The purpose of this research is to develop a mobile network that does not have fixed cellular boundaries. In conventional cellular networks, each user equipment (UE) is connected to the access point (AP) in only one of the many cells (except during handover). At a given time instance, the APs have different numbers of active UEs, causing inter-cell interference. Cellular networks are suboptimal from a channel capacity viewpoint because higher spectral efficiency (SE) (bit/s/Hz/user) can potentially be achieved by co-processing each signal at multiple APs.
In cell-free networks, there are many more geographically distributed APs that can use artificial intelligent techniques to self-organise themselves into Multiple Input Multiple Output (MIMO) groups to jointly serve a relatively smaller number of UEs. Cell-free Massive MIMO can potentially provide ten-fold improvements in Spectral Efficiency for the UEs over a corresponding cellular network with small cells.
The cabling and internal communication between APs is also a challenging issue in practical cell-free Massive MIMO deployments. A cost-efficient architecture is one that self-organise APs as both access points as well as nodes in a front haul network that reduces the requirement for cabling between Aps.
The majority of the project will be carried out using MATLAB, crafting different sections of code to explore different algorithmic options and the Python to incorporate solution on 5G Multiaccess Edge Computing cloud.
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