The detection and mitigation of coverage problems in cellular networks have traditionally followed a cell-level perspective, based on statistics of aggregated user equipment measurements, e.g. to ensure that a required received power level is achieved in a percentage of time and locations within the cell. However, this overall cell-level performance may not accurately capture the user-level perspective of individual users, which can experience too low received signal power during a large percentage of their connection time. This paper proposes an enhanced coverage hole detection solution that combines different types of measurements collected from multiple complementary sources to capture both cell-level and user-level perspectives. In addition, in order to mitigate the identified coverage problems, this paper proposes a solution that combines the adjustment of the base station transmitted power and the deployment of fixed relays. The results have been obtained using real measurements of the space/time user location distribution in a university campus. The presented results demonstrate that the inclusion of the individual user perspective allows the identification of coverage holes which cannot be identified with a traditional cell-level approach. Moreover, the proposed Coverage Hole mitigation solution solves the Coverage Holes in the considered scenario with a reduction around 60% in Capital and Operational Expenditures with respect to a solution based only on the deployment of fixed relays.

Radio Resource Management (RRM) strategies are essential components in mobile wireless networks, such as Long Term Evolution (LTE) or 5G New Radio (NR)[1]. The design of RRM algorithmic solutions is an area of research that has received a lot of attention for decades (see e.g. surveys [2–4] and references therein). Given that RRM strategies need to handle traffic dynamicity in the Radio Access Network (RAN), the availability of realistic user distributions in space and time can be very useful to support a more realistic performance assessment of RRM solutions. For this purpose, this article introduces a dataset containing real measurements of the number of users connected to the different Wifi Access Points (APs) at the Campus Nord facilities of the Universitat Politècnica de Catalunya (UPC) in Barcelona. The Wifi network is composed of 247 APs. To characterize the temporal variations, the data was collected for each AP every 1000 s (approximately) during 62 days. Besides the number of users connected to each AP (including users connected to both 2.4 GHz and 5 GHz bands), the dataset also contains information about the theoretical coverage area of each AP, so that the number of users connected to each AP can be associated to a specific geographical area. In this way, the dataset captures the spatio-temporal variations of users in the Campus at different times of the day, different days of the week and different periods of the academic year.

This paper aims to improve the user Quality of Service (QoS) in 5G networks by introducing a user-centric view that exploits the predictability of the user's daily motifs. An agglomerative clustering is used to identify these motifs according to the cells in which the user is camping during the day. Then, a technique to extract the personalised QoS observed by the user is proposed. The methodology is illustrated with an example that makes use of real measurements obtained from a specific customer of a 3G/4G operator. The presented results illustrate that the proposed user-centric approach is able to identify situations with poor user perceived QoS which could not be identified by a classical network-centric approach.

The optimization of third-generation mobile communication systems has become an important aspect for network operators. This paper proposes a new methodology for RF failure detection in UMTS networks based on Key Performance Indicators (KPI) which are obtained by measuring certain parameters at different network entities. With the proposed methodology possible uplink problems are identified. The proposed method has been validated with data extracted from a real UMTS network.

This paper proposes and evaluates a radio resource reservation algorithm that takes advantage of location-aware techniques in order to facilitate handovers in a WCDMA system, specially for users following straight trajectories. The mobility characteristics of these users may provide certain information about the instant of time when they require a handover process. The proposed resource reservation algorithm takes into account the user location information in order to manage the available radio resources in a more efficient way. The proposed algorithm optimizes the existing trade-off between the blocking probability of new connection requests and the dropping probability of users in handover. This optimization is obtained by minimizing the system grade of service (GoS). Moreover, the algorithm includes a prioritization of business users over consumer users. The obtained results are compared to a reference algorithm and the impact on the most important performance indicators has been analyzed, including the influence of call duration and service bit rate

This paper evaluates the impact of static and dynamic hotspots on the performance of a WCDMA network and provides certain guidelines and mechanisms in order to manage in an appropriate way the use of radio resources under non-homogeneous traffic spatial distributions. First of all, the impact of the geographical location of a static hotspot has been analysed for the forward link. Then, dynamic hotspots (i.e. hotspots that move following a certain mobility pattern) have been studied, indicating how the hotspot movement affects on the network performance. Moreover, a pilot power adjustment algorithm that equalises the base station transmission power of the hotspot cell and its adjacent cells has been proposed and analysed. The improvement provided by this pilot power adjustment algorithm has been evaluated in terms of base station transmission power, transmission power of pilot channel, dropping probability and rate of handovers per user.

The definition and assessment of suitable radio resource management (RRM) strategies able to provide a required QoS in the framework of the UTRA segment of UMTS is a key issue for achieving the expectations created on 3G technology. This paper proposes and evaluates specific algorithms for the different RRM functions involved in the uplink direction. In particular, the admission control of a new connection, the congestion control mechanisms to deal with peak interference situations and the dynamic management of the transmission parameters are studied by considering interactive-like services as a reference.