Improving Energy Efficiency and Minimizing Backhaul Traffic in LTE-A Network with Cooperation and DTX Mechanism
P. Bhuvaneswari1, L. Nithyanandan2
1P. Bhuvaneswari, Department of Electronics and Communication Engineering, Pondicherry Engineering College, (Puducherry), India.
2L. Nithyanandan, Department of Electronics and Communication Engineering, Pondicherry Engineering College, (Puducherry), India.
Manuscript received on 11 October 2019 | Revised Manuscript received on 20 October 2019 | Manuscript Published on 02 November 2019 | PP: 399-405 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10610982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1061.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The promising approach to enhance energy efficiency (EE) in LTE-A network is to switch underutilized evolved node B (eNB) to sleep mode, but it increases the transmission power to guarantee the coverage under the remaining active eNBs. The increase in transmission power can be reduced by coordinated multi-point (CoMP) technique through eNB cooperation, but this technique consumes extra power due to backhaul traffic and signal processing. This problem can be solved by the proposed energy efficient acceleration factor failure rate (EEAFR) algorithm. The algorithm jointly considers the eNB cooperation and DTX mechanism to minimize the backhaul traffic with less failure rate. Also, to enhance energy efficiency, the proposed algorithm efficiently utilizes the cooperation in all traffic load scenarios based on the decision criteria and DTX mechanism. The results are compared with the existing AFEE and Green CoMP with Backhaul Traffic algorithm. In all the traffic loads EEAFR save 59.8% energy and reduces the network outage which depends on the failure rate of the eNB components
Keywords: Backhaul Traffic, Cooperation, DTX, Failure Rate.
Scope of the Article: RF Energy Harvesting