Optimizing mobile networks in the rapidly evolving field of wireless communication is increasingly challenging due to two main issues associated with current methods. First, the technical complexity of the Radio Access Network (RAN) with multiple technologies, frequency bands, and cell sizes makes it difficult for manual processing to keep pace with the growing number of issues to be resolved. Second, network optimization usually focuses on data gathered by network equipment, i.e. base stations, and overlooks user-side information, which can offer data with better spatial precision and more accurate Quality of Service (QoS) as seen by the end user.

Millimeter-wave frequency bands pose significant challenges to cellular communications because of their increased path loss and lower robustness against signal obstruction, reflection or blocking phenomena. Beamforming is generally perceived as the most convenient solution to overcome this issue, usually relying on a combination of beam scanning and reciprocity-based precoding. However, channel reciprocity cannot be assumed in FDD spectrum bands, hence forcing initial access to rely solely on beam scanning with the subsequent impact on initial access time. This paper presents an initial access scheme applicable to FDD bands, where second-order channel statistics are exploited through digital beamforming. Link-level and Monte Carlo simulations are performed using the QuaDRiGa channel model, showing good results of the initial access time even in very low signal to noise ratio conditions.

An algorithm is proposed that computes the solution to the power control problem with closed-loop effects (L. Mendo and J.M. Hernando, 2007). Analytical and simulation results show that the algorithm converges under the same conditions as that given in the cited reference, while achieving a reduction in computational load in a wide range of conditions.

This letter presents an improved result on the negative-binomial Monte Carlo technique analyzed in a previous paper1 for the estimation of an unknown probability p. Specifically, the confidence level associated to a relative interval [p/μ2, pμ1], with μ1, μ2 > 1, is proved to exceed its asymptotic value for a broader range of intervals than that given in the referred paper, and for any value of p. This extends the applicability of the estimator, relaxing the conditions that guarantee a given confidence level.

A system-level model for power control in the uplink of direct-sequence code-division multiple access (DS-CDMA) cellular networks is presented. The model takes into account the effects of the closed loop, namely average transmit power rise, power headroom, and variable soft hand-off gains, which are not considered in existing power control models. The power control problem is analyzed in this setting, and a number of properties are derived which generalize results from the classical model without closed-loop effects. Based on this analysis, an algorithm is given that determines required transmit powers taking into account these effects. This algorithm is a generalization of classical iterative algorithms without closed-loop effects. Finally, simulation results are presented to assess the validity of the approach

In this paper, a sequential stopping rule for the estimation of a probability p by means of Monte Carlo simulation is analyzed. It is shown that the proposed estimator is almost unbiased, and guarantees a given relative precision irrespective of p. Under very mild conditions, the method also guarantees a certain confidence level for a given relative estimation error, provided that p does not exceed a maximum value. An extension to importance sampling is discussed.

This work presents a model for the uplink of CDMA networks that takes into account the effects of closed-loop power control, and proposes an assignment algorithm. The performance of this algorithm is assessed by means of simulations using the presented model. Results show that the algorithm can provide a capacity increase with respect to minimum-attenuation assignment.

An algorithm is proposed that finds the optimum assignment of mobile users to base stations, and its associated transmission powers, in a cellular direct-sequence code-division multiple-access network, with a computational complexity that grows polynomially with the number of users and base stations. The algorithm detects infeasible situations and allows the inclusion of power constraints. Its performance is analyzed in terms of complexity and system capacity.

We show how the dimension of power control equation systems can be reduced from K, the number of users in the system, to M, the number of cells, without any loss of generality or accuracy. Decentralized downlink power control algorithms are then presented which generalize previously proposed ones broadening the range of application while maintaining reduced complexity.