The growth in mobile network traffic due to the increase in MTC (Machine Type Communication)
applications, brings along a series of new challenges in traffic routing and
management. The goals are to have effective resolution times (less delay), low energy
consuption (given that wide sensor networks which are included in the MTC category, are
built to last years with respect to their battery consuption) and extremely reliable communication
(low Packet Error Rates), following the fifth generation (5G) mobile network
demands.
In order to deal with this type of dense traffic, several uplink strategies can be devised,
where diversity variables like space (several Base Stations deployed), time (number of
retransmissions of a given packet per user) and power spreading (power value diversity
at the receiver, introducing the concept of SIC and Power-NOMA) have to be handled
carefully to fulfill the requirements demanded in Ultra-Reliable Low-Latency Communication
(URLLC).
This thesis, besides being restricted in terms of transmission power and processing of a
User Equipment (UE), works on top of an Iterative Block Decision Feedback Equalization
Reciever that allows Multi Packet Reception to deal with the diversity types mentioned
earlier. The results of this thesis explore the possibility of fragmenting the processing
capabilities in an integrated cloud network (C-RAN) environment through an SINR estimation
at the receiver to better understand how and where we can break and distribute
our processing needs in order to handle near Base Station users and cell-edge users, the
latters being the hardest to deal with in dense networks like the ones deployed in a MTC
environment
