitters. IEEE Trans Veh Technol, 2014, 63: 1232–1241

    Article  Google Scholar 

  11. 11

    Wang J, Wang Y M, Feng W, et al. An iterative power allocation scheme for improving energy efficiency in massively dense distributed antenna systems. In: Proceedings of the 83rd Vehicular Technology Conference, Nanjing, 2016

    Google Scholar 

  12. 12

    Akbas A, Yildiz H U, Tavli B, et al. Joint optimization of transmission power level and packet size for WSN lifetime maximization. IEEE Sens J, 2016, 16: 5084–5094

    Article  Google Scholar 

  13. 13

    Li P, Guo S, Cheng Z X. Max-min lifetime optimization for cooperative communications in multi-channel wireless networks. IEEE Trans Parall Distrib Syst, 2014, 25: 1533–1542

    Article  Google Scholar 

  14. 14

    Yu W, Lui R. Dual methods for nonconvex spectrum optimization of multicarrier systems. IEEE Trans Commun, 2006, 54: 1310–1322

    Article  Google Scholar 

  15. 15

    Boyd S, Vandenberghe L. Convex Optimization. Cambridge: Cambridge University Press, 2004

    Book  Google Scholar 

  16. 16

    Garfinkel R, Nemhauser G. Integer Programming. New York: Wiley, 1972

    MATH  Google Scholar 

  17. 17

    Chen B, Lei M, Zhao M J. An optimal resource allocation method for multi-user multi-relay DF cognitive radio networks. IEEE Commun Lett, 2016, 20: 1164–1167

    Article  Google Scholar 

  18. 18

    Ni M J, Xu X, Mathar R. A channel feedback model with robust SINR prediction for LTE systems. In: Proceedings of the 7th European Conference on Antennas and Propagation, Gothenburg, 2013. 1866–1870

    Google Scholar 

  19. 19

    Zhou K X, Zhang L, Jiang M. Enhanced effective SNR prediction for LTE downlink. In: Proceedings of IEEE/CIC International Conference on Communications in China, Shenzhen, 2015

    Google Scholar 

Download references


This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61401321, 61701392, 91538105), Fundamental Research Funds for the Central Universities (Grant No. JB180107), National Basic Research Program of China (Grant No. 2014CB340206), Open Research Fund of National Mobile Communications Research Laboratory (Grant No. 2015D01), Scientific Research Plan Projects of Shaanxi Provincial Department of Education (Grant Nos. 16JK1498, 16JK1501), China Postdoctoral Science Foundation (Grant No. 2015M5826), and Natural Science Foundation of Xi’an University of Science and Technology (Grant No. 2018YQ3-07).

Author information



Corresponding author

Correspondence to Yang Zhang.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pang, L., Zhang, Y., Han, R. et al. Lifetime maximization via joint channel and power assignment for incremental-relay multi-channel systems. Sci. China Inf. Sci. 62, 22301 (2019).

Download citation


  • lifetime maximization
  • incremental relaying
  • amplify-and-forward
  • multi-channel systems
  • resource optimization