Shadowed Rician model is considered to be the most appropriate that is used to characterize the impairments seen in wireless channels, which suffer Line-Of-Sight (LOS) shadowing and small-scale fading. In this model, the Probability Density Function (PDF) of the Signal to Noise Ratio (SNR) per symbol needs numerical solutions to be evaluated. More than that, for some values of the fading parameters, the numerical solution converging too slowly, and so needs too much time to be evaluated. This is considered as a problem in real time applications where delay is a critical issue. In this paper, the authors present and prove approximations for Shadowed Rician model according to the values of the fading parameters, which are the Rice factor and the Shadowing standard deviation. With the proposed approximation, the required PDF could be written in intervals which make it easier to calculate at parameters values that causes slow converging.
Expanding network capacity and guaranteeing the Quality of Service (QoS) are significant goals in fifth-Generation (5G) for high densities of mobile terminals. Femtocell-based 5G is an essential radio access technology that meets the exponentially increasing demand. Femtocells have emerged as an efficient solution for improving the capacity and coverage of wireless cellular networks, especially, for indoor wireless users. However because of the limited wireless radio resources, resource allocation is a key issue in femtocell networks. Motivated by this challenge in this study, we propose an efficient resource allocation approach that satisfies the QoS requirements for High-Priority (HP) users while serving Best-Effort (BE) users effectively as possible. The user differentiation strategy ensures the QoS guarantee uponthe priority level of each user. We consider major metrics for performance evaluation which are: the rate of rejected users, throughput satisfaction rate, spectrum spatial reuse and fairness. Dedicated simulations prove that our proposal outperforms one of the most effective techniques in the literature.
In this paper, we propose two algorithms for joint power allocation and bit-loading in multicarrier systems using discrete modulations. The objective is to maximize the data rate under the constraint of a suitable Bit Error Rate per subcarrier. The first algorithm is based on the Lagrangian Relaxation of the discrete optimization problem in order to find an initial solution. A discrete solution is found by bit truncation followed by an iterative modulation adjustment. The second algorithm is based on Discrete Coordinate Ascent framework with iterative modulation increment of one selected subcarrier at each iteration. A simple cost function related to the power increment per bit is used for subcarrier selection. A sub-optimal low complexity Discrete Coordinate Ascent algorithm is proposed that overcome the limitations of the Hughes-Hartogs algorithm. The Lagrangian Relaxation algorithm provides a suboptimal solution for non-coded system using M-QAM modulations, whereas the low complexity Discrete Coordinate Ascent algorithm provides a near optimal solution for coded as well as for non-coded system using an arbitrary modulation set. Numerical results show the efficiency of the proposed algorithms in comparison with traditional methods.
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