Energy- and Spectral-Efficient Wireless Cellular Networks

  • Mustafa Ismael Salman
  • Chee Kyun Ng
  • Nor Kamariah Noordin
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 51)


The limited spectrum resources and the negative impacts of carbon dioxide emission resulted from inefficient use of wireless technologies have led to the development of green radio. Both the energy and spectral efficiencies should be considered together to meet green radio requirements. In this paper, we investigate the trade-off between energy efficiency and spectral efficiency through different approaches. Cognitive radio is a paradigm-shift technology which is used to increase both the energy and spectral efficiencies. Some efficient spectrum sensing techniques are considered in terms of energy and time consuming. Furthermore, it can be shown that the power control strategies can play a key role in avoiding interference between cognitive and primary users, and hence it can also enhance both the energy and spectral efficiencies. In addition to cognitive radio, a new infrastructure for deploying the cellular base stations which is a heterogeneous infrastructure of macro-, pico-, and femto-cells is proposed to overcome the energy and bandwidth constraints. Further details related to hardware-constraints in a green base station have also been covered.


Green radio energy efficiency spectral efficiency cognitive radio spectrum sensing transmit power control heterogeneous networks 


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  1. 1.
    CO2 Now | CO2 Home,
  2. 2.
    Sistek, H.: Green-tech base stations cut diesel usage by 80 percent. Green Tech - CNET News,
  3. 3.
    Amanna, A.: Green Communications. Annotated Literature Review and Research Vision (2010)Google Scholar
  4. 4.
    Vo, Q.D., Choi, J.-P., Chang, H.M., Lee, W.C.: Green perspective cognitive radio-based M2M communications for smart meters. In: IEEE International Conference on Information and Communication Technology Convergence (ICTC), pp. 382–383. IEEE Press, Jeju (2010)Google Scholar
  5. 5.
    Miao, G., Himayat, N., Li, Y., Swami, A.: Cross-layer optimization for energy-efficient wireless communications: a survey. Wireless Communications and Mobile Computing 9(4), 529–542 (2009)CrossRefGoogle Scholar
  6. 6.
    Guowang, M., Himayat, N., Li, G.Y., Koc, A.T., Talwar, S.: Interference-Aware Energy-Efficient Power Optimization. In: IEEE International Conference on Communications, ICC 2009, pp. 1–5. IEEE Press, Dresden (2009)CrossRefGoogle Scholar
  7. 7.
    Marsan, M.A., Chiaraviglio, L., Ciullo, D., Meo, M.: Optimal Energy Savings in Cellular Access Networks. In: IEEE International Conference of the Communications Workshops, ICC Workshops, pp. 1–5. IEEE Press, Dresden (2009)Google Scholar
  8. 8.
    Chiaraviglio, L., Ciullo, D., Meo, M., Marsan, M.A.: Energy-efficient management of UMTS access networks. In: 21st IEEE International Conference on Teletraffic Congress, ITC 21, pp. 1–8. IEEE Press, Paris (2009)Google Scholar
  9. 9.
    Marsan, M.A., Meo, M.: Energy Efficient Management of Two Cellular Access Networks. SIGMETRICS Perform. Eval. Rev. 37(4), 69–73 (2010)CrossRefGoogle Scholar
  10. 10.
    Shuguang, C., Goldsmith, A.J., Bahai, A.: Energy-efficiency of MIMO and Cooperative MIMO Techniques in Sensor Networks. IEEE Journal on Selected Areas in Communications 22(6), 1089–1098 (2004)CrossRefGoogle Scholar
  11. 11.
    Wenyu, L., Xiaohua, L., Mo, C.: Energy efficiency of MIMO transmissions in wireless sensor networks with diversity and multiplexing gains. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005), pp. 897–900. IEEE Press (2005)Google Scholar
  12. 12.
    An, H., Srikanteswara, S., Reed, J.H., Xuetao, C., Tranter, W.H., Kyung Kyoon, B., Sajadieh, M.: Minimizing Energy Consumption Using Cognitive Radio. In: IEEE International Conference on Performance, Computing and Communications Conference, IPCCC, pp. 372–377. IEEE Press, AustinGoogle Scholar
  13. 13.
    Palicot, J.: Cognitive radio: an enabling technology for the green radio communications concept. In: International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly. ACM, Leipzig (2009)Google Scholar
  14. 14.
    Grace, D., Jingxin, C., Tao, J., Mitchell, P.D.: Using Cognitive Radio to Deliver Green Communications. In: IEEE 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, pp. 1–6. IEEE Press, Hannover (2009)Google Scholar
  15. 15.
    Akyildiz, I.F., Lee, W.-Y., Vuran, M.C., Mohanty, S.: NeXt Generation/dynamic Spectrum Access/cognitive Radio Wireless Networks: A Survey. Computer Networks 50(13), 2127–2159 (2006)CrossRefMATHGoogle Scholar
  16. 16.
    Shellhammer, S.J.: Spectrum Sensing in IEEE 802.22. IAPR Wksp. Cognitive Info. Processing (2008)Google Scholar
  17. 17.
    Ying-Chang, L., Yonghong, Z., Peh, E.C.Y., Anh Tuan, H.: Sensing-Throughput Tradeoff for Cognitive Radio Networks. IEEE Transactions on Wireless Communications 7(4), 1326–1337 (2008)CrossRefGoogle Scholar
  18. 18.
    Su, H., Zhang, X.: Power-Efficient Periodic Spectrum Sensing for Cognitive MAC in Dynamic Spectrum Access Networks. In: IEEE Conference on Wireless Communications and Networking (WCNC), pp. 1–6. IEEE Press, Sydney (2010)Google Scholar
  19. 19.
    Jin, W., Xi, Z.: Energy-Efficient Distributed Spectrum Sensing for Wireless Cognitive Radio Networks. In: INFOCOM IEEE Conference on Computer Communications Workshops, pp. 1–6. IEEE Press (2010)Google Scholar
  20. 20.
    Liu, Y., Xie, S., Zhang, Y., Yu, R., Leung, V.: Energy-Efficient Spectrum Discovery for Cognitive Radio Green Networks. Mobile Networks and Applications, 1–11 (2011)Google Scholar
  21. 21.
    Budiarjo, I., Lakshmanan, M., Nikookar, H.: Cognitive Radio Dynamic Access Techniques. Wireless Personal Communications 45(3), 293–324 (2008)CrossRefGoogle Scholar
  22. 22.
    Weiss, T.A., Jondral, F.K.: Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency. IEEE Communications Magazine 42(3), 8–14 (2004)CrossRefGoogle Scholar
  23. 23.
    Rui, Z.: Optimal Power Control over Fading Cognitive Radio Channel by Exploiting Primary User CSI. In: IEEE Global Telecommunications Conference, IEEE GLOBECOM, pp. 1–5. IEEE Press, New Orleans (2008)Google Scholar
  24. 24.
    Musavian, L., Aissa, S.: Ergodic and Outage Capacities of Spectrum-Sharing Systems in Fading Channels. In: IEEE Global Telecommunications Conference, GLOBECOM 2007, pp. 3327–3331. IEEE Press (2007)Google Scholar
  25. 25.
    Tripathi, P.S.M., Cianca, E., di Sanctis, M., Ruggieri, M., Prasad, R.: Truncated Power Control Over Cognitive Redo Networks: Trade-off Capacity/Energy Efficiency. In: 13th International Symposium on Wireless Personal Multimedia Communications (WPMC), Recife, Brazil (2010)Google Scholar
  26. 26.
    Khandekar, A., Bhushan, N., Ji, T., Vanghi, V.: LTE-Advanced: Heterogeneous networks. In: IEEE European Wireless Conference (EW), pp. 978–982. IEEE Press (2007, 2010)Google Scholar
  27. 27.
    Ying, H., Laurenson, D.I.: Energy Efficiency of High QoS Heterogeneous Wireless Communication Network. In: IEEE Conference on Vehicular Technology Conference Fall (VTC 2010-Fall), pp. 1–5. IEEE Press, Ottawa (2010)Google Scholar
  28. 28.
    Claussen, H., Ho, L.T.W., Pivit, F.: Effects of Joint Macrocell and Residential Picocell Deployment on the Network Energy Efficiency. In: IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1–6. IEEE Press, Cannes (2008)CrossRefGoogle Scholar
  29. 29.
    Badic, B., O’Farrrell, T., Loskot, P., He, J.: Energy Efficient Radio Access Architectures for Green Radio: Large versus Small Cell Size Deployment. In: IEEE Conference on Vehicular Technology Conference Fall, pp. 1–5. IEEE Press, Anchorage (2009)Google Scholar
  30. 30.
    Wei, W., Gang, S.: Energy Efficiency of Heterogeneous Cellular Network. In: IEEE Conference on Vehicular Technology Conference Fall, pp. 1–5. IEEE, Ottawa (2010)Google Scholar
  31. 31.
    Haratcherev, I., Fiorito, M., Balageas, C.: Low-Power Sleep Mode and Out-Of-Band Wake-Up for Indoor Access Points. In: IEEE GLOBECOM Workshops. IEEE (2009)Google Scholar
  32. 32.
    Wang, X., Vasilakos, A.V., Chen, M., Liu, Y., Kwon, T.T.: A Survey of Green Mobile Networks: Opportunities and Challenges. Mobile Networks and Applications, 1–17 (2011)Google Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • Mustafa Ismael Salman
    • 1
  • Chee Kyun Ng
    • 1
  • Nor Kamariah Noordin
    • 1
  1. 1.Department of Computer and Communication Systems Engineering, Faculty of EngineeringUniversity Putra Malaysia, UPM SerdangMalaysia

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