Terahertz (THz) communications is envisaged as one of the key enablers for beyond fifth-generation (5G) wireless networks because of its massive bandwidth opportunities. However, wireless transmission at such high frequencies comes with its own challenges, including the increased power consumption and hardware complexity, the challenging task of channel estimation, as well as the strong impact of phase noise (PN). In this work, we consider coherent and noncoherent transmission techniques based on spatial modulation (SM) for the THz channel with PN impairments. SM schemes carry part of the information by the baseband modulated symbols and part by the used antenna or subarray index. Our investigations show that the index detection in the SM chain remains robust against the strong PN impairment, unlike the symbol detection which deteriorates as the modulation order increases. The robustness of index detection under PN coupled with low modulation order renders SM an attractive candidate for THz communications. Under strong PN, space-shift keying (SSK) schemes, i.e., SM schemes which solely transmit index information, are preferable.

The standardization of the fourth generation of mobile communication systems was mainly driven by the demands for higher data-rates and improved Quality of Service. To reach these goals interference coordination has been identified as a promising research field for better exploitation of the time and frequency resources. This paradigm shift from interference avoidance to interference coordination is also reflected in the ongoing enhancement of the 4th generation of mobile communication systems such as 3GPP Long Term Evolution. In this context, numerous investigations have focused on the allocation of precoding matrices that are part of the link adaptation process by some form of base station (eNB) coordination. Within this work we develop a non-centralized interference coordination scheme by noticing that the re-allocation of a precoding matrix can lead to an uncontrolled change of the interference level at users located in neighboring cells, especially at the edge. To this end, we provide a fully closed form mathematical framework describing these changes. Based on this, we derive a simple metric that improves the precoding matrix selection process in the User Equipment with the result that interference changes can be reduced without having any standard impact. This novel scheme can also be seen as an extension to previous inter-cell interference coordination schemes without the need of base-station cooperation.

Base station cooperation in the downlink of cellular systems has been recently suggested as a promising concept towards a better exploitation of the communication system's physical resources. It may offer a high gain in capacity through interference mitigation. This however, comes at a cost of high information exchange between cooperating entities and a high computational burden. Clustering of base stations into subgroups is an alternative to guarantee such cooperation benefits in a lower scale. The optimal definition of clusters, however, and a systematic way to find a solution to such problem is not yet available. In this work, we highlight the combinatorial nature of the problem, exploit this to describe the system of users and base stations as a graph and formulate a pure 0-1 program. Its solution suggests a cost optimal way to form clusters and assign user subsets to them.

Coordinated Multipoint (CoMP) transmission technique is one method to improve performance of cellular wireless systems, e.g. LTE Advanced, by cooperation of cells for reducing interference and increasing SINR of users in weak radio conditions, e.g. located at cell edge. In this paper, we present an adaptive clustering algorithm to dynamically adjust the cooperation sets of a CoMP system to the UE perceived signal strength in order to maximize the overall system performance while avoiding major system architecture modifications. We show that additional gain in SINR could be achieved compared to non UE-aware fixed cluster with limited increase of system complexity, for a practical adaptive CoMP clustering scheme performing not far from an upper bound UE-specific scheme.