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This study aimed to analyse the trajectories and mortality of multimorbidity patterns in patients aged 65 to 99 years in Catalonia (Spain). Five year (2012–2016) data of 916,619 participants from a primary care, population-based electronic health record database (Information System for Research in Primary Care, SIDIAP) were included in this retrospective cohort study. Individual longitudinal trajectories were modelled with a Hidden Markov Model across multimorbidity patterns. We computed the mortality hazard using Cox regression models to estimate survival in multimorbidity patterns. Ten multimorbidity patterns were originally identified and two more states (death and drop-outs) were subsequently added. At baseline, the most frequent cluster was the Non-Specific Pattern (42%), and the least frequent the Multisystem Pattern (1.6%) . Most participants stayed in the same cluster over the 5 year follow-up period, from 92.1% in the Nervous, Musculoskeletal pattern to 59.2% in the Cardio-Circulatory and Renal pattern. The highest mortality rates were observed for patterns that included cardio-circulatory diseases: Cardio-Circulatory and Renal (37.1%); Nervous, Digestive and Circulatory (31.8%); and Cardio-Circulatory, Mental, Respiratory and Genitourinary (28.8%). This study demonstrates the feasibility of characterizing multimorbidity patterns along time. Multimorbidity trajectories were generally stable, although changes in specific multimorbidity patterns were observed. The Hidden Markov Model is useful for modelling transitions across multimorbidity patterns and mortality risk. Our findings suggest that health interventions targeting specific multimorbidity patterns may reduce mortality in patients with multimorbidity.

This paper proposes a positioning strategy for a fleet of unmanned aerial vehicles (UAVs) airlifting wireless base stations driven by communication constraints. First, two schedulers that model the distribution of resources among users within a single cell are analyzed. Then, an UAV autonomous positioning strategy is developed, based on a fair distribution of the radio resources among all the users of all the cells in a given scenario, in such a way that the user bitrate is the same regardless the users’ distribution and spatial density. Moreover, two realistic constraints are added related to capacity of the backhaul link among the UAVs and the ground station: the bitrate delivered per UAV and the total backhaul bandwidth shared among all the UAVs. Additionally, an energy consumption model is considered to evaluate the efficiency and viability of the proposed strategy. Finally, numerical results in different scenarios are provided to assess both the schedulers performance and the proposed coordinated positioning strategy for the UAVs.

This paper deals with the development of several strategies for associating users to base stations (BSs) in heterogeneous networks. These strategies are able to balance the rate among users and BSs and increase the overall network utility. Constraints related to the energy availability at BSs are considered explicitly in the design, assuming that the BSs are equipped with batteries that are recharged through energy harvesting. We develop a general association strategy, and then we present several suboptimum but less complex solutions suitable for scenarios with high mobility or deployments of BSs with low computational capabilities. We also present an implementation that is to be executed in a distributed way among users and BSs without the need of having a central entity gathering all the information. The performance of the proposed strategies is evaluated through simulations in terms of rate balancing and the effect of the energy harvesting capabilities on the network throughput is shown. We also compare the proposed strategies with the traditional max-SINR user association approach.

This paper provides a methodology for the dimensioning of the access network in remote rural areas, considering the progressive introduction of cellular services in these regions. A 3G small cell (SC) network with one or several carriers deployed at the SC, fed with solar panels and connected to a backhaul with limited capacity is considered for the analysis. Because the backhaul may be inexistent or very expensive (e.g., satellite-based backhaul) the network design pursues the minimization of the required backhaul bandwidth. The required backhaul bandwidth and the required energy units (i.e., the size of the solar panels and the required number of batteries) are then obtained as an output of the dimensioning analysis. Both the backhaul minimization objective and the constraints associated with each of the carriers (low maximum radiated power and low number of users connected simultaneously) require a novel methodology compared to the classical dimensioning techniques. We also develop a procedure for switching on/off carriers in order to minimize the energy consumption without affecting the quality of service (QoS) perceived by the users. This technique allows reducing the required size of the energy units, which directly translates into a cost reduction. In the development of this on/off switching strategy, we first assume perfect knowledge of the traffic profile and later, we develop a robust Bayesian approach to account for possible error modeling in the traffic profile information.

With the objective of improving the spectral efficiency and coverage homogeneity of wireless cellular systems in the downlink, we investigate how to take advantage of two promising transmission technologies envisioned in current standards: network-MIMO and relay stations (RSs). It is assumed that half-duplex RSs are deployed in a cellular system, where the duration of the relay-receive and the relay-transmit phases is fixed beforehand for all cells. In order to reduce the spectral efficiency loses associated to half-duplex relaying, we propose the use of base station (BS) cooperation under a network-MIMO precoding strategy based on block-diagonalization zero-forcing, and optimize radio resources under the convex performance criteria constrained by the per-BS power, modulation and coding schemes and the transmission rate in the relay-transmit phase. By applying convex optimization techniques, the optimal precoding strategy is derived and a suboptimal low complexity solution is also proposed. The obtained solutions are evaluated at system level and compared to other cooperative and non-cooperative BS-based schemes.

We evaluate the costs in the deployment of a 4G relay-assisted network in the 2.6 GHz band following a technoeconomic methodology that departs from cell dimensioning based on spectral efficiency and outage capacity requirements. Different decode-and-forward relaying protocols are considered in the analysis, assuming a certain traffic load evolution over a period of ten years, different geotypes, and a progressive deployment of base stations and relay stations. Results show significant benefits for operators as well as reduction in the total radiated power.