Optimisation Of indoor LTE devices

Introduction:
The conventional techniques used to simulate wireless access points take a long time, increasing significantly as the frequency of interest increases, with a trade-off between accuracy and computation time. A technique for speeding up this calculation and improving the performance of domestic small cells has the potential for high impact on the telecommunications industry. It is highly desirable to be able to model coverage both inside and outside of buildings from small cells that are inside. It is also desirable to have a dynamic channel model, i.e., one that takes channel variation into account, caused by movement of people, terminals etc. within the building. This project will develop an effective method for simulating next-generation systems (e.g. LTE and 5G) and their performance in a cluttered domestic environment and for this to be fast enough to allow for optimisation of the location of the LTE transmitters.

Workplan:
The project will be to design fast methods to optimise the location of LTE FemtoCell transmitters, antennas and reflectors in a cluttered domestic environment.


(1a) Develop ray-tracing methods in 3D, for a small number of specific domestic environments with walls and furniture. This will model the likely performance of radio links in terms of coverage and SIR plus noise. Considering both indoor-to-indoor and indoor-to-outdoor paths and comparing with experimental results. A series of calculations will be made for different antennas and realisations of the domestic environments and the effect of different wall materials, furniture types and placements, and the location of people. Consider the effect of interference from neighbours. Determine the signal to interference curves.

(1b) Also to implement 2D PDE models and compare results.

(2a) Develop a stochastic model for the walls, furniture, and people, and replace the large number of realisations by a much smaller number using the stochastic information and carefully designed stochastic numerical methods. These results will be compared both with experiment and with the results of the first part of the project and the stochastic descriptors refined and developed as needed. Movement in the channel will also be considered.

(2b) Compare with empirical analytical models.

(3a) Map results of 1 and 2 to actual performance measures.

(3b) These will be combined with the solution of a partial differential equation Monge-Ampère method to determine the optimal location of the transmitters and possible extra reflectors. Following its formulation the resulting equation will be solved by extending and developing earlier research of the primary supervisor. These results will again be supported by experiment and a limited measurement campaign. Refinements on the link budget and dependency on base-station location will be given. This will provide information on how multi-path rich the link is, which is an important factor in determining how well the system will work.

Using the methods above the aim will be to optimise the location of the LTE femtocells within the domestic environment and to quantify the sensitivity of this optimisation of the effects of wall material, furniture and other clutter. Optimise
(a) spectrum utility (b) energy (c) signal to noise ratio.