Browsing by Author "Wang, Siyi"

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    Energy Efficiency and Spectral Efficiency Trade-off of a Novel Interference Avoidance Approach for LTE-Femtocell Networks
    (IEEE., 2012) Wang, Siyi; Turyagyenda, Charles; O’Farrell, Tim
    The trade-off between energy efficiency and downlink spectral efficiency for LTE-femtocells can be significantly balanced by a novel interference management technique in the presence of the interference from the co-channel outdoor micro-cell and the neighbouring femtocell access points. The simulation results have been demonstrated to be meaningful in the context of considering capacity saturation of realistic modulation and coding schemes rather than theoretical Shannon's equation. The paper shows that the radio-head and operational improvement of up to 12% and 3% can be achieved. Moreover, it has been shown that the improvement does not significantly degrade the user's data rate and the proposed scheme can be implemented in unplanned self- organising networks.
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    Integrated Cross-Layer Energy Savings in a Smart and Flexible Cellular Network
    (IEEE., 2012) Guo, Weisi; Wang, Siyi; Turyagyenda, Charles; O’Farrell, Tim
    A key challenge for mobile operators is how to reduce the operational energy and cost expenditure, whilst meeting the growing demand for throughput. In recent years, individual research techniques have shown that significant savings can be made. The majority of savings are achieved in the signal transmission stage and are obtained under certain modeling conditions and assumptions. How the gains can be combined together to yield higher total operational savings is largely unexplored, especially under a realistic multi-cell multi-user environment. This paper employs an integrated analysis of the cross-layer techniques that reduce energy consumption or improve the spectral- and energy- efficiency tradeoff. The research is part of the key integration process of the MVCE Green Radio (GR) programme, which combines architecture, transmission technique, resource management, and hardware research. The integrated operational energy savings have been shown to be above 90% and the associated cost savings are up to 34%. Furthermore, the paper discusses the impact of machine-learning and energy harvesting on the energy and cost consumption, to create a smart and flexible cellular network.