Abstract
The growing demands for wireless communication services pose new challenges in the coming generation of cellular networks design. In Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) networks, ever-higher data rate and energy efficiency (EE) are required to meet the increasing demands in cellular traffic. High data rates can be achieved, however, it requires high level of energy consumption which needs to be controlled especially in this era of green communication trends. The energy consumption of cellular networks worldwide has become a major obstacle to the continued future development of mobile data services, considering that the number of mobile phone users worldwide has already surpassed 4 billion and as the near exponential increase of data traffic carried over mobile networks continues, mobile network operators are faced with rapidly increasing energy costs and regulatory pressures to reduce their carbon footprint to operate more “green” networks. Hence, efficient solutions are necessary to optimize EE and at the same time achieve high data rates to meet green LTE requirements. This thesis proposed an efficient algorithm, namely, the Quality of Service (QoS) and Energy Efficient Aware (QEEA). The goal of QEEA is to achieve maximum throughput and improve the EE by using low transmitted power (43 dBm) which is the lowest power setting according to the 3GPP LTE specifications. This algorithm considers the head of line (HOL) delay, achievable throughput, past average throughput and transmitted power…
Metadata
Item Type: | Book Section |
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Creators: | Creators Email / ID Num. Mohd Yusoff, Nurulanis UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Algorithms |
Divisions: | Universiti Teknologi MARA, Shah Alam > Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS) |
Series Name: | IGS Biannual Publication |
Volume: | 18 |
Number: | 18 |
Keywords: | Abstract; Abstract of thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM; long term evolution network ; LTE |
Date: | 2018 |
URI: | https://ir.uitm.edu.my/id/eprint/20542 |
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