Abstract-In this work, we study the problem of allocating resources in a multi-service cellular network aiming at maximizing the total system rate while providing suitable Quality of Experience (QoE) to the network users. In our formulation, we try to satisfy at least a certain number of users per service plan, which is an important constraint from the mobile network operators' perspective. We manage to reformulate this nonlinear optimization problem as an Integer Linear Problem (ILP), that can be solved by standard methods. However, due to the exponentially high complexity to solve large instances of this problem, we propose and evaluate a suboptimal algorithm with a much lower complexity, called Rate Maximization under Experience Constraints (RMEC), whose main idea is to divide the problem into three smaller subproblems with reduced complexity. By means of computational simulations, we show that our proposed algorithm presents a near optimal performance and outperforms the state-of-art solution of the literature.

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Abstract-We formulate the resource and power assignment problem of maximizing the spectral efficiency of a wireless system subject to user satisfaction constraints in the multiservice scenario. We show that although this optimization problem is nonlinear, it can be converted to an integer linear program. In this way, standard techniques can be used to obtain the optimal solution. Motivated by the high computational complexity of the optimal solution, we propose a fast suboptimal algorithm. Simulation results show that our proposal achieves near-optimal performance in low and medium loads with a much lower computational complexity compared with the algorithm used to obtain the optimal solution. Therefore, our proposed algorithm achieves a good tradeoff between performance and computational complexity. We also show that the addition of adaptive power allocation renders significant performance gains in the considered scenario.Index Terms-Multiservice, quality of service (QoS), rate maximization, resource and power assignment.

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The Dual Connectivity (DC) technology has gained a lot of momentum in the LTE Release 12 as a means to enhance the per-user throughput and provide mobility robustness. Some studies in the literature have discussed the interworking between the LTE and the air interface of the upcoming Fifth Generation (5G) in a DC scenario. That integration may provide some benefits to meet the high throughput, reliability and availability requirements of the 5G networks. This work firstly presents a brief overview of the DC technology considering the integration between 4G e 5G. Then, we highlight some open issues and challenges for future investigation involving Radio Resource Management (RRM) in such a scenario, which includes: (i) user-cell association, (ii) interaction between base stations and (iii) resource allocation. After that, we propose an extension of a utility-based resource allocation algorithm for DC scenarios. Finally, a performance evaluation is conducted in multi-Radio Access Technology (RAT) LTE-NR scenarios considering the bearer split configuration of the DC technology, where the gains provided by the proposed algorithm are demonstrated.

In this paper, a new stochastic channel model (SCM) is proposed for fifth-generation (5G) systems. By means of the sum-of-sinusoids (SoS) method to generate spatially consistent random variables (SCRVs), the proposed model extends the 3rd Generation Partnership Project (3GPP)-SCM by considering three important features for accurate simulations in 5G, i.e., support for dual mobility, spatial correlation at both ends of the link and considerable reductions of the required memory consumption when compared with existing models. A typical problem presented in existing channel models, namely the generation of uncorrelated large scale parameters (LSPs) and small scale parameters (SSPs) for close base stations (BSs), is solved, then allowing for more realistic numerical evaluations in most of the 5G scenarios characterized by a large density of BSs and user equipments (UEs) per unit of area, such as ultra-dense networks (UDNs), indoor environments, device-to-device (D2D) and vehicular-to-vehicular (V2V). The proposed model emerges as the first SCM, and therein lower complexity when compared with ray-tracing (RT)based models, that comprises all the following features: support for single and dual mobility with spatial consistency, smooth time evolution, dynamic modeling, large antenna array, frequency range up 100 GHz and bandwidth up to 2 GHz. Some of the features are calibrated for single mobility in selected scenarios and have shown a good agreement with the calibration results found in the literature.