Cell-free massive multiple-input multiple-output (CF-mMIMO) is an advanced variant of network multiple-input multiple-output (MIMO) which considers absence of cell boundaries. Thus, the interference between cells in cellular systems is greatly minimised and the system s coverage capacity is improved due to the shorter distances between the access points (APs) and the users. It is a multi-user massive MIMO communications solution that involves an extended number of APs that can either be equipped with MIMO or single antennas to provide service to users simultaneously. The APs are controlled by a central processing unit (CPU) to ensure coordination within the network and for information processing and decoding. Possible arrangements for the CF-mMIMO architecture include, but are not limited to: centralized and decentralized schemes. In this thesis, the uplink of a CF-mMIMO system architecture is studied for the centralized and decentralized implementations. In particular, we study the performance of interference mitigation techniques for CF-mMIMO networks using iterative detection and decoding (IDD) schemes. The performance of the system is studied assuming perfect and imperfect channel state information (CSI). Access point selection based on the effective channel gain to make the network more practical and scalable are devised. The use of low-density parity check (LDPC) codes that adopt message passing has been investigated. Furthermore, log likelihood ratio (LLR) refinement strategies have been proposed to improve decentralized processing for CF-mMIMO networks. Finally, the performance of the considered schemes is analyzed theoretically and simulations are used to assess the performance in terms of BER, number of fronthaul signaling, and computational cost.