Network Interference Cancelation for 5G

Abstract

The future fifth generation (5G) mobile communication systems are currently being developed under expectations of fulfilling various technical requirements, which include massive connectivity, high capacity, low latency and ultra-reliability. In order to achieve high capacity, operating at high frequency spectrum such as millimeter wave is considered as an appealing option, which requires more dense allocation of Transmission Reception Points (TRP). With more micro and macro TRPs deployed with small inter-site distance, cell-edge users in 5G networks may encounter strong interference from neighbor transmissions in both uplink and downlink. Successive Interference Cancelation (SIC) receivers, which are applied in 5G with Non-Orthogonal Multiple Access (NOMA), have been presented as a potential solution for heavy interference scenarios, where the performance gain can be further improved by network Interference Cancelation (IC). Motivated by the demands for improving spectral efficiency in different interference environments, this thesis addresses Radio Resource Management (RRM) optimization with network IC in specific 5G uplink and downlink scenarios. In the uplink, this thesis investigates Device-to-Device (D2D) communications. D2D pairs of transmitters and receivers share the same cellular uplink resource. Situations with and without an uplink cellular user are considered. A centralized RRM optimization algorithm is proposed where the cellular base station maximizes the network utility by adjusting all D2D and cellular users' transmission power, rate and IC configurations. Additionally, distributed RRM algorithms based on strategic games are developed. Simulation results of the centralized and the distribute algorithms show considerable gains in spectral efficiency. In the downlink, a scenario with only cellular users is considered. Each cellular user may perform SIC on one of the two strongest nearby downlink transmissions. This opens up the possibility that a cell-edge user may be served by the second nearest cell, and cancel the interference from the closest cell. This is called cell-edge inversion in this thesis. The utility of the whole network is maximized by a radio resource optimization method that is distributed among the cells. The simulation results show significant improvement of the rate of cell-edge users.