This research will look at ways to carry our radio propagation studies inside working factories quickly and accurately. Many things now need to be connected but in 5G we need links to be low latency and highly reliable. Controlling machines using radio is tricky in factories because there is a great deal of interference so it's important to carry out proper measurements so that radio coverage can be planned. However, factories are rarely quiet and getting access for time consuming propagation studies may be difficult. This research will look at ways to speed up radio surveys using software defined radio and augment them new fractal algorithms. This work will open career pathways in industries such as automotive, aerospace and defence.
Building on existing research carried out at Loughborough related to radio propagation, this work will look at the problem of radio planning for fully connected machines. Initially, you will research 5G in industrial environments and begin to understand how waves propagate within modern workspaces. The frequencies can be much higher for 5G than for other technologies giving some advantages as well as bringing many challenges. You will look in particular at the two requirements of low latency and ultra-reliable communications. What is it about a factory that might stop us realising 99% connectivity and what can be done to make machines react quickly to remote commands. Using software defined radio, you will carry out measurement campaigns inside one or more of the University’s workshops and then begin to look at the workspaces of other modern companies.
In the second stage of your PhD, you will refine your measurement techniques to allow you to simulate factory environments that you have not actually visited. For example, what key information do you need to simulate a factory, new or old, in a way that is accurate enough to decide on what radio technology is suitable for AI machine control. This may involve fractals or 3D scanning/Lidar.
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