Efficient energy management in ultra-dense wireless networks

The increase in demand for more network capacity has led to the evolution of wireless networks from being largely Heterogeneous (Het-Nets) to the now existing Ultra-dense (UDNs). In UDNs, small cells are densely deployed with the goal of shortening the physical distance between the base stations (BSs) and the UEs, so as to support more user equipment (UEs) at peak times while ensuring high data rates. Compared to Het-Nets, Ultra-dense networks (UDNs) have many advantages. These include, more network capacity, higher flexibility to routine configurations, and more suitability to achieve load-balancing, hence, fewer blind spots as well as lower call blocking probability. It should be noted that, in practice, due to the high density of deployed small cells in Ultra-Dense Networks, a number of issues, or rather concerns, come with this evolution from Het-Nets. Among these issues include problems with efficient radio resource management, user cell association, inter- and intra-cell interference management and, last but not least, efficient energy consumption. Some of these issues which impact the overall network efficiency are largely due to the use of obsolete algorithms, especially those whose resource allocation is based solely on received signal power (RSSP). In this paper, the focus is solely on the efficient energy management dilemma and how to optimally reduce the overall network energy consumption. Through an extensive literature review, a detailed report into the growing concern of efficient energy management in UDNs is provided in Chapter 2. The literature review report highlights the classification as well as the evolution of some of the Mobile Wireless Technologies and Mobile Wireless Networks in general. The literature review report provides reasons as to why the energy consumption issue has become a very serious concern in UltraDense networks as well as the various techniques and measures taken to mitigate this. It is shown that, due to the increasing Mobile Wireless Systems’ carbon footprint which carries serious negative environmental impact, and the general need to lower operating costs by the network operators, the management of energy consumption increases in priority. By using the architecture of a Fourth Generation Long Term Evolution (4G-LTE) UltraDense Network, the report further shows that more than 65% of the overall energy consumption is by the access network and base stations in particular. This phenomenon explains why most attention in energy efficiency management in UDNs is largely centred on reducing the energy consumption of the deployed base stations more than any other network components like the data servers or backhauling features used. Furthermore, the report also provides detailed information on the methods/techniques, their classification, implementation, as well as a critical analysis of the said implementations in literature. This study proposes a sub-optimal algorithm and Distributed Cell Resource Allocation with a Base Station On/Off scheme that aims at reducing the overall base station power consumption in UDNs, while ensuring that the overall Quality of Service (QoS) for each User Equipment (UE) as specified in its service class is met. The modeling of the system model used and hence formulation of the Network Energy Efficiency (NEE) optimization problem is done viii using stochastic geometry. The network model comprises both evolved Node B (eNB) type macro and small cells operating on different frequency bands as well as taking into account factors that impact NEE such as UE mobility, UE spatial distribution and small cells spatial distribution. The channel model takes into account signal interference from all base stations, path loss, fading, log normal shadowing, modulation and coding schemes used on each UE’s communication channels when computing throughout. The power consumption model used takes into account both static (site cooling, circuit power) and active (transmission or load based) base station power consumption. The formulation of the NEE optimization problem takes into consideration the user’s Quality-of-service (QoS), inter-cell interference, as well as each user’s spectral efficiency and coverage/success probability. The formulated NEE optimization problem is of type Nondeterministic Polynomial time (NP)-hard, due to the user-cell association. The proposed solution to the formulated optimization problem makes use of constraint relaxation to transform the NP-hard problem into a more solvable, convex and linear optimization one. This, combined with Lagrangian dual decomposition, is used to create a distributed solution. After cellassociation and resource allocation phases, the proposed solution in order to further reduce power consumption performs Cell On/Off. Then, by using the computer simulation tools/environments, the “Distributed Resource Allocation with Cell On/Off” scheme’s performance, in comparison to four other resource allocation schemes, is analysed and evaluated given a number of different network scenarios. Finally, the statistical and mathematical results generated through the simulations indicate that the proposed scheme is the closest in NEE performance to the Exhaustive Search algorithm, and hence superior to the other sub-optimal algorithms it is compared to

Developing a tool to assess the integration of sustainability into banks: A case study on a bank in Egypt

Banks have an important role to play in the global transition to a more sustainable planet. Not only are they a powerful agent through their control of the money supply, the projects they finance, and clients they lend, but they also have financial, reputational, and legal motivations to adopt more sustainable practices. Based on the importance of banks as sustainability agents and their motivation to become more sustainable, this study focuses on the sustainability integration process in the banking sector and proposes a measurement for this integration. More specifically, this study has three objectives: To create a diagnostic tool or model that can assess the extent to which a bank has integrated sustainability, to pilot the tool on a sample bank that has attempted to integrate sustainability in Egypt, and to refine the tool based on the pilot conducted in the second objective. The tool has been developed to probe for a set of standards that a bank is suggested to follow to integrate sustainability. The standards were developed from the review of literature which suggested following division for the standards: vision and strategy, core business, culture and leadership, communication, and internal environment. Once the tool was developed and piloted on the Arab African International Bank in Egypt, it was found that the bank was 38.16% sustainable. However, the pilot experience revealed many refinements that should be made to the tool. After these refinements were taken into consideration, the updated, and fairer, score for the bank was found to be 43.64%. The plans and strategies of the bank, which in the bank\u27s case, covered the next three years, were also accounted for in a separate tool, post-refinement, and revealed a score of 54.51%. This means that if the bank were to follow through the strategy it expressed over the next three years, it can become 54.51% sustainable, up from 43.64%. There are charts that complement every score which reveal precisely the breakdown of each score. The purpose of this study is not to suggest a tool as an end product, rather it is to suggest it as a starting point for future studies and practitioners, such as banks and consultants, to build on and adjust. The refinement process undertaken study is also a method this study aims to propose. The details of the tool may vary, but there is at least a skeleton and an approach that has resulted from this study on which future research can rely