The WinProp software has been added to the Electromagnetic Solver FEKO. WinProp includes sophisticated ray-optical and empirical wave propagation models for computing the radio coverage as well as for the radio channel analysis. The supported scenarios range from large rural or suburban areas to dense urban city centers, and even complex indoor scenarios can be predicted. For the detailed network planning modules for almost all air interfaces (incl. LTE, WLAN) are available, which compute the overall signal and interference situation by superposing the contributions from multiple transmitting sites.

Wave propagation and radio network planning software WinProp added to the electromagnetic solver package FEKO

The trials and rollout of the fifth generation (5G) network technologies are gradually intensifying as 5G is positioned as a platform that not only accommodates exploding data traffic but also unlocks a multitude use cases, services and deployment scenarios. However, the need for hyperdense 5G deployments is revealing some of the limitations of planning approaches that hitherto proved adequate for pre-5G systems. The hyperdensification envisioned in 5G networks not only adds complexity to network planning and optimization problems, but underlines need for more realistic data-driven approaches that consider cost, varying demands and other contextual attributes to produce feasible topologies. Furthermore, the quest for network programmability and automation including the 5G radio access network (RAN), as manifested by network slicing technologies and more flexible RAN architectures, are also among other factors that influence planning and optimization frameworks. Collectively, these deployment trends, technological developments and evolving (and diverse) service demands point towards the need for more holistic frameworks. This article proposes a data-driven multiobjective optimization framework for hyperdense 5G network planning with practical case studies used to illustrate added value compared to contemporary network planning and optimization approaches. Comparative results from the case study with real network data reveal potential performance and cost improvements of hyperdense optimized networks produced by the proposed framework due to increased use of contextual data of planning area and focus on objectives that target demand satisfaction.

/pdf/a-data-driven-multiobjective-optimization-framework-for-4hyqnokh5t.pdf

A Data-Driven Multiobjective Optimization Framework for Hyperdense 5G Network Planning

In this paper, a novel method to simulate radio propagation is presented. The method consists of two steps: automatic 3D scenario reconstruction and propagation modeling. For 3D reconstruction, a machine learning algorithm is adopted and improved to automatically recognize objects in pictures taken from target region, and 3D models are generated based on the recognized objects. The propagation model employs a ray tracing algorithm to compute signal strength for each point on the constructed 3D map. By comparing with other methods, the work presented in this paper makes contributions on reducing human efforts and cost in constructing 3D scene; moreover, the developed propagation model proves its potential in both accuracy and efficiency.

/pdf/a-novel-method-for-radio-propagation-simulation-based-on-5gdfd5oc2g.pdf

A novel method for radio propagation simulation based on automatic 3D environment reconstruction

The deployment of low-power small cells is envisaged as the main driver to accommodate the mobile broadband traffic growth in cellular networks. Depending on the spatial distribution of the user traffic, a densification of the small cells may be required in confined areas. However, deploying more and more cells in given areas may imply an increase of the inter-cell interference among the small cells. This study aims at investigating if the inter-cell interference among outdoor small cells may represent an impairment to the user experience, and evaluates if and in what conditions the interference coordination is worthwhile compared to the universal frequency reuse. Results show that the inter-cell interference depends on the small cell deployment in the urban environment (e.g. streets and squares) and on the network load condition. In case of deployment along urban streets, the inter-cell interference does not affect the user throughput and no interference coordination is required. On the other hand, if deployed in open areas (e.g. city squares) the interference coordination enhances both average and coverage user throughput in case of high network load condition.

/pdf/the-inter-cell-interference-dilemma-in-dense-outdoor-small-2m34t88fcj.pdf

The Inter-Cell Interference Dilemma in Dense Outdoor Small Cell Deployment

Enhanced intercell interference coordination (eICIC) is a key ingredient in boosting the performance of cochannel heterogeneous networks. eICIC encompasses two main techniques: almost blank subframes (ABS), during which the macrocell remains silent to reduce the interference; and biased user association to offload more users to the picocells. However, its application to realistic irregular deployments raises a number of research questions. In this paper, we investigate the operation of eICIC in a realistic deployment based on 3-D data from a dense urban European capital area. Rather than the classical semistatic and network-wise configuration, the importance of having highly dynamic and distributed mechanisms that are able to adapt to local environment conditions is revealed. We propose two promising cell association algorithms: one aiming at pure load balancing and an opportunistic approach exploiting the varying cell conditions. Moreover, an autonomous fast distributed muting algorithm is presented, which is simple, robust, and well suited for irregular network deployments. Performance results for realistic network deployments show that the traditional semistatic eICIC configuration leads to modest gains, whereas the set of proposed fast dynamic eICIC algorithms results in capacity gains on the order of 35%–120%, depending on the local environment characteristics. These attractive gains, together with the simplicity of the proposed solutions, underline the practical relevance of such schemes.

/pdf/dynamic-enhanced-intercell-interference-coordination-for-2g0al6qsn6.pdf

Dynamic Enhanced Intercell Interference Coordination for Realistic Networks

With the growing interest for broadband mobile services in mobile communication networks, the investigation of radio transmission in and into buildings is getting more important. Popular empirical and deterministic models for the propagation inside buildings compute the field strength based on the inner structure of the buildings (walls, furniture). But for current and future wireless networks (3G, B3G, WLAN, WiMax,..), the neighboring buildings must also be considered to avoid interference problems in these buildings. Additionally the indoor coverage of outdoor transmitters must be analyzed to guarantee a high QoS even inside buildings. A new concept for the prediction of the field strength in such hybrid scenarios (urban and indoor) is presented in this paper. This new concept does not rely only on the direct ray (like empirical models) and it does not consider hundreds of rays for a single radio link (like ray tracing). The new model focuses on the most dominant path between transmitter and receiver. It allows the computation of the transition from an urban to an indoor scenario and vice versa, thus allowing an accurate computation of the received power inside and around buildings. The new model is validated with various measurements and shows a good accuracy.

G. Wolfle

Papers

Combined urban and indoor network planning using the dominant path propagation model