In wireless communication systems, the need to simultaneously and reliably provide multiple users with high-rate communication links leads to challenging optimization problems. Questions of cell and resource block assignment, interference, and power consumption at base station and mobile devices have to be answered in the face of time-varying frequency-selective channels. Furthermore, the heterogeneity and densification of both the users and the network infrastructure adds further complication to the network deployment. These questions and challenges can generally be formulated as resource allocation or network deployment problems. Standardizations from the Third Generation Partnership Project (3GPP) can also be incorporated in the planning of a heterogeneous network. For example Licensed Shared Access (LSA) and LTE-WLAN Aggregation (LWA) are two new theoretical solutions to the increase in data demand which can be used to optimize capacity and QoS for the end user.

Resource Allocation in Future Network Generations

This research is concerned with the modeling, analysis and solving of resource allocation problems. As the combinatorial nature of these problems is computationally prohibitive, the development of approximation techniques and algorithms plays an important practical role. By combining results from integer, convex and nonconvex optimization theory, performance estimates and bounds for these approaches can be derived.

Wireless Network Deployment and Planning

The planning of wireless networks remains a crucial and complex problem in the future not least due to rising traffic demands. The problems generally entail base station (BS) placement and traffic node (TN) assignment to BSs fulfilling the required bit rates. Moreover, inter-cell interference must also be taken into consideration for the total network setting. The power consumption of wireless networks is an important factor, not only from an ecological but also from a financial point of view. Therefore, the objective of the wireless network planning problem is to minimize the total power consumption of the network while minimizing the number of not covered TNs.

Related publications


Alireza Zamani, Kiraseya Preusser, Anke Schmeink.

© INDA at RWTH Aachen