THESIS: Cost efficient 5G heterogeneous base station deployment using meta-heuristicsLed design and development a 5G system model for simulating 5G radio access network use-cases, using data structures (like graphs, matrices, sets), MATLAB software and geo-spatial industry Data; used to support network design analysis; Translated to code base to OO PythonFormulated the 5G network design problem as a combinatorial multi-objective optimisation problem using Mixed Integer Linear programming (MILP).Researched, developed and tested meta-heuristics and dedicated heuristic algorithms using Python, Java, MATLAB and CPLEX solver;Proposed and developed a novel network-wide strategy and framework based on the application of intelligent meta-heuristics search optimisation for cost-efficient design of 5G mobile networks that reduced network power consumption by 34%; Published my novel technique in the IET networks Journal.Applied the above strategies to provide insights into tackling the problem of cost-efficient design of 5G mobile network from different deployment scenarios;Analysed cost and energy efficiency deployment strategies for cost efficient design of 5G mobile networks from both technical and economic perspectives;Analysed the potential of exploiting renewable energy sources in the design of green 5G mobile networks from both technical and economic perspectives;Visualized data using Tableau software and presented advisory reports on findings to industrial and academic stakeholders as well as presenting at international conferences to both technical and non-technical audiences with excellent feedback; Managed Communication between the industry and academic stakeholders, ensuring that research objectives were aligned with industry partner objectives;Led progress and advisory meetings with industry and academic stakeholders, communicating very complex use cases to a non-technical senior audience